Patent Publication Number: US-2022223275-A1

Title: System and method for remote optimization of medical procedures and technologies

Description:
BACKGROUND OF THE INVENTION 
     According to data from the National Center for Health Statistics, nearly fifty (50) million surgical inpatient procedures were performed in 2009 in the United States alone, and that number continues to grow. Optimization of those procedures is crucial for medical practitioner efficiency, patient safety, and team workflow. Additionally, the number of clinical trials is also on the rise, and it is important that new medical procedures, products (such as drugs and biologics), and devices are thoroughly accurately tested, and the results evaluated. For example, according to data from the National Library of Medicine (https://clinicaltrials.gov), there were over 360,000 registered studies in December 2020, up from only about 2,100 at the end of 2000. 
     Clinical trials may be complex studies that stretch out over a long period of time. When conducting a clinical trial, the medical practitioners and professionals involved must carefully log data and report that data when the trial is complete. Additionally, patient safety is a primary concern and precautions should be taken to minimize risk. Many regulatory and government agencies (for example, the Food and Drug Administration (FDA), Center for Disease Control and Prevention (CDC), and National Institutes of Health (NIH)), as well as private companies (such as pharmaceutical and medical device companies) have an interest in the performance of clinical trials and their outcomes, and could perhaps provide valuable insights, but collaboration during clinical trials can be difficult or cost-prohibitive because of technology shortcomings or travel costs. Likewise, these entities may also have an interest in optimization of new medical procedures, such as the use and implantation of a newly approved prosthetic or other implantable device. Again, however, remote collaboration may not be possible. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
       The accompanying figures, where like reference numerals refer to identical or functionally similar elements throughout the separate views, together with the detailed description below, are incorporated in and form part of the specification, and serve to further illustrate embodiments of concepts that include the claimed invention and explain various principles and advantages of those embodiments. 
         FIG. 1  is a block diagram of an exemplary medical procedure system in accordance with some embodiments. 
         FIG. 2  is a block diagram of an optimization system in accordance with some embodiments. 
         FIG. 3  is a block diagram of a communication device for use within the optimization system of  FIG. 2  in accordance with some embodiments. 
         FIG. 4  is a block diagram of a mixed reality device for use within the optimization system of  FIG. 2  in accordance with some embodiments. 
         FIG. 5  is a block diagram of an optimization computing device for use within the optimization system of  FIG. 2  in accordance with some embodiments. 
         FIG. 6  is a flow diagram of a method for use in medical procedure optimization in accordance with some embodiments. 
         FIG. 7  is a flow diagram of a method of medical procedure optimization in accordance with some embodiments. 
         FIG. 8  is a functional block diagram of a medical procedure optimization system in accordance with some embodiments. 
         FIG. 9  is a flow diagram of a method of extended continuous procedure optimization using the functionality of  FIG. 8  in accordance with some embodiments. 
         FIG. 10  is a functional block diagram of a method for medical procedure room information exchange in accordance with some embodiments. 
         FIG. 11  illustrates a system for remote optimization of medical procedures and technologies in accordance with some embodiments. 
         FIG. 12  is a flow diagram of a method for remote optimization of medical procedures and technologies in accordance with some embodiments. 
     
    
    
     Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention. 
     The apparatus and method components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. 
     DETAILED DESCRIPTION OF THE INVENTION 
     In an embodiment, a system for remote optimization of a medical technology is described. The system comprises a plurality of optimization systems for optimizing at least one medical technology, each of the plurality of optimization systems is configured to acquire, via a mixed reality device, data associated with one or more attributes of operation of the respective medical technology. The plurality of optimization systems is further configured to obtain medical information associated with the one or more attributes of operation of the respective medical technology. Further, the plurality of optimization systems is further configured to analyze the obtained medical information and the acquired data to optimize the operation of the respective medical technology and determine data associated with one or more predefined parameters related to the optimized operation of the respective medical technology. The system further comprises a remote medical technology optimization system communicatively coupled to the plurality of optimization systems, the remote medical technology optimization system configured to obtain from each of the one or more optimization systems, the data associated with the one or more predefined parameters related to the optimized operation of the respective medical technology. The remote medical technology optimization system is configured to analyze the obtained data associated with the one or more predefined parameters related to optimized operation of the respective medical technology and determine an optimized data associated with the one or more predefined parameters for optimal operation of the medical technology based on the analyzed data. 
     A method for remote optimization of a medical technology is described. The method comprises acquiring, by a plurality of optimization systems, via a mixed reality device, data associated with one or more attributes of operation of the respective medical technology. The method further comprises obtaining, by the plurality of optimization systems, medical information associated with the one or more attributes of operation of the respective medical technology. The method further comprises analyzing, by the plurality of optimization systems, the obtained medical information and the acquired data to optimize the operation of the respective medical technology. The method further comprises determining, by the plurality of optimization systems, data associated with one or more predefined parameters related to the optimized operation of the respective medical technology. The method further comprises obtaining, by a remote medical technology optimization system, from each of the one or more optimization systems, the data associated with the one or more predefined parameters related to the optimized operation of the respective medical technology. Further, the method comprises analyzing, by the remote medical technology optimization system, the obtained data associated with the one or more predefined parameters related to optimized operation of the respective medical technology, and determining an optimized data associated with the one or more predefined parameters for optimal operation of the medical technology based on the analyzed data. 
     Referring now to  FIG. 1 , a block diagram of an exemplary medical procedure system (hereinafter interchangeably referred to a medical technology system)  100  is shown. In one embodiment, the medical procedure system  100  generally includes a medical procedure room  102  and an optimization system  104 . The configuration of the medical procedure room  102  and/or optimization system  104 , including physical placement of components, inventory and supplies, medical equipment used, medical personnel  130  involved, networking of equipment, and other characteristics may be referred to as a medical procedure room setup and is indicated in  FIG. 1  with reference number  106 . The medical procedure room  102  shown in  FIG. 1  is a non-limiting example of a medical procedure system  100 , and it will be understood that the systems and methods disclosed herein are not limited to the number, type, placement, and configuration of items of equipment, components, medical personnel  130 , and/or other elements shown. Additionally, although shown within the medical procedure room  102  in  FIG. 1 , it will be understood that one or more of the items of equipment, components, medical personnel  130 , and/or other elements of the medical procedure room setup  106  may be physically located outside or external to the walls of the room  102  and still be considered to be part of the medical procedure room setup  106 . 
     Continuing to refer to  FIG. 1 , in one non-limiting example, the medical procedure room  102  may include a medical procedure table  108 , one or more auxiliary tables or stands  110  (such as a Mayo stand), one or more storage closets or rooms  112 , nurse workstations  114 , back tables  116 , anesthesia systems  118 , electrocautery systems,  120 , enabling technology systems or workstations  122  (for example, but not limited to, microscopes, robotic surgical systems, networked robotics, illumination systems, or the like, and accompanying monitors or displays), user input devices  124  (such as mobile devices, or tablets, or any communication device now known or in the future developed), biometric readers  126 , and/or wireless transceivers  128 , as well as medical personnel  130  (for example, but not limited to, surgical technicians, surgical team members (such as medical doctors and nurses), and anesthesiologists). In some embodiments, at least one member of medical personnel  130  wears a mixed reality device  132  during the medical procedure (hereinafter interchangeably referred to as medical technology), and each mixed reality device  132  is in wireless and/or wired communication with the optimization system  104 . As noted above, it will be understood that the medical procedure system  100  and medical procedure room setup  106  is not limited to those items shown in  FIG. 1 , and may include any number of items of equipment, electronic devices, imaging devices, surgical robots or other systems, lights, or any other devices and/or supplies preferred or required by the medical practitioner and/or other medical personnel  130 . 
     Continuing to refer to  FIG. 1 , the exemplary medical procedure room setup  106  may be a preferred medical procedure room setup of the practitioner performing the medical procedure, based on the type of procedure, number of medical procedure room personnel, available room layout and dimensions, and other factors. As discussed in greater detail below, the layout of the preferred medical procedure room setup  106  may be uploaded or input into the optimization system  104  and may be displayed to a medical practitioner and/or medical personnel  130  through one or more mixed reality devices  132  of the optimization system  104 . Further, in one embodiment, inventory of disposable items, chargeable items, and/or items that will remain in the patient is also uploaded or input into the optimization system  104  for tracking, analysis, and/or inventory management. In one embodiment, the optimization system  104  may suggest, or at least partially suggest, to the medical practitioner and/or medical personnel  130  an optimized medical procedure room setup  106 , amount and type of inventory and items of medical equipment, and other characteristics to enhance efficiency of the medical procedure. For example, such suggestions may be based at least in part on user input and/or data collected by the optimization system  104  from previous medical procedures (hereinafter interchangeably referred to as reference medical technologies) of the same type or in the same medical procedure room. Additionally, or alternatively, each practitioner&#39;s preferred medical procedure room layout for each procedure may be stored in the optimization system  104  as a default setup and suggested to a user and/or the practitioner when planning a new setup for the same or similar medical procedure. As the medical practitioner, medical personnel  130 , and/or other user of the optimization system  104  performs each step of the procedure and uses, moves, or removes each item of equipment and/or inventory, such activity is logged by the optimization system  104  for later analysis, inventory replenishment, education, procedural support, or other purposes. 
       FIG. 2  is a block diagram of an optimization system  104  in accordance with some embodiments. Specifically, the optimization system of  FIG. 2  may be the optimization system  104  of  FIG. 1 . The optimization system  104  provides for medical practitioner specific room organization, set up, supply, logistics, tracking and performance across surgical and medical procedures with features for augmented reality, artificial intelligence and machine learning, as will be described further in accordance with some embodiments hereinbelow. As shown, the optimization system  104  includes one or more communication devices  124 , one or more mixed reality devices  132  at least one optimization computing device  206 , a network  210 , and one or more remote connections  208 . 
     The optimization computing device  206  may be communicatively coupled to, and receive information from, the one or more communication devices  124 , the one or more mixed reality devices  132  and the one or more remote connections  208 . Communication between the optimization computing device  206  and various components can occur through the network  210 . In some embodiments, the network  210  is, for example, a wide area network (WAN) (for example, a transport control protocol/internet protocol (TCP/IP) based network), a cellular network, or a local area network (LAN) employing any of a variety of communications protocols as is well known in the art. 
     Each of the one or more communication devices  124  operates as a user interface for one or more medical procedure room personnel as will be further described with respect to  FIG. 3 . 
     Each of the one or more mixed reality devices  132  further operates as a user interface for one or more medical procedure room personnel as will be further described with respect to  FIG. 4 . 
     The one or more remote connections  208  interact with the optimization computing device  206  via the network  210  to receive and provide information external to the medical procedure room  102 . The one or more remote connections  208  may be one or more distribution agents incorporated within the optimization system  104  or independently connected. The distribution agents may include, for example, but are not limited to, one or more of buyers, purchasing groups, pharmacies, anesthetic components, sterile processing departments (SPD), cleaning, storage, management, and/or any equivalent general processing department. The one or more remote connections  208  further may be one or more collaborators, via one or more collaborator devices (shown in  FIG. 11 ) which may be technology collaborators or specialist collaborators and the like. The collaborators for example may include, but are not limited to, one or more of radiology, anesthesiology, fluoroscopy, electrophysiology, robotic and navigational systems, x-ray equipment techs, and the like. The one or more remote connections  208  may be one or more educators including, for example, but not limited to researchers, universities, training facilities, clinical trials, and the like. 
     In some embodiments the one or more remote connections  208  comprise one or more local or remote practitioners, via one or more devices, receiving, exchanging and transmitting electrophysiologic data for the purpose of interpreting and monitoring electrophysiological responses such as somatosensory evoked potentials, brainstem auditory evoked potentials, motor evoked potentials, electromyography or other neurological monitoring methodologies, providing timestamps linked to field data for step of a procedure and to provide patient safety information linking the adverse effect to a specific tool application or action, and linking it to the remedy. For example, the one or more remote connections  208  may include technicians to observe, log, track, identify and transmit procedure specific information to industry specialists who support enabling technology, medical implants, devices, and implants conferring the ability for remote industry support reducing the burden of personnel in the procedure room environment. 
     In operation, the optimization computing device  206  optimizes the organization, preparation, and set up of a medical procedure space for efficient and predictable execution of one or more medical procedures. The optimization computing device  206 , in some embodiments, operates to optimize pre-preparation of a procedure, orientation of medical personnel  130  for a procedure, and location and identification of equipment for a procedure. 
       FIG. 3  is a block diagram of one exemplary embodiment of a communication device  124  for use within the optimization system  104  of  FIG. 2  in accordance with some embodiments. The communication device  124  is electrically and/or communicatively connected to a variety of other devices and databases as previously described with respect to  FIG. 2  herein. In some embodiments, the communication device  124  includes a plurality of electrical and electronic components, providing power, operational control, communication, and the like within the communication device  124 . For example, in one embodiment, the communication device  124  includes, among other things, a communication device transceiver  302 , a communication device user interface  304 , a communication device network interface  306 , a communication device processor  308 , a communication device memory  310 , and one or more communication device sensors  320 . 
     It should be appreciated by those of ordinary skill in the art that  FIG. 3  depicts the communication device  124  in a simplified manner and a practical embodiment may include additional components and suitably configured logic to support known or conventional operating features that are not described in detail herein. It will further be appreciated by those of ordinary skill in the art that the communication device  124  may be a personal computer, desktop computer, tablet, smartphone, wearable device (wrist worn, eye worn, and the like), or any other computing device now known or in the future developed. It will further be appreciated by those of ordinary skill in the art that the communication device  124  alternatively may function within a remote server, cloud computing device, or any other remote computing mechanism now known or in the future developed. 
     The components of the communication device  124  (for example  302 ,  304 ,  306 ,  308  and  310 ) are communicatively coupled via a communication device local interface  318 . The communication device local interface  318  may be, for example but not limited to, one or more buses or other wired or wireless connections, as is known in the art. The communication device local interface  318  may have additional elements, which are omitted for simplicity, such as controllers, buffers (caches), drivers, repeaters, and receivers, among many others, to enable communications. Further, the communication device local interface  318  may include address, control, and/or data connections to enable appropriate communications among the aforementioned components. 
     The communication device processor  308  is a hardware device for executing software instructions. The communication device processor  308  may be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with the communication device processor  308 , a semiconductor-based microprocessor, or generally any device for executing software instructions. When the communication device  124  is in operation, the communication device processor  308  is configured to execute software stored within the communication device memory  310 , to communicate data to and from the communication device memory  310 , and to generally control operations of the communication device  124  pursuant to the software instructions. 
     The communication device user interface  304  may be used to receive user input from and/or for providing system output to the user or to one or more devices or components. User input may be provided via, for example, a keyboard, touch pad, and/or a mouse. System output may be provided via a display device, speakers, and/or a printer (not shown). The communication device user interface  304  may further include, for example, a serial port, a parallel port, an infrared (IR) interface, a universal serial bus (USB) interface and/or any other interface herein known or in the future developed. 
     The communication device network interface  306  may be used to enable the communication device  124  to communicate on a network, such as the network  210  of  FIG. 2 , a wireless access network (WAN), a radio frequency (RF) network, and the like. The communication device network interface  306  may include, for example, an Ethernet card or adapter or a wireless local area network (WLAN) card or adapter. Additionally, or alternatively the communication device network interface  306  may include a radio frequency interface for wide area communications such as Long-Term Evolution (LTE) networks, or any other network now known or in the future developed. The communication device network interface  306  may include address, control, and/or data connections to enable appropriate communications on the network. 
     The communication device memory  310  may include any non-transitory memory elements comprising one or more of volatile memory elements (for example, random access memory (RAM), nonvolatile memory elements (for example, read only memory “ROM”), and combinations thereof. Moreover, the communication device memory  310  may incorporate electronic, magnetic, optical, and/or other types of storage media. Note that the communication device memory  310  may have a distributed architecture, where various components are situated remotely from one another, but can be accessed by the communication device processor  308 . The software in the communication device memory  310  may include one or more software programs, each of which includes an ordered listing of executable instructions for implementing logical functions. The software in the communication device memory  310  includes a suitable communication device operating system  314  and one or more communication device applications  316 . The communication device operating system  314  controls the execution of other computer programs, such as the one or more communication device applications  316 , and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The one or more communication device applications  316  may be configured to implement the various processes, algorithms, methods, techniques, and the like. described herein. 
     The communication device memory  310  further includes a communication device data storage  312  used to store data. In the exemplary embodiment of  FIG. 3 , the communication device data storage  312  is located internal to the communication device memory  310  of the communication device  124 . Additionally, or alternatively (not shown), the communication device data storage  312  may be located external to the communication device  124  such as, for example, an external hard drive connected to the communication device user interface  304 . In a further embodiment (not shown), the communication device data storage  312  may be located external and connected to the communication device  124  through a network and accessed via the communication device network interface  306 . 
     In operation, information for storage in the communication device data storage  312  may be entered via the communication device user interface  304 . Alternatively, information for storage in the communication device data storage  312  may be received from the optimization computing device  206 , the mixed reality devices  132 , or the remote connections  208  via the communication device transceiver  302 . Alternatively, information for storage in the communication device data storage may be received from one or more sensors (not shown) external to the communication device  124  via the communication device transceiver  302 . Alternatively, information for storage in the communication device data storage  312  may be received from one or more communication device sensors  320 . For example, tutorials, room layouts, inventory, checklists, and the like may be stored in the communication device data storage  312 . Medical personnel  130  can create, revise, or refine medical, procedure, and inventor notes as appropriate using the communication device user interface  304  to store new information in the communication device data storage  312 . 
     The communication device  124  in the exemplary example includes the communication device transceiver  302 . The communication device transceiver  302  incorporating within a communication device transceiver antenna (not shown), enables wireless communication from the communication device  124  to, for example, the optimization computing device  206  and the network  210  of  FIG. 2 . It will be appreciated by those of ordinary skill in the art that the communication device  124  may include a single communication device transceiver  302  as shown, or alternatively separate transmitting and receiving components, for example but not limited to, a transmitter, a transmitting antenna, a receiver, and a receiving antenna. 
     The communication device  124  in the illustrated example includes one or more communication device sensors  320 . It will be appreciated by those of ordinary skill in the art that the one or more communication device sensors  320  may be of any sensor technology now known or in the future developed. For example, the one or more communication device sensors  320  may be IoT (Internet of Things) sensors, RFID (radio frequency identification) sensors, image sensors, light based (lidar) sensors, biometric sensors, printed sensors, wearable sensors, and optical image sensors. IoT sensors include temperature sensors, proximity sensors, pressure sensors, RF (radio frequency) sensors, pyroelectric IR (infrared) sensors, water-quality sensors, chemical sensors, smoke sensors, gas sensors, liquid-level sensors, automobile sensors and medical sensors. 
     Each of the one or more communication device sensors  320  comprise a detector allowing the monitoring and control of various parameters within the medical procedure room, for example, environmental parameters (temperature, humidity, carbon dioxide, and the like.), technological processes (automation, robotics, materials analysis, and the like.), and/or biometric tracking (movement, health contextual conditions, and the like.). More specifically, the one or more communication device sensors  320  may provide personal fitness monitoring of a user of the communication device  124 , a patient, and/or any other personnel associated with the medical procedure room. Alternatively, the one or more communication device sensors  320  may provide automation such as security, lighting, energy management, and access control for the medical procedure room. Alternatively, the one or more communication device sensors  320  may provide monitoring of the various devices and equipment associated with the medical procedure room. Alternatively, the one or more communication device sensors  320  may provide haptic or proprioception inputs, such as via accelerometers or bionic exoskeleton style components, which assess relative position of mechanical components of a joint or prosthesis or robotic arm, applicator device and the like. In operation, the one or more communication device sensors  320  communicate with one another, with other sensors within the medical procedure room, and/or with any other device within or external to the medical procedure room. For example, although not illustrated, the one or more communication device sensors  320  may communicate directly or indirectly with sensors implanted within a patient. 
       FIG. 4  is a block diagram of one exemplary embodiment of a mixed reality device  132  for use within the optimization system  104  of  FIG. 2  in accordance with some embodiments. The mixed reality device  132  may provide a virtual reality interface in which a computer-simulated reality electronically replicates an environment with which a user may interact. In some embodiments, the mixed reality device  132  may provide an augmented reality interface in which a direct or indirect view of real-world environments in which the user is currently disposed are augmented (for example, supplemented, by additional computer-generated sensory input such as sound, video, images, graphics, Global Positioning System (GPS) data, or other information). In still other embodiments, the mixed reality device  132  may provide a mixed reality interface in which electronically generated objects are inserted in a direct or indirect view of real-world environments in a manner such that they may co-exist and interact in real time with the real-world environment and real-world objects. It will be appreciated by those of ordinary skill in the art that the mixed reality device  132  may comprise any mixed reality or virtual reality technology now known or in the future developed. 
     The mixed reality device  132  is electrically and/or communicatively connected to a variety of other devices and databases as previously described with respect to  FIG. 2  herein. In some embodiments, the mixed reality device  132  includes a plurality of electrical and electronic components, providing power, operational control, communication, and the like within the mixed reality device  132 . For example, the mixed reality device  132  in one embodiment includes, among other things, a mixed reality device transceiver  402 , a mixed reality device user interface  404 , a mixed reality device network interface  406 , a mixed reality device processor  408 , a mixed reality device memory  410 , and one or more mixed reality device sensors  424 . 
     It should be appreciated by those of ordinary skill in the art that  FIG. 4  depicts the mixed reality device  132  in a simplified manner and a practical embodiment may include additional components and suitably configured logic to support known or conventional operating features that are not described in detail herein. It will further be appreciated by those of ordinary skill in the art that the mixed reality device  132  may be a head-mounted display device in the form of eyeglasses, goggles, a helmet, a visor, or any other mixed reality device eyewear now known or in the future developed. It will further be appreciated by those of ordinary skill in the art that the mixed reality device  132  generates and/or displays virtual reality images, mixed reality images, and/or augmented reality images. In the mixed reality device  132 , a scene produced on a display device can be oriented or modified based on user input. The mixed reality device  132  provides a visual image in which real world and virtual world objects are presented together within a single display. It will be appreciated by those of ordinary skill in the art that although the embodiments herein are illustrated with a mixed reality device, alternative embodiments within the scope include a virtual reality device or an augmented reality device. 
     The components of the mixed reality device  132  (for example  402 ,  404 ,  406 ,  408  and  410 ) are communicatively coupled via a mixed reality device local interface  418 . The mixed reality device local interface  418  may be, for example but not limited to, one or more buses or other wired or wireless connections, as is known in the art. The mixed reality device local interface  418  may have additional elements, which are omitted for simplicity, such as controllers, buffers (caches), drivers, repeaters, and receivers, among many others, to enable communications. Further, the mixed reality device local interface  418  may include address, control, and/or data connections to enable appropriate communications among the aforementioned components. 
     The mixed reality device processor  408  is a hardware device for executing software instructions. The mixed reality device processor  408  may be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with the mixed reality device processor  408 , a semiconductor-based microprocessor, or generally any device for executing software instructions. When the mixed reality device  132  is in operation, the mixed reality device processor  408  is configured to execute software stored within the mixed reality device memory  410 , to communicate data to and from the mixed reality device memory  410 , and to generally control operations of the mixed reality device  132  pursuant to the software instructions. 
     The mixed reality device user interface  404  may be used to receive user input from and/or for providing system output to the user or to one or more devices or components. The mixed reality device user interface  404  may include one or more input devices, including but not limited to a navigation key, a function key, a microphone, a voice recognition component, joystick or any other mechanism capable of receiving an input from a user, or any combination thereof. Further, mixed reality device user interface  404  may include one or more output devices, including but not limited to a speaker, headphones, display, or any other mechanism capable of presenting an output to a user, or any combination thereof. In some embodiments, the mixed reality device user interface  404  includes a user interface mechanism such as a touch interface or gesture detection mechanism that allows a user to interact with the display elements of the mixed reality device display  422  or projected into the eyes of the user. 
     As illustrated, a mixed reality device display  422  may be a separate user interface or combined within the mixed reality device user interface  404 . The mixed reality device display  422  may provide a two dimensional or three-dimensional image visible to the wearer of the mixed reality device  132 . The mixed reality device display  422  may be, for example, a projection device for displaying information such as text, images, or video received from the optimization computing device  206 , communication devices  124 , and/or remote connections  208  via the network  210  of  FIG. 2 . 
     The mixed reality device user interface  404  may further include, for example, a serial port, a parallel port, an infrared (IR) interface, a universal serial bus (USB) interface and/or any other interface herein known or in the future developed. 
     The mixed reality device network interface  406  may be used to enable the mixed reality device  132  to communicate on a network, such as the network  210  of  FIG. 2 , a wireless access network (WAN), a radio frequency (RF) network, and the like. The mixed reality device network interface  406  may include, for example, an Ethernet card or adapter or a wireless local area network (WLAN) card or adapter. Additionally, or alternatively the mixed reality device network interface  406  may include a radio frequency interface for wide area communications such as Long-Term Evolution (LTE) networks, or any other network now known or in the future developed. The mixed reality device network interface  406  may include address, control, and/or data connections to enable appropriate communications on the network. 
     The mixed reality device memory  410  may include any non-transitory memory elements comprising one or more of volatile memory elements (for example, random access memory (RAM), nonvolatile memory elements (for example, read only memory, “ROM”), and combinations thereof. Moreover, the mixed reality device memory  410  may incorporate electronic, magnetic, optical, and/or other types of storage media. Note that the mixed reality device memory  410  may have a distributed architecture, where various components are situated remotely from one another, but can be accessed by the mixed reality device processor  408 . The software in the mixed reality device memory  410  may include one or more software programs, each of which includes an ordered listing of executable instructions for implementing logical functions. The software in the mixed reality device memory  410  includes a suitable mixed reality device operating system  414  and one or more mixed reality device applications  416 . The mixed reality device operating system  414  controls the execution of other computer programs, such as the one or more mixed reality device applications  416 , and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The one or more mixed reality device applications  416  may be configured to implement the various processes, algorithms, methods, techniques, and the like. described herein. 
     The mixed reality device memory  410  further includes a mixed reality device data storage  412  used to store data. In the exemplary embodiment of  FIG. 4 , the mixed reality device data storage  412  is located internal to the mixed reality device memory  410  of the mixed reality device  132 . Additionally, or alternatively, (not shown) the mixed reality device data storage  412  may be located external to the mixed reality device  132  such as, for example, an external hard drive connected to the mixed reality device user interface  404 . In a further embodiment, (not shown) the mixed reality device data storage  412  may be located external and connected to the mixed reality device  132  through a network and accessed via the mixed reality device network interface  406 . 
     In operation, information for storage in the mixed reality device data storage  412  may be entered via the mixed reality device user interface  404 . In some embodiments, the mixed reality device data storage  412  stores data received by an augmented reality interface  420  which, for example, recognizes and registers the spatial characteristics of a medical procedure room. 
     Alternatively, information for storage in the mixed reality device data storage  412  may be received from the optimization computing device  206 , the communication devices  124 , or the remote connections  208  via the mixed reality device transceiver  402 . Alternatively, information for storage in the mixed reality device data storage  412  may be received from one or more sensors (not shown) external to the mixed reality device  132  via the mixed reality device transceiver  402 . Alternatively, information for storage in the mixed reality device data storage  412  may be received from one or more mixed reality device sensors  424 . For example, tutorials, room layouts, inventory, checklists, and the like may be stored in the mixed reality device data storage  412 . Medical personnel  130  can create, revise, or refine medical, procedure, and inventor notes as appropriate using the mixed reality device user interface  420  to store new information in the mixed reality device data storage  412 . 
     The mixed reality device  132  in the exemplary example includes the mixed reality device transceiver  402 . The mixed reality device transceiver  402  incorporating within a mixed reality device transceiver antenna (not shown), enables wireless communication from the mixed reality device  132  to, for example, the optimization computing device  206  and the network  210  of  FIG. 2 . It will be appreciated by those of ordinary skill in the art that the mixed reality device  132  may include a single communication device transceiver  302  as shown, or alternatively separate transmitting and receiving components, for example but not limited to, a transmitter, a transmitting antenna, a receiver, and a receiving antenna. 
     The mixed reality device  132  in the illustrated example includes one or more mixed reality device sensors  424 . It will be appreciated by those of ordinary skill in the art that the one or more mixed reality device sensors  424  may be of any sensor technology now known or in the future developed. For example, the one or more mixed reality device sensors  424  may be IoT (Internet of Things) sensors, RFID (radio frequency identification) sensors, image sensors, light based (lidar) sensors, biometric sensors, printed sensors, wearable sensors, and optical image sensors. IoT sensors include temperature sensors, proximity sensors, pressure sensors, RF (radio frequency) sensors, pyroelectric IR (infrared) sensors, water-quality sensors, chemical sensors, smoke sensors, gas sensors, liquid-level sensors, automobile sensors and medical sensors. 
     Each of the one or more mixed reality device sensors  424  comprise a detector allowing the monitoring and control of various parameters within the medical procedure room, for example, environmental parameters (temperature, humidity, carbon dioxide, and the like.), technological processes (automation, robotics, materials analysis, and the like.), and/or biometric tracking (movement, health contextual conditions, and the like.). More specifically, the one or more mixed reality device sensors  424  may provide personal fitness monitoring of a user of the mixed reality device  132 , a patient, and/or any other personnel associated with the medical procedure room. Alternatively, the one or more mixed reality device sensors  424  may provide automation such as security, lighting, energy management, and access control for the medical procedure room. Alternatively, the one or more mixed reality device sensors  424  may provide monitoring of the various devices and equipment associated with the medical procedure room. Alternatively, the one or more mixed reality device sensors  424  may provide haptic or proprioception inputs, such as via accelerometers or bionic exoskeleton style components, which assess relative position of mechanical components of a joint or prosthesis or robotic arm, applicator device and the like. In operation, the one or more mixed reality device sensors  424  communicate with one another, with other sensors within the medical procedure room, and/or with any other device within or external to the medical procedure room. 
       FIG. 5  is a block diagram of one exemplary embodiment of an optimization computing device  206  for use within the optimization system  104  of  FIG. 2 . Specifically, the optimization computing device  206  can implement the various methods described herein. 
     The optimization computing device  206  is electrically and/or communicatively connected to a variety of other devices and databases as previously described with respect to  FIG. 2  herein. In some embodiments, the optimization computing device  206  includes a plurality of electrical and electronic components, providing power, operational control, communication, and the like within the optimization computing device  206 . For example, the optimization computing device  206  in one embodiment includes, among other things, an optimization computing device transceiver  502 , an optimization computing device user interface  504 , an optimization computing device network interface  506 , an optimization computing device processor  508 , an optimization computing device memory  510 , and one or more optimization computing device sensor(s)  522 . 
     It should be appreciated by those of ordinary skill in the art that  FIG. 5  depicts the optimization computing device  206  in a simplified manner and a practical embodiment may include additional components and suitably configured logic to support known or conventional operating features that are not described in detail herein. It will further be appreciated by those of ordinary skill in the art that the optimization computing device  206  may be a personal computer, desktop computer, tablet, smartphone, or any other computing device now known or in the future developed. 
     It will further be appreciated by those of ordinary skill in the art that the optimization computing device  206  alternatively may function within a remote server, cloud computing device, or any other remote computing mechanism now known or in the future developed. For example, the optimization computing device  206  in some embodiments may be a cloud environment incorporating the operations of the optimization computing device processor  508 , the optimization computing device memory  510 , the optimization computing device user interface  504 , and various other operating modules to serve as a software as a service model for the communication devices  124  and the mixed reality devices  132 . 
     The components of the optimization computing device  206  (for example  502 ,  504 ,  506 ,  508  and  510 ) are communicatively coupled via an optimization computing device local interface  518 . The optimization computing device local interface  518  may be, for example but not limited to, one or more buses or other wired or wireless connections, as is known in the art. The optimization computing device local interface  518  may have additional elements, which are omitted for simplicity, such as controllers, buffers (caches), drivers, repeaters, and receivers, among many others, to enable communications. Further, the optimization computing device local interface  518  may include address, control, and/or data connections to enable appropriate communications among the aforementioned components. 
     The optimization computing device processor  508  is a hardware device for executing software instructions. The optimization computing device processor  508  may be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with the optimization computing device processor  508 , a semiconductor-based microprocessor, or generally any device for executing software instructions. When the optimization computing device  206  is in operation, the optimization computing device processor  508  is configured to execute software stored within the optimization computing device memory  510 , to communicate data to and from the optimization computing device memory  510 , and to generally control operations of the optimization computing device  206  pursuant to the software instructions. 
     The optimization computing device user interface  504  may be used to receive user input from and/or for providing system output to the user or to one or more devices or components. User input may be provided via, for example, a keyboard, touch pad, and/or a mouse. System output may be provided via a display device, speakers, and/or a printer (not shown). The optimization computing device user interface  504  may further include, for example, a serial port, a parallel port, an infrared (IR) interface, a universal serial bus (USB) interface and/or any other interface herein known or in the future developed. 
     The optimization computing device network interface  506  may be used to enable the optimization computing device  206  to communicate on a network, such as the network  210  of  FIG. 2 , a wireless access network (WAN), a radio frequency (RF) network, and the like. The optimization computing device network interface  506  may include, for example, an Ethernet card or adapter or a wireless local area network (WLAN) card or adapter. Additionally, or alternatively the optimization computing device network interface  506  may include a radio frequency interface for wide area communications such as Long-Term Evolution (LTE) networks, or any other network now known or in the future developed. The optimization computing device network interface  506  may include address, control, and/or data connections to enable appropriate communications on the network. 
     The optimization computing device memory  510  may include any non-transitory memory elements comprising one or more of volatile memory elements (for example, random access memory (RAM), nonvolatile memory elements (for example, read only memory “ROM”), and combinations thereof. Moreover, the optimization computing device memory  510  may incorporate electronic, magnetic, optical, and/or other types of storage media. Note that the optimization computing device memory  510  may have a distributed architecture, where various components are situated remotely from one another, but can be accessed by the optimization computing device processor  508 . The software in the optimization computing device memory  510  may include one or more software programs, each of which includes an ordered listing of executable instructions for implementing logical functions. The software in the optimization computing device memory  510  includes a suitable optimization computing device operating system  514  and optimization programming code  512 . The optimization computing device operating system  514  controls the execution of other computer programs, such as the optimization program code  512 , and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The optimization program code  512  may be configured to implement the various processes, algorithms, methods, techniques, and the like described herein. 
     The optimization computing device memory  510  further includes an optimization computing device data storage  516  used to store data. In the exemplary embodiment of  FIG. 5 , the optimization computing device data storage  516  is located internal to the optimization computing device memory  510  of the optimization computing device  206 . Additionally, or alternatively, (not shown) the optimization computing device data storage  516  may be located external to the optimization computing device  206  such as, for example, an external hard drive connected to the optimization computing device user interface  504 . In a further embodiment, (not shown) the optimization computing device data storage  516  may be located external and connected to the optimization computing device  206  through a network and accessed via the optimization computing device network interface  506 . 
     The optimization computing device data storage  516 , in accordance with some embodiments, stores optimization data  520  for operational use in the various processes, algorithms, methods, techniques, and the like. described herein. In operation, information for storage in the optimization computing device data storage  516  may be entered via the optimization computing device user interface  504 . Alternatively, information for storage in the optimization computing device data storage  516  may be received from the mixed reality devices  132 , the communication devices  124 , or the remote connections  208  via the optimization computing device transceiver  502 . Alternatively, information for storage in the optimization computing device data storage  516  may be received from one or more sensors (not shown) external to the optimization computing device  206  via the optimization computing device transceiver  502 . Alternatively, information for storage in the optimization computing device data storage  516  may be received from one or more optimization computing device sensors  522 . For example, tutorials, room layouts, inventory, checklists, and the like may be stored in the optimization computing device data storage  516 . Medical personnel  130  can create, revise, or refine medical, procedure, and inventor notes as appropriate using the optimization computing device user interface  504  to store new information in the optimization computing device data storage  516 . 
     The optimization computing device  206  in the exemplary example includes the optimization computing device transceiver  502 . The optimization computing device transceiver  502  incorporating within an optimization computing device transceiver antenna (not shown), enables wireless communication from the optimization computing device  206  to, for example, one or more communication devices  124 , one or more mixed reality devices  132 , and the network  210 . It will be appreciated by those of ordinary skill in the art that the optimization computing device  206  may include a single optimization computing device transceiver as shown, or alternatively separate transmitting and receiving components, for example but not limited to, a transmitter, a transmitting antenna, a receiver, and a receiving antenna. 
     The optimization computing device  206  in the illustrated example includes one or more optimization computing device sensors  522 . Each of the one or more optimization computing device sensors  522  comprise a detector allowing the monitoring and control of various parameters within the medical procedure room, for example, environmental parameters (temperature, humidity, carbon dioxide, and the like.), technological processes (automation, robotics, materials analysis, and the like), and/or biometric tracking (movement, health contextual conditions, and the like). More specifically, the one or more optimization computing device sensors  522  may provide personal fitness monitoring of a user of the optimization computing device  206 , a patient, and/or any other personnel associated with the medical procedure room. Alternatively, the one or more optimization computing device sensors  522  may provide automation such as security, lighting, energy management, and access control for the medical procedure room. Alternatively, the one or more optimization computing device sensors  522  may provide monitoring of the various devices and equipment associated with the medical procedure room. Alternatively, the one or more optimization computing device sensors  522  may provide haptic or proprioception inputs, such as via accelerometers or bionic exoskeleton style components, which assess relative position of mechanical components of a joint or prosthesis or robotic arm, applicator device and the like. In operation, the one or more optimization computing device sensors  522  communicate with one another, with other sensors within the medical procedure room, and/or with any other device within or external to the medical procedure room. 
       FIG. 6  is a flow diagram of a method for medical procedure optimization in accordance with some embodiments. Specifically,  FIG. 6  is a flow diagram for an initial setup program  600  of a medical procedure optimization in accordance with some embodiments. The initial setup program  600 , for example, may be implemented within the optimization program code  512  of  FIG. 5 . In an alternative embodiment, the initial setup program  600  may be implemented as a cloud-based internet program accessed via the communication devices  124  and the optimization computing device  206 . In yet another alternative embodiment, the initial setup program  600  can be distributively implemented within a system in which the various components are remotely located from each other in other embodiments. For example, a first set of components of the initial setup program  600  may be implemented and stored within the optimization computing device  206 , a second set of components of the initial setup program  600  may be implemented and stored within one or more of the communication devices  124 , a third set of components of the initial setup program  600  may be implemented and stored within one or more of the mixed reality devices  132 , and/or a fourth set of components of the initial setup program  600  may be implemented and stored within other devices connected to the network  210  or otherwise communicatively coupled to the optimization computing device  206 , the communication devices  124 , and the mixed reality devices  132 . It will be appreciated that any and all distribution arrangements of the initial setup program  600  are within the scope of the claimed invention herein. 
     It will be appreciated by those of ordinary skill in the art that the flow diagram of  FIG. 6  is simply an exemplary embodiment and other alternative process flows are within the scope of the claimed invention herein. 
     In operation, the optimization computing device processor  508  accesses and executes the initial setup program  600 . As illustrated in  FIG. 6 , the initial setup program  600  begins with the receipt of various inputs and information to process an initial medical procedure setup. For example, the optimization computing device  206  receives user input at its optimization computing device user interface  504 , stores the information within the user input in the optimization computing device data storage  516 , and accesses the optimization program code  512  by the optimization computing device processor  508  for executing initial setup program  600 . Alternatively, the communication device  124  receives user input including setup information at its communication device user interface  304 , sends the information via its communication device network interface  306  through the network  210  to the optimization computing device  206 . The optimization computing device  206  thereafter receives the information via its optimization computing device network interface  506 , stores the information within the user input in the optimization computing device data storage  516 , and accesses the optimization program code  512  by the optimization computing device processor  508  for executing initial setup program  600 . It will be appreciated that the information may originate from and be received through various alternative methods in accordance with some embodiments. 
     Referring to  FIG. 6 , the initial setup program  600  begins generally with a new profile at operation  602  including creating a profile at operation  604  followed by email confirmation at operation  606 . The initial setup program  600  thereafter proceeds to or alternatively begins with a login at operation  608 . Next, in operation  610  a creator portal opens and displays. Next, in one embodiment, an edit to the medical procedure room occurs at operation  612 . For example, the edit to the medical procedure room includes one or more of change in the available room layout and dimensions, change in position of the items corresponding to one or more of the medical devices, consumables, general tray, and equipment in the medical procedure room. Thereafter, the edited room is saved at operation  614 . Alternatively, from operation  610 , a new medical procedure room is created at operation  616 . For instance, the new medical procedure room is created by providing required layout and dimensions for the new medical procedure room. It will be appreciated that the required layout and dimensions can be provided by using various techniques, such as but not limited to, uploading images of the medical procedure room. In some embodiments, the created new medical procedure room or the edited room is assigned a medical procedure room identifier. Thereafter, or after operation  614 , the medical practitioner input is received and saved in operation  618 . In accordance with various embodiments, the medical practitioner input may include the medical practitioner identifier, such as but not limited to, the name, the ID, or the like of the medical practitioner. Next, a procedure input is received and saved in operation  620 . In accordance with various embodiments, the procedure input may include the procedure identifier, such as but not limited to, the name, the ID, or the like of the medical procedure. In operation  622  a room canvas is created. In accordance with various embodiments, the room canvas is created based on previous medical procedure room setups that are associated with the received medical practitioner input, the procedure input, or the edited/new medical room. The room canvas of operation  622  next includes creating consumables in operation  624 , creating medical devices in operation  625 , creating a general tray in operation  626  and creating equipment lists in operation  628 . 
     It will be appreciated that in some embodiments, along with the information of room canvas created in  622 , the data entered in operations  628 ,  624 ,  625 , and  626  precisely configures a given medical practioner&#39;s room organization for a given procedure. For example, the data entered in operations  628 ,  624 ,  625 , and  626 , in some embodiments, identifies inventory of fixed equipment, external enabling technology system  122  such as microscopes, drills, fluoroscopy units, navigation systems, robotic systems, lights, electrophysiology systems, anesthetic systems, vacuum and gas management and operating room back table. Similarly, the data entered in operations  628 ,  624 ,  625 , and  626 , in some embodiments, identifies surgical instruments, reusable and disposable. For example, the data entered in operations  628 ,  624 ,  625 , and  626 , in some embodiments, identifies medical devices including pharmaceutical devices, implants, generators, stimulators, screws, plates, cages, arthroplasty joint replacement devices, heart valves, stents, coils, pacemakers, portals, biologics, catheters, and shunts. Similarly, the data entered in operations  628 ,  624 ,  625 , and  626 , in some embodiments, identifies chargeable resources/items such as sutures, sponges, clips, medical implants, screws, rods, arthroplasty devices, stimulators, needles, scalpel blades, and drill bits. Similarly, the data entered in operations  628 ,  624 ,  625 , and  626 , in some embodiments, identifies pharmaceutical resources such as medications, anesthetics, antibiotics, cardiac drugs, blood pressure drugs, sedatives, paralytic agents, pain management, and the like. 
     Continuing with  FIG. 6 , thereafter, in operation  630  all the items corresponding to the medical devices, consumables, general tray, and equipment&#39;s from the previous one or more operations, or the previous medical procedures are accessed from a searchable index/list in operation  630 . For example, in some embodiments, preference cards for each medical practitioner&#39;s preferences and procedures are preloaded for access during the initial setup procedure  600 . 
     Next, in operation  632 , the items are populated in operation  632 . For example, in one embodiment the items are populated using a drag and drop method. In an embodiment, the data associated with usage, such as but not limited to, sequence of use, pattern of use, instructions for use, priority of use of one or more of an item, a tool, and/or equipment during the medical procedure is also provided. It will be appreciated that any suitable method can be used for operation  632 . Next in operation  634 , the items are placed in the medical procedure room virtually. Thereafter, the placement is confirmed in operation  636  or alternatively, edits are completed in operation  640  and cycled back through operations  630 ,  632 , and  634  until confirmation in operation  636  occurs. 
     Lastly, in operation  638 , the room configuration, data and all other information associated with the medical practitioner for the particular procedure are stored. It will be appreciated, that the room configuration, data, and information may be stored within one or more of the optimization computing device memory  510 , one or more of the communication device memory  310 , one or more of the mixed reality device memory  410  or any combination thereof. 
     Upon completion of the initial setup program  600 , the stored medical practitioner specific and procedure specific room configuration, data, and information would provide medical personnel  130  whose responsibility is to organize, prepare and set up a medical procedure space with specific detail to best organize, optimize and prepare the space for efficient and predictable execution of that procedure for that medical practitioner. It will be further appreciated that, in some embodiments, although not illustrated in  FIG. 6 , additional patient specific information may be entered and stored. It will further be appreciated that the initial setup created and stored can be used hereinafter to create a three-dimensional mixed reality map of the medical procedure room  102  with items, tools, consumables, and equipment placement based on medical practitioner and procedure preference. 
       FIG. 7  is a flow diagram of a method for medical procedure optimization in accordance with some embodiments. Specifically,  FIG. 7  is a flow diagram of a medical procedure initial setup  700 . The medical procedure initial setup  700 , for example, may be implemented within the mixed reality device applications  416  of  FIG. 4 . In an alternative embodiment, the medical procedure initial setup  700  may be implemented as a cloud-based internet program accessed by one or more of the mixed reality devices  132 . In yet another alternative embodiment, the medical procedure initial setup  700  can be distributively implemented within a system in which the various components are remotely located from each other in other embodiments and accessed by one or more of the mixed reality devices  132 . It will be appreciated that any and all distribution arrangements of the medical procedure initial setup  700  are within the scope of the claimed invention herein. 
     It will be appreciated by those of ordinary skill in the art that the flow diagram of  FIG. 7  is simply an exemplary embodiment and other alternative process flows are within the scope of the claimed invention herein. 
     In operation, the mixed reality device processor  408  accesses and executes the medical procedure initial setup  700 . As illustrated in  FIG. 7 , the medical procedure initial setup  700  begins with the receipt of various inputs and information to process an initial medical procedure setup  106 . For example, the mixed reality device  132  receives user input at its mixed reality device user interface  404 , stores the information within the user input in the mixed reality device data storage  412 , and accesses the mixed reality device applications  416  by the mixed reality device processor  408  for executing the medical procedure initial setup  700 . Alternatively, the communication device  124  receives user input including setup information at its communication device user interface  304 , sends the information via its communication device network interface  306  through the network  210  to the mixed reality device  132 . The mixed reality device  132  thereafter receives the information via its mixed reality device network interface  406 , stores the information within the user input in the mixed reality device data storage  412 , and accesses the mixed reality device applications  416  by the mixed reality device processor  408  for executing the medical procedure initial setup  700 . It will be appreciated that the information may originate from and be received through various alternative methods in accordance with some embodiments. 
     Referring to  FIG. 7 , the medical procedure initial setup  700  begins generally with a new profile at operation  702  including creating a profile at operation  704  followed by email confirmation at operation  706 . The medical procedure initial setup  700  thereafter proceeds to or alternatively begins with a login at operation  708 . Next, in operation  710  an experience portal opens and displays. In some embodiments, the experience portal is displayed on the mixed reality device display  422 , providing, for example, a mixed reality representation of the medical procedure environment. 
     Next, in operation  712 , a medical practitioner identifier (for example a medical practitioner) is selected from a list of medical practitioner identifiers. Next, in operation  714  a procedure identifier is selected from a list of procedures. Once the medical practitioner identifier and the procedure identifier have been selected, a medical procedure room  102  is identified. For example, in one embodiment the medical procedure room identifier is obtained by scanning a Quick Response code (“QR code”) representing the medical procedure room  102  at operation  716 . 
     With knowledge of the medical practitioner, the procedure, and the medical procedure room, the operation next auto places consumables in operation  718 , auto places medical devices in operation  719 , auto places the general tray in operation  720 , auto places the equipment in  722 , along with any auto placements related to the medical procedure room, procedure, and medical practitioner. It will be appreciated by those of ordinary skill in the art that any and all tangible items now known or later discovered for use in the particular procedure may be auto placed by the method  700 . As previously described herein, the medical practitioner, procedure, and associated auto placements may be stored in one or more of the mixed reality device data storage  412 , the communication device data storage  312 , the optimization computing device data storage  516 , a cloud-based memory accessed by one or more of the mixed reality devices  132 , or any other associated memory communicatively coupled to the mixed reality device  132 . In other words, representations in visual mixed reality format specific to a given medical practitioner for a given procedure may be stored in one or more data storage devices. In this manner, the medical procedure initial setup  700  may provide preference cards for each medical practitioner&#39;s preferences and procedures pre-loaded for predictive planning and education on each procedure step by step from start to finish. 
     The medical procedure initial setup  700  continues with operation  730  wherein a medical procedure room map is rendered. For example, the room map may be rendered on the mixed reality device display  422  for visual access. Thereafter, in operation  738  a searchable index is accessed, and lastly in operation  740  the tool/tray is highlighted For example, in one embodiment, the inputted data would be mixed reality expressed by one or more of mixed reality interface augmented reality glasses/goggles/headpieces. 
     The previously described operations of the medical procedure initial setup  700  is completed during a setup time  724 . Further, a medical procedure  732  is completed during a procedure time  726 . In accordance with various embodiments, the data related to usage of one or more of the item, the equipment, or device is acquired during the procedure time  726 . Lastly an implant count  734  and a consumable count  736  are identified and stored during a transitional time  728 . 
     The medical procedure initial setup  700  provides for configuration, organization and three-dimensional planning of the geometric space of the medical procedure room environment for a given medical practitioner for a given procedure. Specifically, the mixed reality device display, for example, a holograph glass system, may create a virtual three-dimensional environment for the entire operating organization field for a specific medical practitioner, and a specific procedure and for a specific patient, enabling complete data control and digitally managed integration of data of equipment for each specific procedure for each specific patient, with extreme precision of inventory use, control, management, performance, tracking and billing sales control and accuracy. 
     In one example, once the medical procedure initial setup  700  is completed, a medical personnel  130 , such as a surgical technician, would be able to look through the glasses and see mixed reality representation of each medical instrument, device or inventory item, and identify exactly where on the field it would be placed, what number of devices would be placed, what the device was called, and ultimately provide for instrument or device placement, identification, tracking registration and analytics, and ultimately inventory management. Disposable instruments or medical implants/devices would be able to be logged in for inventory at this step and converted to charge after application or use at the end of the procedure. 
       FIG. 8  is a functional block diagram of a system of medical procedure optimization in accordance with some embodiments. Specifically,  FIG. 8  illustrates an optimization functional block diagram  800  utilizing artificial intelligence in a continuous loop system of optimization in accordance with some embodiments. The optimization functional block diagram  800 , in some embodiments, may be implemented within the optimization system  104  as described previously herein. Specifically, the optimization functional block diagram  800 , in some embodiments, illustrates the optimization of preparation of a procedure, steps and order of steps of a procedure, orientation of medical personnel  130  for a procedure, and location and identification of equipment for a procedure. The real-time feedback and training of the optimization functional block diagram  800  allows for optimized efficiency and reduction of unnecessary steps throughout medical procedures. It will be appreciated that the optimization functional block diagram  800  in operation enables identification of experience based predictive data for performance, safety, outcome efficiency and inventory control/management for one or more procedures. 
     Module  802  implements a procedure set up. For example, in operation, the module  802  may implement medical technology as described hereinbefore for  FIGS. 1 through 7 . In accordance with various embodiments, the medical technology may correspond to a medical procedure, a medical procedure room set up, a tool, an item, or an equipment. In an embodiment, the module  802  is configured to obtain a medical procedure input for one or more attributes of operation of the medical technology associated with one or more of a medical practitioner identifier, a medical procedure identifier, and a medical procedure room identifier. The one or more attributes of operation of the medical technology may include usage of one or more of the item, the equipment, the tool, and an enabling technology system  122  and/or attributes associated with set up of one or more of the item, the equipment, the tool, and the enabling technology systems  122  in the medical procedure room set up. For example, the medical procedure input corresponding to the one or more attributes of operation of the medical technology may include one or more of steps for operation of the medical procedure, order of steps for operation of the medical procedure, instructions for one or more steps for operation of the medical procedure. Similarly, the medical procedure input corresponding to the attributes associated with set up of one or more of the item, the equipment, the tool, and enabling technology systems  122  in the medical procedure room set up may include count of one or more of the item, the tool, the enabling technology system  122 , or the equipment, geographical positioning of the one or more of the item, the tool, the enabling technology system  122 , or the equipment, geographical positioning of medical personnel  130 , priority of use of the one or more of the item, the tool, the enabling technology system  122 , or the equipment, and the like. The medical procedure input corresponding to the one or more attributes associated with one or more of the item, the tool or the equipment may include usage, geographical positioning, orientation, count of the respective item, tool, or equipment. 
     In some embodiments, the procedure set up of module  802  is implemented for a specific medical practitioner&#39;s preference for a particular procedure in a particular medical procedure room  102 . For example, the data stored in the data module  810  may include pre-stored preference information for each medical practitioner&#39;s preferences and procedures. Medical personnel  130 , in operation, utilize the medical practitioner specific, procedure specific, room specific data stored in the data module  810  to organize, prepare and set up a medical procedure with specific detail to best organize, optimize and prepare for efficient and predictable execution of that procedure. It will be appreciated that the medical practitioner specific, procedure specific, room specific data stored in the data module  810  allows for medical practitioners and medical personnel  130  to best organize and optimize efficient and predictable execution of a procedure. For example, the procedure setup may include a layout and orientation of where each medical practitioner and medical procedure room personnel will be positioned during the medical procedure. Further, the procedure set up may include detailed steps and instructions for each step of the procedure process. 
     Information from the procedure module  802  feeds into the data module  810  and also feeds into a procedure input module  804 . 
     In some embodiments, the module  802  is configured to provide virtual image guidance, via one or more mixed reality devices, for operation of the medical technology based on the received at least one medical procedure input. In an embodiment, the virtual guidance is provided via a three-dimensional reality map reflecting one or more of the steps for operation of the medical technology, the order of steps for operation of the medical technology, the instructions for one or more steps for operation of the medical procedure, positioning and/or set up of the one or more of the item, the tool, the enabling technology system  122  or the equipment, and the like, in accordance with the received input. 
     In operation, the procedure set up of module  802  includes utilization of one or more mixed reality devices  132 . The one or more mixed reality devices  132  provide the ability to use virtual image guidance for procedure set up and execution. In some embodiments, the one or more mixed reality devices  132  provide a work-flow chart for a given procedure, for a given medical practitioner, providing an interactive real time checklist for execution of that procedure, registering outline, order, sequence, steps completed, steps pending, and organization management for execution of that procedure, and ultimately provide data for optimization of future evolutions of procedural performance. 
     In some embodiments, the one or more mixed reality devices  132  provide integration of multimedia data management, acquisition and expression from secondary enabling medical technologies, such as operating microscope, fluoroscope, navigational system, robotic system, endoscopic system, for that medical practitioner, for that procedure for the purpose of audiovisual data management and expression, given patient confidentiality standards. 
     In some embodiments, the one or more mixed reality devices  132  further produce customizable three-dimensional templates for training other team members for optimal procedure set ups that reduce unnecessary time wasted. 
     The one or more mixed reality devices  132  further may provide for instrument tray recognition and back table recognition for pre-planned procedure tray placement reducing setup times and turnover times between and during medical procedures. The one or more mixed reality devices  132  may also provide for instrument tray three-dimensional view of tray and expansion ability in order to picture virtual images of all instruments inside of tray without opening. In an embodiment, the instruments are Network Intelligent Operating Room Equipment having the ability for tracking, counting virtually through object recognition with names and purpose with detailed explanations. Tracking instruments in this way will provide less personnel training and provide a guide for limited passing throughout procedures. Using pre-populated lists stored in the data module  810  of exact instruments needed for each specific medical procedure and specific location provides for most efficient and lean practices. The one or more mixed reality devices  132  allows instrumentation to be viewed at all angles to become more familiar with functionality and how each tool works and assembles as well as dissembles. 
     The data stored in data module  810  may include, but is not limited to, medical procedure room organization, setup, logistics, performance, inventory and the like. Specifically, the data stored in data module  810  includes one or more of the data stored in the communication device data storage  312 , the mixed reality device data storage  412 , and the optimization data  520  stored in the optimization computing device data storage  516 , all as described previously herein. 
     The data stored in the data module  810 , may also include, for example, technique guides on instrumentation and various equipment used for each procedure preloaded for real-time feedback and training that will optimize efficiency and reduce unnecessary steps throughout procedures that will overall provide a safer environment to patient care. The data stored in the data module  810 , may also include, for example, tutorial education for each instrument and each medical procedure tray by name and its purpose for use in medical procedure for real-time feedback, support or training. It will be appreciated that stored video tutorials for anatomy and physiology for a medical procedure will reduce time in training personnel for new procedures and cut down on redundancy and overall reduce risk factors and improve safety for patient care and healthcare providers. In general, the data stored in the data module  810  provides for predictive planning and education on each procedure step by step from start to finish. In an exemplary embodiment, the data module  810  is configured to store one or more of technique guides or tutorials associated with the execution of one or more steps of the medical procedure, setups of one or more of the item, the tool, the enabling technology system  122 , or the equipment in the medical procedure room, storing of one or more of the item, the tool, the enabling technology system  122 , or the equipment in the medical procedure room, and the like. In some embodiments, the data module  810  is also configured to store data associated with one or more steps of the medical procedure previously performed by the medical practitioner corresponding to the medical practitioner identifier. Similarly, the data module  810  is also configured to store data associated with one or more previous medical procedure room setups used by the medical practitioner corresponding to the medical practitioner identifier. Similarly, one or more previous medical procedures performed and/or medical procedure room set up in a medical procedure room is recorded, associated with the medical procedure room identifier and stored in the data module  810 . Similarly, each of the one or more previously performed medical procedures and/or medical procedure room set up is recorded, associated with a medical procedure identifier and stored in the data module  810 . In some embodiments, the one or more previous medical procedures or set ups may be obtained from the tutorials and technique guides stored in the data module  810 . In an embodiment, the data module  810  is also configured to store data, such as, patient name, patient identification, medical reports, medical diagnosis, health conditions, or the like, associated with a patient undergoing the medical procedure. 
     The data stored in the data module  810  may provide medical personnel  130  with the ability to search for instruments to provide information for unfamiliar tools and give feedback of optimal placement. The data stored in the data module  810 , may also include, for example, layout of equipment placement, relative to patients position for a medical procedure that will save on turnover times and efficiency for each procedure and practitioner preference. The layout and orientation may include where each of the medical practitioners and medical personnel  130  will be positioned during the procedure. 
     The data stored in the data module  810 , may also include, for example, guided imaging for setup of the various components of the medical procedure room  102  as described previously herein in  FIG. 1  for continuous updating, editing, and ultimately optimizing. The data stored in the data module  810 , may also include, for example, primary and ancillary, primary and ancillary equipment supplies listed specifically to each procedure. In accordance with various embodiments, the data module  810  is configured to store data received from the one or more remote connections  208 . In an embodiment, the received data is stored in the data module  810  along with a timestamp. In operation, after the procedure module  802 , the optimization functional block diagram  800  proceeds to the procedure input module  804 . The procedure input module  804  includes, but is not limited to, user input received by one or more of the communication device user interface  304 , the communication device sensor(s)  320 , the mixed reality device user interface  404 , the mixed reality device sensor(s)  424 , the optimization computing device user interface  504 , and the optimization computing device sensor(s)  522 . It will be appreciated by those of ordinary skill in the art that the user input may be received before, during, and after a particular medical procedure. 
     In practice, the procedure input module  804  incorporates notes for each medical procedure, medical practitioner specific to each procedure for future efficiencies and personnel. The procedure input module  804  may also incorporate for example usage of one or more primary and ancillary devices and other medical items including disposable items. In one embodiment, these items include pre-bar code or reference code allowing to track disposable costs and reduce the amount of wasted procedure costs. 
     In various embodiments, the procedure input module  804  is configured to acquire, via a mixed reality device, data associated with one or more attributes of operation of the respective medical technology. For instance, as described above, the one or more attributes operation of the medical technology may include set up and/or usage of one or more of the item, the equipment, the tool, and the enabling technology system  122 , and the like. The procedure input module  804  is configured to acquire, via the one or more mixed reality devices  132 , data associated with set up and/or usage of at least one or more of the item, the equipment, the tools, the one or more remote connections  208 . For instance, the data associated with usage of at least one of the item, the equipment, the tool, the enabling technology system  122  includes data associated with at least a pattern of use, a sequence of use, and a priority of use of at least one of the item, the tool, the enabling technology systems  122 , and the equipment during the medical procedure. In an exemplary embodiment, the data associated with the set up of one or more of the item, the tool, the enabling technology system  122 , the equipment, and the personnel in the medical procedure room set up may include one or more of identification, count, orientation, and geographical position of the respective the item, the tool, the enabling technology system  122 , the equipment, and the personnel in the medical procedure room. In an exemplary embodiment, the data associated with the medical technology for example one or more of the item, the equipment, or the tool may include one or more of count, usage, orientation, geographical position of the respective item, equipment or tool. 
     In an embodiment, the procedure input module  804 , via the one or more mixed reality devices  132 , is configured to acquire data associated with at least one of a position and an orientation of at least one personnel for operation of the medical procedure. Further, in practice the procedure input module  804  includes tracking of use (including use in visual mixed reality format), patterns for use, sequence of use, percentage and priority of use for chargeable resources such as sutures, sponges, clips, medical implants, screws, rods, arthroplasty devices, stimulators, needles, scalpel blades, drill bits. 
     In some embodiments, the procedure input module  804  is configured to provide the received data to a machine learning module  812 . The machine learning module  812  may be any system configured to learn and adapt itself to do better in changing environments. The machine learning module  812  may employ any one or combination of the following computational techniques: neural network, constraint program, fuzzy logic, classification, conventional artificial intelligence, symbolic manipulation, fuzzy set theory, evolutionary computation, cybernetics, data mining, approximate reasoning, derivative-free optimization, decision trees, and/or soft computing. 
     The machine learning module  812  may implement an iterative learning process. The learning may be based on a wide variety of learning rules or training algorithms. The learning rules may include one or more of back-propagation, patter-by-pattern learning, supervised learning, and/or interpolation. As a result of the learning, the machine learning module  812  may learn to determine the operations being performed by the optimization system  104 . 
     In accordance with some embodiments of the invention, the machine learning algorithm may utilize any machine learning methodology, now known or in the future developed, for classification. For example, the machine learning methodology utilized may be one or a combination of: Linear Classifiers (Logistic Regression, Naive Bayes Classifier); Nearest Neighbor; Support Vector Machines; Decision Trees; Boosted Trees; Random Forest; and/or Neural Networks. The machine learning module  812  continually evolves the specifics of operation of a medical technology in real time with new data inputs. The machine learning intent is to continually implement optimized medical technology overtime. 
     In an embodiment, medical information from the one or more remote connections  208  is received via one or more input module. In various embodiments, the medical information may include medical diagnosis data like medical history of a patient, training data like video tutorials, lectures and the like associated with the one or more attributes of operation of the medical technology, and recommendation data associated with the one or more attributes of operation of the medical technology. The medical information may be received from one or more collaborator devices (as shown in  FIG. 11 ), the communication devices  104  and the like. For example, the one or more input module may be a remote input module  808  or a local input module  814 . The input from remotely present one or more remote connections  208  is received via the remote input module  808  and the input from locally present one or more remote connections  208  is received via the local input module  814 . In various embodiments, the modules  808  and  814  of the optimization system  104 , are configured to obtain medical information associated with the one or more attributes of operation of the medical technology. 
     In one embodiment, the medical technology is the medical procedure and the one or more attributes of operation of the medical technology correspond to usage of one or more of the item, the equipment, the tool, and the enabling technology system  122 . In one embodiment, the medical technology is the medical procedure room set up and the one or more attributes of operation of the respective medical technology correspond to one or more attributes associated with set up of one or more of the item, the equipment, the tool, and the enabling technology systems  122  in the medical procedure room set up. In one embodiment, the medical technology is one or more of the item, the equipment, or the tool and the one or more attributes of operation of the respective medical technology correspond to one or more attributes associated with the count, identification, geographical positioning, orientation of the respective item, equipment or tool in the medical procedure room. In an embodiment, the modules  808  and  814  are configured to obtain the medical information from one or more remote connections  208  via one or more communication device  124 , one or more collaborator devices (shown in  FIG. 11 ) and the like. In various embodiments, the modules  808  and  814  are configured to provide the obtained medical information to the machine learning module  812 . 
     In various embodiments, the machine learning module  812  is configured to analyze the obtained medical information and the acquired data, to optimize the operation of the medical technology. The machine learning module  812  of the optimization system  104  is further configured to analyze, via machine learning module  812 , the obtained medical information and the acquired data by determining whether the acquired data associated with one or more attributes of operation of the medical technology correspond to the obtained medical information. Further, when the acquired data associated with one or more attributes of operation of the medical technology does not correspond to the obtained medical information, the machine learning module  812  identifies deviation of the acquired data associated with one or more attributes of operation of the medical technology from the obtained medical information and provides recommendation associated with the identified deviations to optimize the operation of the medical technology. For example, when the medical information indicates that the surgical incision of four (4) to six (6) inches be made during the operation of the medical technology and the acquired data indicates that the surgical incision of only three (3) inches has been made, the machine learning module  812  is configured to detect the deviation and provide recommendation to make a bigger surgical incision. 
     In an embodiment, the machine learning module  812  is also configured to analyze the prestored data, in the data module  810 , associated with one or more of setup and/or usage of the item, the equipment, the tool, and the enabling technology systems  122  in one or more reference medical procedure room corresponding to the one or more of the medical practitioner identifier, the medical procedure identifier, and the medical procedure room identifier. For example, the prestored data associated with setups and/or usage of one or more of the item, the equipment, the tool, and the enabling technology systems  122  in the medical procedure room include one or more of count, orientation, usage, and geographical position of the respective item, equipment, tool, and enabling technology systems  122  in the medical procedure room. In an embodiment, the analysis of the prestored data comprises determining the optimal relationship of the data associated with the setup and/or the usage of the one or more of the item, the equipment, the tool, and the enabling technology systems  122  in the one or more reference medical procedure room with the one or more of the medical practitioner identifier, the medical procedure identifier, and the medical procedure room identifier. The machine learning module  812  is configured to compare the acquired data associated with the one or more of the item, the equipment, the tool, and the enabling technology systems  122  in the medical procedure room with the analyzed prestored data associated with the respective one or more of the item, the equipment, the tool, and the enabling technology systems  122  in the one or more reference medical procedure room. In an embodiment, the machine learning module  812  is configured to compare the acquired data with the analyzed prestored data by determining whether the acquired data associated with the one or more of the item, the equipment, the tool, and the enabling technology systems  122 , in the medical procedure room correspond to the determined optimal relationship for the one or more of the medical practitioner identifier, the medical procedure identifier, and the medical room identifier. The machine learning module  812  is configured to provide recommendations to the module  802  for optimizing the medical procedure technology based on the comparison. In accordance with various embodiments, the machine learning module  812  is configured to provide recommendations to the module  802  for optimizing the medical procedure technology when the acquired data associated with the one or more of the item, the equipment, the tool, and the enabling technology system  122 , in the medical procedure does not correspond to the determined optimal relationship. The machine learning module  812  is configured to provide the recommendations based on the determined optimal relationship. In an embodiment, the module  802  is further configured to update the virtual image guidance for the medical procedure technology based on the received recommendations. In an embodiment, the machine learning module  812  is further configured to provide the at least one medical procedure input corresponding to one or more of the medical practitioner identifier, the medical procedure identifier, and the medical procedure room identifier to the procedure module  802 . 
     In various embodiments, the machine learning module  812  of the optimization system  104  is further configured to determine data associated with one or more predefined parameters related to the optimized operation of the medical technology. In accordance with various embodiments, the one or more predefined parameters are associated with performance of the optimal operation of the respective medical technology. For example, the one or more predefined parameters may include any performance related parameter, such as but not limited to, time spent on the operation of the medical technology, units of blood infused to the patient, etc. 
     The continuous loop of the optimization functional block diagram  800 , in practice provides real time feedback and optimization of a procedure. For example, as the procedure moves along the procedure input module  804  includes tracking of instruments that are highlighted, and arrows point to the location in the room as needed through artificial prompt and data analysis. This continuous loop optimization provides for metric tracking to create safety, efficiencies, simplicity across all aspects of the procedure. The metric will be able to produce specific and tailored feedback regarding the procedure as well as allow for real time oversight (local or remote). Live feedback and machine learning suggestions may be provided during this process. Messaging between medical personnel  130  and medical practitioners may be automated, and artificial intelligence triggered to notify the entire team of progress and current step of the procedure. For example, procedure tracking at the procedure input module  804  may provide instructions such as bringing the patient in. In another example, after the patient enters the medical procedure room, a message may be triggered that the patient will need to be postponed for a period of time based on the machine learning data experience. Additional checks and balances can be set in place including, for example, facial recognition, prompts to double check the incision site, and the like. 
     In practice, the procedure input module  804  may include communication between the communication devices  124 , the mixed reality devices  132 , the optimization computing device  206 , and/or the remote connections  208 . For example, the procedure input module  804  may indicate an instrument missing from the medical procedure room and request a remote connection provide it. This provides for increased safety and sterilization procedures and increased efficiency, reduced turnover times for cases, communication and messaging across the team including real-time and automated, tracking/counting of consumables during a procedure, and the like. In practice, the procedure input module  804  includes acquiring of data via one or more mixed reality devices  132 . In operation, the one or more mixed reality devices  132  provide a view of the procedure room once the procedures start so personnel will have an exact idea and view of where each member will be standing during the perioperative portion of the procedure. Further, the one or more mixed reality devices  132  may receive information about medical procedure resources in visual mixed reality format, including quantities and tracking of these resources, use, patterns for use, sequence of use, percentage and priority of use. In an embodiment, the machine learning module  812  is configured to compare the received medical procedure input with the data acquired via the mixed reality devices  132 , associated with the usage of one or more of the item, the equipment, the tool, and the enabling technology systems  122  during the medical procedure. In an embodiment, the machine learning module  812  is configured to generate an alert when the data associated with the usage of one or more of the item, the equipment, the tool, and the enabling technology systems  122  during the medical procedure is not consistent with the received medical procedure input. In an exemplary embodiment, the machine learning module  812  is configured to generate warnings, prompts, alerts for counts, location, and management of missing instruments, devices, disposables on the field or within the patient as appropriate. 
     In operation, during a procedure, the one or more mixed reality devices  132  may provide for an interactive data interface linking the medical procedure environment through the data exchange of a microscope, endoscopic system, fluoroscopic system, navigation/robotic system, for live web-based conferencing, education and training, and surgical demonstrations for technology, remote surgery, or remote surgery demonstration/education. In an embodiment, the input module is coupled to one or more medical enabling technology system  122  and is configured to control operations of the one or more medical enabling technology system  122 . In particular, the machine learning module  812  is configured to control, via the input module, the operations of the one or more medical enabling technology system  122  based on the stored data associated with the patient undergoing the medical procedure. For example, the machine learning module  812  is configured to control a specific anesthesia dosage required for a particular medical procedure based on the stored data associated with the patient. Specifically, the one or more mixed reality devices  132  may provide for interactive data interface linking the anesthesia environment, gas exchange machines and monitors, anesthesia machines and telemetry, gas rates and anesthesia measures, for purpose of tracking patient specific data related to adequacy, safety, prescription and optimization of anesthetic induction, maintenance, and recovery. 
     Specifically, procedure inputs from the one or more mixed reality devices  132  may provide direct external visualization of the operating room environment through the eyes of the medical personnel  130  wearing the mixed reality device  132 , through the external visualization of, for example, a microscope, an endoscopic system, a fluoroscopic system, a navigation/robotic system to an external expert, product specialist, or other professional. In some embodiments, a three-dimensional aerial perspective view of the medical procedure room  102  suite allows personnel capability for predictive planning of layout of equipment placement, relative to patients position for surgical case that will save on turnover times and efficiency for each surgical procedure and medical practitioner preference. 
     Further, in some embodiments, the one or more mixed reality devices  132  identifies whether one or more bed attachments are correct based on a right side or left side surgery (arm attachments and the like). Using a visual checklist, the one or more mixed reality devices  132  determines and provides procedure inputs that additional items for the medical practitioner are correct and documented as well as location is saved. 
     In practice, the one or more mixed reality devices  132  may store and transmit animation, videos, demonstrations and live coaching in a way where the specific medical practitioner, for the specific procedure, and a specific device or technology could receive education, consultation, and instruction of best use or trouble shooting remotely as indicated by a remote input module  808 . This transmission may be stored information, live two-way transmitted information, could be interfaced with mixed reality ‘white boards’ and drawing/display tools and with virtual representation of real instruments/devices either stored in the data module  810  or one or more remote connections (for example the remote input module  808 ). As described above, the input module may be the remote input module  808  and the local input module  814 . The remote input as illustrated by module  808 , may be received from remote connections  208  before, during, and after a particular medical procedure. Remote input of module  808 , for example may include the integration of multimedia data management, acquisition and expression from secondary enabling medical technologies. In an embodiment, the local input as illustrated by the local input module  814  may be received from local enabling technology system  122  present in the medical procedure room. 
     In various embodiments, at least one device communicatively coupled to the optimization system  104 , is configured to receive from the optimization system  104 , the acquired data associated with one or more attributes of operation of the respective medical technology. In an embodiment, the at least one device may be coupled to a plurality of optimization systems  104 . For instance, the at least one device may be a communication device  124 , the one or more of medical enabling technology system  122 , and the like. The at least one device may be a device associated with the one or more medical personnel  130 , medical staff, supporting staff. In an embodiment, the acquired data is associated with respective time stamps. For example, the at least one device may acquire information from the medical procedure room that anesthesia has been given to the patient during the medical procedure. 
     The at least one device is further configured to receive medical health data associated with a patient during the operation of medical technology. The medical health data may be received from the one or more enabling technology system  122 , one or more collaborator devices (shown in  FIG. 11 ), and the like. For instance, the at least one device may be configured to receive data related to health parameters such as, but not limited to, heart rate, blood pressure, sugar level, and the like during the operation of the medical technology. In an embodiment, the medical health data received by the at least one device is associated with respective time stamps. For example, in view of the above stated example, at this stage, the at least one device receives information that the blood pressure of the patient has increased after giving the anesthesia. 
     In an embodiment, the at least one device is further configured determine a relationship between the acquired data related to usage of one or more the item, the equipment, the tool, and the enabling technology system  122  and the received medical health data during the operation of the medical technology. The at least one device is further configured to provide the medical information associated with optimizing the operation of the medical technology based on the determined relationship. For instance, at this stage, in the above stated example, at least one device provides recommendation to reduce the amount of anesthesia used to maintain the blood pressure of the patient. 
     Module  806  implements a natural language processing algorithm. The natural language processing algorithm collects unstructured data from various sources including procedure input of module  804 , and remote inputs of module  808 , and local inputs of the module  814 . These inputs are converted into machine-readable structured data, stored in the data module  810 , and then analyzed by the machine learning module  812 . It will be appreciated that the machine learning module  812 , in some embodiments, may analyze the data in the data module  810  prior to a next procedure room set up  802 , during a procedure itself to modify a procedure room set up, and/or after a procedure for analytical and training purposes. The machine learning module  812  may analyze the data in the data module  810  at other instances now known or hereinafter developed. 
     In practice, the machine learning module uses the data in the data module  810  for procedure efficiency, outcome and optimization. The machine learning module  812  may, for example use medical practitioner specific identification of the procedure room and the equipment and supply characteristics for any given procedure, and any given patient, for optimization of procedure sequence, flow and execution, and ultimately help to define lean simple system design for optimal operating room setup and procedure steps for that specific medical practitioner and for that specific procedure. Practitioner specific identification of the procedure room and the equipment and supply characteristics for any given procedure, and any given patient, would then enable identification of experience based predictive data for performance, safety, outcome efficiency and inventory control/management for medical practitioners learning new procedures/devices/systems on behalf of their patients. 
     It will be appreciated that the optimization functional block diagram  800  in implementation provides for medical practitioner specific identification of the medical procedure room and the equipment and supply characteristics for any given procedure, and any given patient, enabling machine learning processes for optimization of procedure sequence, flow and execution, and ultimately help to define lean simple system design for optimal medical procedure room setup for that specific medical practitioner and for that specific procedure. 
       FIG. 9  is a flow diagram of a method of extended continuous optimization using the functionality of  FIG. 8  in accordance with some embodiments. Specifically,  FIG. 9  is a flow diagram  900  illustrating the implementation of the optimization system  104  and various functionality as described previously herein for one or more medical practitioners, one or more medical procedure rooms, and/or one or more medical procedures. 
     The flow diagram  900  begins with operation  902  wherein a procedure identifier is initiated by setting the medical procedure identifier “P” equal to one “1”. Next, in operation  904 , a medical procedure room identifier is initiated by setting the medical procedure room identifier “R” equal to one “1”. Next, in operation  906 , a medical practitioner identifier is initiated by setting the medical practitioner identifier “MP” equal to one “1”. 
     Next, in operation  908 , optimization functionality occurs. It will be appreciated by those of ordinary skill in the art that the optimization operation  908  includes the optimization described previously herein for  FIGS. 1 through 8 . 
     After the optimization operation  908 , the process of flow diagram  900  continues to operation  910  in which it is determined whether there are more medical practitioners. Specifically, it is determined whether MP=MP+1 is to be included. When MP+1 is determined to be included, the process continues to operation  912  in which the MP identifier is incremented to MP=MP+1. The process then cycles back to the optimization operation  908 . In operation, at this stage, in one embodiment, the optimization system  104  is configured to optimize the medical technology for instance, execution of one or more steps of the medical procedure based on the plurality of received medical practitioner identifiers (for example, MP and MP+1). For example, the optimization system  104  is configured to obtain data associated with preferred operation of the medical procedure associated with the received medical practitioner identifiers and optimize the execution of one or more steps of the medical procedure based on the obtained information. In some embodiments, the optimization may include merging the data associated with preferred operation of the medical procedure associated with the received plurality of received medical practitioner identifiers or selecting the data associated with preferred operation of the medical procedure associated with the primary/predefined medical practitioner, in case of any conflict. The optimized medical procedure may then be associated with the received plurality of medical practitioner identifiers and stored in the data module  810 . 
     In another embodiment, at this stage  908 , in one embodiment, the optimization system  104  is configured to optimize the medical technology for instance, the medical procedure room set up based on the plurality of received medical practitioner identifiers (in other words, MP and MP+1). For example, the optimization system  104  is configured to obtain the preferred medical procedure room setup associated with the received medical practitioner identifiers and optimize the medical procedure room set up based on the preferred medical procedure room setup associated with the received medical practitioner identifiers. In some embodiments, the optimization may include merging the preferred medical procedure room setup associated with the received plurality of medical practitioner identifiers or selecting the preferred medical procedure room setup associated with the primary/predefined medical practitioner, in case of any conflict. The optimized medical procedure room setup may then be associated with the received plurality of medical practitioner identifiers and stored in the data module  810 . 
     When, in operation  910 , it is determined that there is no MP+1 to include, the process continues to operation  914  in which it is determined whether there are more medical procedure rooms. Specifically, it is determined whether R=R+1 is to be included. When R+1 is determined to be included, the process continues to operation  916  in which the R identifier is incremented to R=R+1. The process then cycles back to the operation  906 . In operation, at this stage, in an embodiment, the optimization system  104  is configured to optimize the medical technology, for instance execution of one or more steps of the medical procedure based on the plurality of received medical procedure room identifiers (for example, R and R+1). For example, the optimization system  104  is configured to obtain data associated with preferred operation of the medical procedure associated with the received medical procedure room identifiers and optimize the execution of one or more steps of the medical procedure based on the obtained information. The optimized medical procedure may then be associated with the received plurality of medical procedure room identifiers and stored in the data module  810 . 
     In another embodiment, at this stage  906 , in one embodiment, the optimization system  104  is configured to optimize the medical technology, for instance, the medical procedure room set up based on the plurality of received medical procedure room identifiers (for example, R and R+1). For example, the optimization system  104  is configured to obtain the preferred medical procedure room setups associated with the received medical procedure room identifiers and optimize the medical procedure room set up based on the preferred medical procedure room setups associated with the received medical procedure room identifiers. The optimized medical procedure room setup may then be associated with the received plurality of medical procedure room identifiers and stored in the data module  810 . 
     When, in operation  914 , it is determined that there is no R+1 to include, the process continues to operation  918  in which it is determined whether there are more medical procedures. Specifically, it is determined whether P=P+1 is to be included. When P+1 is determined to be included, the process continues to operation  920  in which the P identifier is incremented to P=P+1. The process then cycles back to the operation  904 . In operation, at this stage, in one embodiment, the optimization system  104  is configured to optimize the medical technology for instance, execution of one or more steps of the medical procedure based on the plurality of received medical procedure identifiers (for example, P and P+1). For example, the optimization system  104  is configured to obtain data associated with preferred operation of the medical procedure associated with the received medical procedure identifiers and optimize the execution of one or more steps of the medical procedure based on the obtained information. The optimized medical procedure may then be associated with the received plurality of medical procedure identifiers and stored in the data module  810 . 
     In another embodiment, at this stage  904 , in one embodiment, the optimization system  104  is configured to optimize medical technology for instance, the medical procedure room set up based on the plurality of received medical procedure identifiers (for example, P and P+1). For example, the optimization system  104  is configured to obtain the preferred medical procedure room setups associated with the received medical procedure identifiers and optimize the medical procedure room set up based on the preferred medical procedure room setups associated with the received medical procedure identifiers. The optimized medical procedure room setup may then be associated with the received plurality of medical procedure identifiers and stored in the data module  810 . 
     When, in operation  918 , it is determined that there is no P+1 to include, the process cycles back to operation  902  in which P is reset. In this manner, the optimization system  104  and methods described herein provide continuous optimization for one or more medical practitioners, one or more medical procedure rooms, and one or more medical procedures and any combination therein. 
       FIG. 10  is a functional block diagram  1000  of a method for medical procedure room information exchange in accordance with some embodiments. The method for medical procedure room information exchange, in some embodiments, facilitates the procedure room optimization as described previously herein. As illustrated, an interactive information exchange system and method includes the exchange of one or more stored information  1002 , one or more communications  1004 , and one or more visualizations  1006 . In some embodiments, the interactive information and exchange system and method is implemented within the medical procedure system  100 . 
     The information  1002  may be, for example, data stored within the functionality of data module  810  as previously described herein. 
     The information  1002  includes, but is not limited to, stored information  1008  such as education, consultation, and instruction of best use or trouble shooting for one or more procedures. In practice, the stored information  1008  may be data processed by the natural language processing module  806  received via one or more remote inputs  808  as previously described herein in  FIG. 8 . 
     The information  1002  further includes, but is not limited to, optimization information  1010  such as historical data for procedural performance optimization. The optimization information  1010  further may be medical practitioner specific interpretation or medical diagnosis of abnormalities, pathological findings and diagnoses, and remote human interaction for complex consultations, opinions and treatment recommendations. The stored information may be used to identify, log, validate that particular step for best clinical standards, identifying deviation real time or retrospectively. In some embodiments, the optimization information  1010  includes practitioner specific identification of the medical procedure room space and the equipment and supply characteristics for any given procedure, and any given patient, providing best practices enabling optimization for performance, efficiency, safety and inventory control/management. The optimization information  1010  may be derived from the machine learning module  812  of  FIG. 8  as previously described herein. 
     The communications  1004 , operably coupled between the information  1002  and the visualizations  1006 , provides for interactive communication within the medical procedure room. The communications  1004 , includes, but is not limited to, one or more input  1012 , one or more interactions  1014 , and one or more drawings  1016 . The communications  1004  may be various interactions as illustrated and described previously herein between the optimization computing device  206  and one or more devices, such as, the communication devices  124 , the mixed reality devices  132  of a medical procedure room, and one or more collaborator devices (as shown in  FIG. 11 ). The communications  1004 , for example, in some embodiments, enables two-way transmission of information  1002  between the visualizations  1006 , the information  1002 , and other various communication mechanisms. 
     The visualizations  1006 , operably coupled to the communications  1004 , may include, but are not limited to, one or more virtual white boards  1018 , one or more virtual representations  1020  of instruments and devices within the medical procedure room, one or more displays  1022 , and one or more medical procedure room visualizations  1024 . For example, the one or more medical procedure room visualization  1024  may be a direct external visualization of the medial procedure room environment through the mixed reality device display  422  of one or more mixed reality devices  132 . Similarly, the one or more virtual representations  1020  of instruments and devices may be external visualization of instruments such as an operating microscope, endoscopic system, fluoroscopic system, navigation/robotic system through the mixed reality device display  422  of one or more mixed reality devices  132 . 
     One exemplary embodiment of the method for medical procedure room information exchange includes visualization  1006  on one or more mixed reality devices  132 , which then via the communications  1004  transmit the training data, such as but not limited to, animation, videos, demonstrations and live coaching to the information  1002  which then then via the communications  1004  updates the visualization and live coaching back to the visualizations  1006 . This optimization method may be in real time or alternatively before or after commencement of a medical procedure. Further, the information  1002  may be, as described previously herein, communicated to a particular medical practitioner or medical personnel  130 , for a specific procedure, and/or a specific device or technology.  FIG. 11  illustrates a system  1100  for remote optimization of medical technologies in accordance with some embodiments. As illustrated, the system  1100  includes one or more optimization systems  104 -N. It will be appreciated that the one or more optimization systems  104 -N comprise and operate as previously illustrated and described herein for  FIGS. 1 through 9 . The one or more optimization systems  104 -N are communicatively coupled to at least one remote medical technology optimization system  1102 . The operation of the remote medical technology optimization system  1102  is illustrated and described in  FIG. 12  hereinafter. The remote medical technology optimization system  1102  for example, may be one or more clinical trials of a procedure, device, or other technology now known or hereinafter developed. 
     The one or more optimization systems  104 -N, in some embodiments, are communicatively coupled to one or more collaborator devices  1104 . The one or more collaborator devices  1104 , for example, may include all or a subset of the one or more remote connections  208  previously described. Further, the one or more collaborator devices  1104  may include medical specialists, systems, and/or devices that support enabling technology, medical implants, devices, and implants. The one or more collaborator devices  1104  alternatively may comprise external regulatory bodies, systems, and/or devices, such as within the Food and Drug Administration (“FDA”) operating to observe, log, track, identify and transmit procedure specific information for a specific medical procedure or technology being optimized. As such, the one or more collaborator devices  1104  are further communicatively coupled to the at least one medical procedure or medical technology optimization system  1102 . 
       FIG. 12  is a flow diagram  1200  of a method for remote optimization of medical technologies in accordance with some embodiments. The method illustrated in  FIG. 12  enables not only validation of a given, new medical technology, but also provides real time machine learning for optimization of that new technology towards best clinical use, enabling clinical trials that not only validate safe application of technology given live clinical use, but optimize best clinical use during the live application phase of the device, procedure, or technology evaluation for clinical use. Practitioner and procedure specific identification of the medical procedure room and the equipment and supply characteristics for any given procedure, and any given patient, would then enable precise data acquisition relevant to device clinical trials, performance, optimization, logging, tracking, and time stamping for the purpose of providing new metrics for best clinical use of new medical systems, devices or applications. 
     For example, the method illustrated in  FIG. 12 , may provide a mechanism for medical device execution and use on clinical trials in a way where external regulatory bodies, such as the FDA would be able to observe, log, track, identify and transmit procedure specific information for that specific clinical trial. This data would enable not only validation of a given, new medical technology, but provide real time machine learning for optimization of that new technology towards best clinical use, enabling clinical trials that not only validate safe application of technology given live clinical use, but optimize best clinical use during the live application phase of the device evaluation for clinical use. 
     In another implementation, the method of  FIG. 12  provides for storage and transmitting of animation, videos, demonstrations and live coaching in a way where a medical technician, on the field could learn disassembly, assembly and articulation of complex implants or devices for best clinical use on the field, and apply it to that medical practitioner, for that procedure, and store, identify, log, validate that particular step for best clinical standards, identifying deviation real time or retrospectively. 
     As illustrated in  FIG. 12 , the method begins with operation  1202  in which one or more parameters of interest are initialized by the medical technology optimization system  1102 . The one or more parameters correspond to the one or more predefined parameters related to the optimized operation of the medical technology, as discussed above in  FIG. 8 . Next, in operation  1204 , an identification is set to ID=1. The identification, for example, may be associated with an optimization system  104 . In such a case, for example, an optimization system  104 - 1  for example would have an ID=1. 
     Next, in operation  1206 , it is determined whether one or more inputs have been received from an optimization system  104 . For instance, the one or more input may be the data related to the one or more predefined parameters, the data acquired by the one or more mixed reality devices  132 , the data received from the one or more remote connections  208 , and the like. It will be appreciated that the received one or more inputs in some embodiments include the data, machine learning optimization, and other procedure inputs resulting from the machine learning procedure optimization of  FIG. 8  for a given optimization system  104 . When an input has been received in operation  1206 , the method continues to operation  1208  in which the identifier is incremented to ID=ID+1. Next, the output at operation  1208  cycles back to operation  1206 . 
     Referring back to operation  1206 , when no further input is obtained from the optimization system  104 , the method continues to operation  1210  in which an analysis of data obtained from the one or more optimization systems  104  takes place. 
     In operation  1210 , the remote medical technology optimization system  1102  is configured to analyze the obtained data associated with the one or more predefined parameters related to the optimized operation of the medical technology. In an embodiment, the remote medical technology optimization system  1102  is configured to analyze the data by obtaining, from each of the plurality of optimization systems  104 , data associated with the optimized operation of the medical technology. For instance, the data associated with the optimized operation of the medical technology includes data associated with one or more of medical health of a patient, set up of one or more of the item, one or more of the equipment, the tool, and the enabling technology system  122 , and usage of one or more of the item, one or more of the equipment, the tool, and the enabling technology system  122 , count of the one or more of the item, one or more of the equipment, the tool, orientation and geographical position of the one or more of the item, one or more of the equipment, the tool, and the like. Further, the remote medical technology optimization system  1102  is configured to determine an optimal relationship between the obtained data and the data associated with the one or more predefined parameters related to the optimized operation of the respective medical technology. For example, when the medical technology corresponds to a heart surgery, the obtained data may be one or more of heart rate, usage of a pacemaker, and the length of the surgical incision made during the heart surgery and the predefined parameter may include the time taken to complete the heart surgery. 
     In various embodiments, the remote medical technology optimization system  1102  is configured to determine, in operation  1212 , an optimized data associated with the one or more predefined parameters for optimal operation of the medical technology based on the analyzed data. The optimization comprises optimizing the data associated with the one or more predefined parameters for optimal operation of the medical technology based on the determined optimal relationship. For instance, in view of the above example, the remote medical technology optimization system  1102 , at this stage, may determine that the optimal time for performing a heart surgery is 3 hours. 
     In an embodiment, the remote medical technology optimization system  1102  is further configured to determine the optimized data associated with the one or more predefined parameters for optimal operation of the medical technology based on inputs obtained from one or more of the medical enabling technology system  122 , the communication device  124 , the storage device and the like. 
     The remote medical technology optimization system  1102  is configured to determine the optimal relationship by way of a machine learning module as described in  FIG. 8 . The machine learning module may be any system configured to learn and adapt itself to do better in changing environments. The machine learning module may employ any one or combination of the following computational techniques: neural network, constraint program, fuzzy logic, classification, conventional artificial intelligence, symbolic manipulation, fuzzy set theory, evolutionary computation, cybernetics, data mining, approximate reasoning, derivative-free optimization, decision trees, and/or soft computing. 
     The machine learning module may implement an iterative learning process. The learning may be based on a wide variety of learning rules or training algorithms. The learning rules may include one or more of back-propagation, patter-by-pattern learning, supervised learning, and/or interpolation. As a result of the learning, the machine learning module may learn to determine the operations being performed by the remote medical technology optimization system  1102 . 
     In accordance with some embodiments of the invention, the machine learning algorithm may utilize any machine learning methodology, now known or in the future developed, for classification. For example, the machine learning methodology utilized may be one or a combination of: Linear Classifiers (Logistic Regression, Naive Bayes Classifier); Nearest Neighbor; Support Vector Machines; Decision Trees; Boosted Trees; Random Forest; and/or Neural Networks. The machine learning module continually evolves the specifics of execution of a medical procedure in real time with new data inputs. The machine learning intent is to continually implement optimized medical procedure overtime. 
     In operation  1214 , it is determined that whether the determined optimized data is associated with the one or more predefined parameters. For example, in the case of a clinical trial, the criteria may be an acceptable error rate. When the one or more criteria are met, the optimization method is considered complete in operation  1216 . Alternatively, when the one or more criteria are not met in operation  1214 , the method cycles back to operation  1204  and optimization begins again. 
     In various embodiments, the remote medical technology optimization system  1102 , in operation  1214 , is configured to determine, for each of the plurality of optimization systems  104 -N, whether the optimized data associated with one or more predefined parameters related to the optimized operation of the respective medical technology satisfies a predefined criterion. For instance, in view of the above example, it is determined that whether the optimized time of 3 hours satisfies a predetermined criterion. When the predetermined criteria is not met, then the remote medical technology optimization system  1102  is further configured to repeat the operations related to obtaining, analyzing, and determining until the optimized data associated with one or more predefined parameters related to the optimized operation of the respective medical technology satisfies the predefined criteria. 
     In the methods and systems described herein, a procedure, setup, technology, or device may be optimized using machine learning techniques both in individual medical procedures, medical procedure rooms, and medical practitioners; and in compilation by combining the optimization of many such medical procedures, medical procedure rooms, and medical practitioners. 
     In the foregoing specification, specific embodiments have been described. However, one of ordinary skill in the art appreciates that various modifications and changes can be made without departing from the scope of the invention as set forth in the claims below. Accordingly, the specification and figures are to be regarded in an illustrative rather than a restrictive sense, and all such modifications are intended to be included within the scope of present teachings. 
     The benefits, advantages, solutions to problems, and any element(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential features or elements of any or all the claims. The invention is defined solely by the appended claims including any amendments made during the pendency of this application and all equivalents of those claims as issued. 
     Moreover, in this document, relational terms such as first and second, top and bottom, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The terms “comprises,” “comprising,” “has”, “having,” “includes”, “including,” “contains”, “containing” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises, has, includes, contains a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element preceded by “comprises . . . a”, “has . . . a”, “includes . . . a”, “contains . . . a” does not, without more constraints, preclude the existence of additional identical elements in the process, method, article, or apparatus that comprises, has, includes, contains the element. The terms “a” and “an” are defined as one or more unless explicitly stated otherwise herein. The terms “substantially”, “essentially”, “approximately”, “about” or any other version thereof, are defined as being close to as understood by one of ordinary skill in the art, and in one non-limiting embodiment the term is defined to be within 10%, in another embodiment within 5%, in another embodiment within 1% and in another embodiment within 0.5%. The term “coupled” as used herein is defined as connected, although not necessarily directly and not necessarily mechanically. A device or structure that is “configured” in a certain way is configured in at least that way but may also be configured in ways that are not listed. 
     It will be appreciated that some embodiments may be comprised of one or more generic or specialized processors (or “processing devices”) such as microprocessors, digital signal processors, customized processors and field programmable gate arrays (FPGAs) and unique stored program instructions (including both software and firmware) that control the one or more processors to implement, in conjunction with certain non-processor circuits, some, most, or all of the functions of the method and/or apparatus described herein. Alternatively, some or all functions could be implemented by a state machine that has no stored program instructions, or in one or more application specific integrated circuits (ASICs), in which each function or some combinations of certain of the functions are implemented as custom logic. Of course, a combination of the two approaches could be used. 
     Moreover, an embodiment can be implemented as a computer-readable storage medium having computer readable code stored thereon for programming a computer (for example, comprising a processor) to perform a method as described and claimed herein. Examples of such computer-readable storage mediums include, but are not limited to, a hard disk, a CD-ROM, an optical storage device, a magnetic storage device, a ROM (Read Only Memory), a PROM (Programmable Read Only Memory), an EPROM (Erasable Programmable Read Only Memory), an EEPROM (Electrically Erasable Programmable Read Only Memory) and a Flash memory. Further, it is expected that one of ordinary skill, notwithstanding possibly significant effort and many design choices motivated by, for example, available time, current technology, and economic considerations, when guided by the concepts and principles disclosed herein will be readily capable of generating such software instructions and programs and ICs with minimal experimentation. 
     The Abstract of the Disclosure is provided to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in various embodiments for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separately claimed subject matter.