Patent ID: 12242777

DETAILED DESCRIPTION OF FIGURES

For the purpose of promoting an understanding of the principles of the present disclosure, reference will now be made to the embodiments illustrated in the drawings and specific language will be used to describe the same. It will, nevertheless, be understood that no limitation of the scope of the disclosure is thereby intended; any alterations and further modifications of the described or illustrated embodiments, and any further applications of the principles of the disclosure as illustrated therein are contemplated as would normally occur to one skilled in the art to which the disclosure relates. All limitations of scope should be determined in accordance with and as expressed in the claims.

Whether a term is capitalized is not considered definitive or limiting of the meaning of a term. As used in this document, a capitalized term shall have the same meaning as an uncapitalized term, unless the context of the usage specifically indicates that a more restrictive meaning for the capitalized term is intended. However, the capitalization or lack thereof within the remainder of this document is not intended to be necessarily limiting unless the context clearly indicates that such limitation is intended.

The systems, methods, and processes herein create customized protective devices that provide protection for an intended body portion, allow a subject (e.g., patient) to maintain a normal range of motion, and avoid or minimize discomfort caused by wearing the customized protective device. The customized protective devices described herein generally may include a contoured member that is configured to cover (e.g., extend over) at least a portion of an intended body portion of the subject, with the contoured member having an inner surface disposed opposite an outer surface. The inner surface may be configured to face and/or contact the intended body portion when the customized protective device is worn by the subject, while the outer surface may be configured to face away from the intended body portion.

In some embodiments, a customized protective device may be configured for use with respect to an injured or previously injured body portion to prevent or inhibit further injury or re-injury of the body portion and promote healing. In some embodiments, such a customized protective device may be configured to provide direct impact shielding for the injured or previously injured body portion. As described in detail below, direct impact shielding may be provided by configuring the customized protective device to include one or more contact portions and one or more non-contact portions. When the protective device is worn by the subject, the contact portion(s) may contact the subject's body, while the non-contact portion(s) may be offset (i.e., spaced apart) from the subject's body. In this manner, the non-contact portion(s) may cover an injured or previously injured body portion, while the contact portions distribute impact forces to surrounding body portions. In other embodiments, as described below, a customized protective device may be configured to limit a range of motion of a joint of the subject, for example, an injured joint, such that the joint is protected from further injury.

In at least one embodiment, a customized protective device may be configured for use with respect to an uninjured body portion to prevent or inhibit injury of the body portion. For example, such a customized protective device may be configured to cover a body portion that is likely to be impacted during participation in a given activity, such as contact sports. This type of customized protective device generally may be form-fit to the body portion to be protected, without any non-contact portions. Further, such a customized protective device may be configured to allow the subject to maintain a normal range of motion of nearby joints, while also avoiding undesired contact between the protective device and body portions other than those covered by the customized protective device.

The custom manufacturing processes of several types of customized protective devices are described herein and illustrated in the accompanying drawings. It will be appreciated that these protective devices are merely examples, and that features of the described and illustrated devices, as well as the methods for creating the customized protective devices, may be applied similarly to other types of customized protective devices for protecting other portions of a subject's body.

With reference toFIG.1, shown is a networked environment100that manages the production of a customized protective device, according to one embodiment of the present disclosure. The networked environment100may include a computing environment102, an additive manufacturing device106, and a subject data capture device108, which are in data communication with each other via a network104. In particular embodiments, the final output of the network environment100is a customized protective device151, created by the additive manufacturing device106. In various embodiment, the network104includes, for example, the Internet, intranets, extranets, wide area networks (WANs), local area networks (LANs), wired networks, wireless networks, or other suitable networks, etc., or any combination of two or more such networks. For example, such networks may include satellite networks, cable networks, Ethernet networks, Bluetooth networks, Wi-Fi networks, NFC networks, and other types of networks.

The computing environment102may include, for example, a server computer or any other system providing computing capability. Alternatively, the computing environment102may employ more than one computing devices that can be arranged, for example, in one or more server banks or computer banks or other arrangements. In at least one embodiment, such computing devices are located in a single installation or are distributed among many different geographical locations. For example, the computing environment102may include one or more computing devices that together may include a hosted computing resource, a grid computing resource and/or any other distributed computing arrangement. In some cases, the computing environment102may correspond to an clastic computing resource where the allotted capacity of processing, network, storage, or other computing-related resources can vary over time. In various embodiments, the computing environment102includes remote mobile computing devices that are capable of performing the actions of the computing environment102. For example, a cellular device can process particular data and store the data locally, remotely on a cloud storage system, or a combination of the two.

Various applications and/or other functionality may be executed in the computing environment102according to various embodiments. In particular embodiments, various data is stored in a data store112that is accessible to the computing environment102. The data store112can be representative of one or more of data stores112as can be appreciated. The data stored in the data store112, for example, is associated with the operation of the various applications and/or functional entities described below.

In various embodiments, the computing environment102includes a management service114. The management service114may process and distribute data locally or to other devices connected to the network104. For example, the management service114can receive subject data from a subject data capture device108and store the data in a storage for subject data136in the data store112.

The management service114may include a data management console140and a data processing console142. In at least one embodiment, the data management console140distributes data to particular locations throughout the network environment100. For example, the data management console140may send user data132to the subject data capture device108so that the subject data capture device108can identify the current patient being processed for a customized protective device151. In various embodiments, the data management console140can receive data and store data locally on the data store112. For example, after the subject data capture device108measures particular data from a patient, the data is sent to the computing environment102. Continuing with this example, the data management console140stores the data into a storage location for modeling data124at the data store112.

In some embodiments, the data processing console142processes data for further use. In one or more embodiments, the data processing console142receives data from the data management console140and performs particular actions. In various embodiments, after a patient has been measured and their data has been stored, the data management console140sends subject data136to the data processing console142for further processing. Further processing performed by the data processing console142may include, but is not limited to, three-dimensional (3D) rendering, computer-aided design (CAD) file conversion, smoothing rendered surfaces, orienting data and locating relevant features, creating boundaries for 3D sketches, and processing additional features. In particular embodiments, the data processing console142performs analysis in a relatively quick timeline. For example, after the data is received from the subject data capture device108, the data processing console can process data in at least less than one day, two days, or three days. In one or more embodiments, the data processing console142produces manufacturing data136based on 3D-renderings of a customized protective device151. For example, the 3D rendering of a customized clavicle protective device for a particular patient may be exported to a CAD format and sent to the additive manufacturing device106for creation of the customized clavicle protective device.

In some embodiments, the data processing console142employs machine-learning techniques to recommend particular customized protective devices151based on previous prototype performances. For example, the computing environment102may receive input data regarding the performance of a customized protective device151and employ machine learning techniques to modify future protective devices.

The data store112may include, but is not limited to, the user data132, the modeling data134, subject data136, and manufacturing data138. In particular embodiments, the user data132acts as the head of a linked list of data. In some embodiments, each set of user data132has its own corresponding modeling data134, subject data136, manufacturing data138, and other particular data. For example, when a user is identified and added to the system, their corresponding modeling data134is linked to their particular user data132. In some embodiments, linking the data enables the system to track an individual's data to that particular patient.

In one or more embodiments, the user data132includes any information that pertains to the patient being assessed by the system. The user data may include, for example, a patient's age, height, weight, Body Mass Index (BMI), sport of interest, sport of injury, and any other data that pertains to the specific patient. For example, before examination, the computing environment102can receive particular information identifying the patient and store the information in the storage location of the user data132.

In various embodiments, the modeling data134includes any modeling data received and processed by the data processing console142. For example, the modeling data134can include, but is not limited to, 3D renderings, additional features, models of the subject, various renderings from different angles, CAD files, and reference human models. In various embodiments, after the data processing console142renders 3D structures of the particular patient, the data is stored in the storage location of the modeling data134. The completed CAD files may be transferred from the modeling data134to the manufacturing data138using the data management console140. In some embodiments, the modeling data134stores human models used for referencing when creating a new rendering of a particular patient's injury location.

In one or more embodiments, the subject data136can include any raw data captured by the subject data capture device108. For example, the subject data136can include, but is not limited to, 3D coordinate data, depth, height, width, point cloud data, and 3D triangulation data. In various embodiments, after the subject data capture device108performs a measurement of a subject, the data is sent to the computing environment102and stored for modeling purposes. In some embodiments, the data management module142can combine the subject data136and the modeling data134and reference the data as the subject data136to consolidate storage in the data store112.

In various embodiments, the manufacturing data138can include any information related to the manufacturing of customized protective devices151. The manufacturing data138may include, for example, the finalized CAD file, manufacturing commands, shipping information, deadlines, and any other information pertinent to the manufacturing process. In particular embodiments, the data management console140sends CAD file information obtained from the modeling data134to the storage location of the manufacturing data138. In one or more embodiments, the manufacturing data138is sent to the additive manufacturing device106to produce customized protective devices151. For example, once the data processing console142renders the 3D CAD file, the information is sent to the additive manufacturing device106to produce a 3D printed customized protective device151.

In one or more embodiments, the additive manufacturing device106can receive data from the computing environment102for processing and creating the customized protective device151. In some embodiments, the additive manufacturing device106can employ 3D printing techniques to produce the customized protective device151. In particular embodiments, the additive manufacturing device106can have more than one 3D printing device, where each 3D printing device is programmed to perform a distinct act. For example, a first 3D printer may produce a base lattice structure of the customized protective device151using a specific material and technique, while a second 3D printer may produce an exterior mold of the customized protective device151using a different material and technique for production. In at least one embodiment, the additive manufacturing device106is one individual 3D printing system with configurable settings. For example, the additive manufacturing device106may be capable of creating all components of the customized protective device151.

In various embodiments, the customized protective device151is defined as a padded customized material, designed to protect a particular area of the body for a specific individual. The customized protective device151may be created by the additive manufacturing device106. In one or more embodiments, the customized protective device151is designed and manufactured in distinct layers. In at least one embodiment, the customized protective device151includes base layer, a lattice layer, and a top layer. The base layer and the top layer may add increased rigidity to the customized protective device151. The lattice layer may increase the absorption capabilities of the customized protective device151, as discussed further below with respect toFIGS.32A-E.

In some embodiments, the subject data capture device108measures, records, and sends measurement data to the remaining components of the network environment100. In particular embodiments, the subject data capture device108includes, but is not limited to, a cellphone, tablet, or other mobile computing device with an integrated measurement tool, an attachable scanning system, or a dedicated scanning device. In some examples, the subject data capture device108can perform some or any of the actions of the computing environment102. For example, the subject data capture device108can process data locally and produce a CAD rendering of the patient's measurement data. In one or more embodiments, the subject data capture device108uses a data capturing device108to record point cloud data or triangle mesh data to formulate a 3D rendering of a body part of the patient. The subject data capture device108may store the data locally in a data store116, distribute the data across the network104to other devices, or perform a combination of the two. For example, the data distribution module120can send subject data to the computing environment102. In various embodiments, the data store116includes a script data144and a measurement data146. In one or more embodiments, the script data144can include any code that, when executed by a processor, causes the subject data capture device108to perform operations such as measuring patient information, processing the patient information, and modeling data associated with the patient. In particular embodiments, the operations performed by the subject capture device108in response to executing the script data144result in measured data from a particular patient that is aggregated and locally stored as the measurement data146.

In various embodiments, the subject data capture device108may also measure range of motion data. In one or more embodiments, the subject data capture device108predicts particular motions for the specific body part. In at least one embodiment, the subject data capture device108can capture new 3D scans based on the predicted range of motion of the particular patient. In particular embodiments, the subject data capture device108captures data as the patient moves their particular body part in various directions and using various methods. The subject data capture device108may create a snapshot of each position and create subject data136that relates to the range of motion of the subject. In various embodiments, the subject data capture device108or the computing environment102can employ machine learning algorithms, or any other algorithms, to facilitate predicting range of motions and recommending new customized protective devices151based on the range of motion data.

In some embodiments, the subject data capture device108captures the subject data136in the form of a point cloud or a polygon mesh from a 3D scanner. In at least one embodiment, the data collected by the subject data capture device108includes data from non-relevant sources such as surrounding objects. In various embodiments, the subject data capture device108considers the non-relevant data as noise. In particular embodiments, the subject data capture device108or the data processing console142can correct the subject data136to remove the noise collected during measurement.

In some embodiments, the computing environment102or the subject data capture device108utilizes a previously compiled data set from the subject data136. In various embodiments, a previously compiled data set is defined as subject data136of previous patients. In some embodiments, the computing environment102aggregates subject data136from past patients and uses the subject data136to approximate current or future modeling. The previously compiled data set may include, but is not limited to, polygon meshes or point cloud data taken from model subjects of varying sizes and proportions. In some embodiments, the point clouds or meshes from the subject data136is aligned to a specific coordinate system, plane, or axis depending on the type of customized protective device151. The computing environment102may align and orient the point cloud or polygon mesh subject data136for a current patient by using previously compiled data sets. For example, if the current client is a 5′10″ male weighing 175 pounds, the computing environment102may compare the current subject data136to the previously collected subject data136of patients with a similar body composition. In particular embodiments, the extracted data sets also include labels in the form of meshes, bounding boxes, curves, points, or vectors that are correctly positioned on relevant anatomical landmarks.

In some embodiments, the computing environment102or the subject data capture device108receives subject data136and user data132(e.g., height and weight). In particular embodiments, the computing environment102or the subject data capture device108can parse the subject data136and the user data132for models that are within a defined range of similarity to the subject including factors such as size and gender. For example, searching for gender, size, proportion, or a combination thereof may quickly result in a smaller data set of reference models that are more likely to have similar anatomical feature sizes and/or proportions to the current patient. In various embodiments, the subject data136of the current patient is matched to each of the models in the set of models within the defined range of similarity. In at least one embodiment, the computing environment102or the subject data capture device108utilizes a point-set optimization algorithm that can minimize the distance between vertices in two polygon meshes or point clouds, such as between the models in the set of models and the subject data136. Some example optimization algorithms may include, but are not limited to, the Iterative Closest Point (ICP) and the related Globally Optimized ICP (GO-ICP) algorithms. In particular embodiments, the computing environment102or the subject data capture device108chooses optimization algorithm and runs the algorithm on reduced complexity or decimated data that gives a rough approximation of the relevant shape in question. In one or more embodiments, the first run of the algorithm selects a reference model or a set of reference models that are most similar to the subject data136. In at least one embodiment, the subject data136is matched against the smaller reference data set with higher-precision settings.

Once the subject data136is aligned closely to similar models from the reference set, more localized methods may be used to precisely locate and label features. In some embodiments, the computing environment102or the subject data capture device108uses principal component analysis (PCA) tools to evaluate a region where a bone or limb is expected to be located. In various embodiments, the computing environment102or the subject data capture device108uses local minimum or maximum analysis to precisely locate a bony protrusion or joint. In one or more embodiments, the computing environment102or the subject data capture device108uses neural networks to find these more precise landmarks. In some embodiments, the computing environment102or the subject data capture device108outputs information about relevant anatomical landmarks, such as curves, points, vectors, boxes, spheres, meshes, or point clouds, for further steps in the process. In an embodiment, upon identifying and labeling the relevant anatomical landmarks, the computing environment102may generate a design for the customized protective device151, as discussed in detail below with respect toFIGS.3and4.

With reference toFIG.2, shown is a schematic block diagram of the computing environment102or the subject data capture device108, according to an embodiment of the present disclosure. In some embodiments, the computing environment102or the subject data capture device108includes one or more computing devices200. In particular embodiments, each computing device200includes at least one processor circuit, for example, having a processor210and a memory240, both of which are coupled to a local interface202. To this end, each computing device200may include, for example, at least one server computer or like device. The local interface202may include, for example, a data bus with an accompanying address/control bus or other bus structure as can be appreciated.

In at least one embodiment, stored in the memory240are both data and several components that are executable by the processor210. In particular embodiments, stored in the memory240and executable by the processor210are the management service114, the measurement module118, the data distribution module120, and potentially other applications. In one or more embodiments, also stored in the memory240may be a data store112, a data store116, and other data. In addition, an operating system may be stored in the memory240and executable by the processor210.

It is understood that there may be other applications that are stored in the memory240and are executable by the processor210as can be appreciated. Where any component discussed herein is implemented in the form of software, any one of a number of programming languages may be employed such as, for example, C, C++, C#, Objective C, Java®, JavaScript®, Perl, PHP, Visual Basic®, Python®, Ruby, Flash®, or other programming languages.

In some embodiments, a number of software components are stored in the memory240and are executable by the processor210. In this respect, the term “executable” means a program file that is in a form that can ultimately be run by the processor210. Examples of executable programs may be, for example, a compiled program that can be translated into machine code in a format that can be loaded into a random access portion of the memory240and run by the processor210, source code that may be expressed in a proper format such as object code that is capable of being loaded into a random access portion of the memory240and executed by the processor210, or source code that may be interpreted by another executable program to generate instructions in a random access portion of the memory240to be executed by the processor210, etc. In various embodiments, an executable program may be stored in any portion or component of the memory240including, for example, random access memory (RAM)220, read-only memory (ROM)230, hard drive, solid-state drive, USB flash drive, memory card, optical disc such as compact disc (CD) or digital versatile disc (DVD), floppy disk, magnetic tape, or other memory components.

In particular embodiments, the memory240is defined herein as including both volatile and nonvolatile memory and data storage components. In some embodiments, volatile components are those that do not retain data values upon loss of power. In at least one embodiment, nonvolatile components are those that retain data upon a loss of power. Thus, the memory240may include, for example, random access memory (RAM)220, read-only memory (ROM)230, hard disk drives, solid-state drives, USB flash drives, memory cards accessed via a memory card reader, floppy disks accessed via an associated floppy disk drive, optical discs accessed via an optical disc drive, magnetic tapes accessed via an appropriate tape drive, and/or other memory components, or a combination of any two or more of these memory components. In addition, the RAM220may include, for example, static random access memory (SRAM), dynamic random access memory (DRAM), or magnetic random access memory (MRAM) and other such devices. The ROM230may include, for example, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or other like memory device.

Also, the processor210may represent multiple processors210and/or multiple processor cores and the memory240may represent multiple memories240that operate in parallel processing circuits, respectively. In such a case, the local interface202, network interface250, and/or I/O interface230may be an appropriate network that facilitates communication between any two of the multiple processors210, between any processor210and any of the memories240, or between any two of the memories240, etc. The local interface202may include additional systems designed to coordinate this communication, including, for example, performing load balancing. The processor210may be of electrical or of some other available construction.

Although the management service114, the measurement module118, the data distribution module120, and other various systems described herein may be embodied in software or code executed by hardware as discussed above, as an alternative the same may also be embodied in dedicated hardware or a combination of software/hardware and dedicated hardware. If embodied in dedicated hardware, each can be implemented as a circuit or state machine that employs any one of or a combination of a number of technologies. These technologies may include, but are not limited to, discrete logic circuits having logic gates for implementing various logic functions upon an application of one or more data signals, application-specific integrated circuits (ASICs) having appropriate logic gates, field-programmable gate arrays (FPGAs), or other components, etc.

The flowcharts ofFIGS.3and4may show the functionality and operation of an implementation of portions of the management service114, the measurement module118, the data distribution module120, and any other particular program. If embodied in software, each block may represent a module, segment, or portion of code that includes program instructions to implement the specified logical function(s). The program instructions may be embodied in the form of source code that includes human-readable statements written in a programming language or machine code that includes numerical instructions recognizable by a suitable execution system such as a processor210in a computer system or other system. The machine code may be converted from the source code, etc. If embodied in hardware, each block may represent a circuit or a number of interconnected circuits to implement the specified logical function(s).

Although the flowcharts ofFIGS.3and4show a specific order of execution, it is understood that the order of execution may differ from that which is depicted. For example, the order of execution of two or more blocks may be scrambled relative to the order shown. In various embodiments, two or more blocks shown in succession inFIGS.3and4are executed concurrently or with partial concurrence. Further, in some embodiments, one or more of the blocks shown inFIGS.3and4may be skipped or omitted. In addition, any number of counters, state variables, warning semaphores, or messages might be added to the logical flow described herein, for purposes of enhanced utility, accounting, performance measurement, or providing troubleshooting aids, etc. It is understood that all such variations are within the scope of the present disclosure.

In some embodiments, any logic or application described herein, including the management service114, the measurement module118, the data distribution module120, and any particular program, that includes software or code can be embodied in any non-transitory computer-readable medium for use by or in connection with an instruction execution system such as, for example, a processor210in a computer system or other system. In this sense, the logic may include, for example, statements including instructions and declarations that can be fetched from the computer-readable medium and executed by the instruction execution system. In the context of the present disclosure, a “computer-readable medium” may be any medium that may contain, store, or maintain the logic or application described herein for use by or in connection with the instruction execution system.

In one or more embodiments, the computer-readable medium includes any one of many physical media such as, for example, magnetic, optical, or semiconductor media. More specific examples of a suitable computer-readable medium would include, but are not limited to, magnetic tapes, magnetic floppy diskettes, magnetic hard drives, memory cards, solid-state drives, USB flash drives, or optical discs. Also, the computer-readable medium may be a random access memory (RAM) including, for example, static random access memory (SRAM) and dynamic random access memory (DRAM), or magnetic random access memory (MRAM). In addition, the computer-readable medium may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or other type of memory device.

Further, any logic or application described herein, including the management service114, the measurement module118, and the data distribution module120, may be implemented and structured in a variety of ways. For example, one or more applications described may be implemented as modules or components of a single application. Further, one or more applications described herein may be executed in shared or separate computing devices or a combination thereof. For example, a plurality of the applications described herein may execute in the same computing device200or in multiple computing devices in the same computing environment102or subject data capture device108. Additionally, it is understood that terms such as “application,” “service,” “system,” “engine,” “module,” and so on may be interchangeable and are not intended to be limiting. For example, while specific functionality may be described as happening by a specific application (e.g., the management service114, the measurement module118, and the data distribution module120), it us understood that the functionality described may be interchangeable and is not intended to be limiting to a specific component.

Referring now toFIG.3, illustrated is an example flowchart of a process300for measurement, modeling, and creation of the customized protective device151, according to one embodiment of the present disclosure. In particular embodiments, the process300includes a high-level approach for creating customized protective devices151. In various embodiments, the customized protective devices151are described with respect to clavicle injuries, but the process300is applicable to any injured body part that could benefit from a customized protective device151. For example, the customized protective device151may be produced for a patient with a shin splint or a patient with a large bruise. In at least one embodiment, the customized protective device151takes on any particular shape.

At box302, the process300includes capturing anatomical data. In particular embodiments, the anatomical data is captured from a subject, such as a patient with an injury. In some embodiments, the subject data capture device108may be or may include a 3D scanner, and the subject data136may be a 3D scan captured by the scanner. Various types of 3D scanners may be used, such as a structured-light scanner, an infrared scanner, a mobile computing device with built-in scanning capabilities, a time-of-flight laser scanner, a triangulation-based laser scanner, 3D light detection and ranging (LIDAR) scanner, or other suitable scanning device for obtaining a 3D scan. In some embodiments, the subject data received from the subject data capture device108may be in the form of a point cloud (i.e., a set of data points arranged in 3D space) or a triangle mesh (i.e., a mesh of interlocking triangular surfaces), although other suitable types of polygon mesh may be used. In some embodiments, relevant anatomical features including bone structures, bruises, or pain points are located using 2 or 3-dimensional markings on a patient and captured alongside other relevant patient data. In other embodiments, data captured from the subject may include motion tracking or 3D scans or images taken at several positions including functional weight bearing positions based on the specifications of the subject.

At box304, the process300includes a data modeling process. In an example, the data processing console142may process subject data received from the subject data capture device108and create a digital model of a customized protective device151for the intended subject. In doing so, the data processing console142may utilize various computer-aided design (CAD) software capabilities. In some embodiments, a human user may validate results from data processing console142. In some embodiments, the computing environment102may be designed to easily receive inputs from a human user. In one or more embodiments, this may involve allowing the user to correct some aspects of the customized protective device151design in real time, such as identifying boundary locations, and saving more complex, longer runtime calculations to be completed afterwards. In some examples, the data processing console142may be configured for use by a trained design engineer, a medical professional, or a subject without any CAD experience. In some embodiments, the data processing console142is able to create repeatable, customized protective devices151quickly and easily while still enabling flexible changes based on subject specifications.

At box306, the process300includes manufacturing the customizable protective device151, according to one embodiment of the present disclosure. The additive manufacturing device106may create customized protective devices151using a digital model created by the data processing console142. In some embodiments, the additive manufacturing device106may be or may include a 3D printer, such as a stereolithography (SLA) printer, although other suitable additive manufacturing techniques may be used. In some embodiments, the properties of the material used to form the customized protective device151generally depend on the application and intended purpose of the customized protective device151. As described below, certain types of protective devices may provide direct impact shielding from injured or previously injured body portions, for example, by creating the customized protective device151with a bridge or dome structure.

For such customized protective devices151, the material used may be highly impact resistant and rigid enough to resist deformation. In some embodiments, the material used for these devices may have an Izod impact strength that is equal to or greater than about 60-100 J/m, about 60-70 J/m, about 70 J/m, about 70-80 J/m, about 80-90 J/m, or about 90-100 J/m. In at least one embodiment, the material demonstrates a flexural modulus that is equal to or greater than about 0.4-0.9 GPa, about 0.4-0.5 GPa, about 0.5 GPa, about 0.5-0.6 GPa, about 0.6-0.7 GPa, about 0.7-0.8 GPa, or about 0.8-0.9 GPa. Other types of protective devices may prevent or inhibit rotation or movement of joints. For such applications, it may be advantageous to use a material that emphasizes rigidity over impact resistance. Additionally, the material may be sufficiently robust such that flexing is unlikely to cause material failure. In some embodiments, the material for devices intended to prevent or inhibit rotation or movement of joints may have a flexural modulus that is equal to or greater than 0.85 GPa and an elongation at break of more than 50% in tensile testing. In various embodiments, the material of the protective devices is biocompatible and resists deformation during exposure to heat up to 150 degrees fahrenheit. In some embodiments, a customized protective device151may be formed of polypropylene photopolymer, although other suitable materials satisfying the material properties may be used.

Referring now toFIG.4, illustrated is an example flowchart of the process400for the modeling of the customized protective device151, according to one embodiment of the present disclosure. In particular embodiments, the process400generally relates to the modeling procedure of the data processing console142, such as the data modeling process of box304described above with respect toFIG.3. In some embodiments, the process400is performed to produce a 3D model of a subject using the corresponding subject data136.

At box402, the process400includes orienting data. To aid the orientation process, one or more tracking dots (or other suitable markings) may be placed on the injured location of the patient to enhance the scanning capabilities of the subject data capture device108and/or to provide additional or more targeted data for modeling the injured location. In one or more embodiments, adding a tracking dot can increase the measurement ability of the subject data capture device108by providing the subject data capture device108with a focal point during measurements. After the subject data capture device108records measurements of a particular patient, the subject data capture device108may send the measured subject data136to the computing environment102. In one or more embodiments, the computing environment102receives the measured subject data136in the form of a polygon mesh or point cloud data set.

In particular embodiments, the data processing console142orients the subject data136by positioning the measured subject data136in the correct 3D location. In some embodiments, the data management console140uses the current subject data136to search the data storage112for similar subject data136. In at least one embodiment, the data management console140compiles all similar previously collected subject data136. In one or more embodiments, the data processing console142compares current subject data136to previously collected subject data136to enhance the modeling of the current subject data136. For example, the data processing console142compares subject data136of the previously created model to the current subject data136. Continuing this example, the data processing console142makes adjustments to the subject data136of the current model based on the subject data136of the previously created model. In at least one embodiments, the data processing console142uses similar previously recorded subject data136to accurately align the subject data136of the current patient. In various embodiments, the data processing console142aligns the subject data136in a three coordinate axis system, which corresponds to the three coordinate axis system of the world. For example, when creating a 3D scan of an acromioclavicular (AC) joint, the polygon mesh of the subject data136is properly aligned to a consistent position in 3D digital space.

At box404, the process400includes locating relevant features from the anatomical scan. In some embodiments, the located relevant features include anatomical landmarks from the subject data136. The shape and functions of the customized protective devices151may often be parametrically determined by particular bones, joints, or muscle locations. In various embodiments, if the features can be reliably and precisely identified, the final customized protective device151can be more standardized. For example, a customized protective device151made for a subject may be the same or similar when created from two different sets of subject data136from the same subject. In one or more embodiments, the same devices created for different subjects perform the same functions when worn by the subjects even if the shapes or sizes vary considerably.

In some embodiments, the data processing console142may match, using a closest point optimization algorithm or another similar algorithm, the subject data136in the form of a polygon mesh or point cloud to a set of reference meshes, depth images, or point clouds that contain anatomical data from human models of similar sizes. This process can take on a hierarchical structure. The data processing console142may search through the subject data136and select a set of reference data captured from human models that have similar relevant characteristics to the subject, such as size and anatomical features included in the scan. In some embodiments, the data processing console142runs a closest point optimization algorithm to test the match of the subject data136to each input in the reference set using meshes or point clouds of a reduced size meant to approximate the general shape of the desired anatomical feature. Once the best reference model is selected, the data processing console142may run a similar optimization algorithm or series of algorithms to more precisely match the subject data136to the reference data gathered from the modeling data134. After the subject data136is more closely matched to the reference data that contains labeled anatomical landmarks, the data processing console142may run various other algorithms on localized regions of interest including principal component analysis, local minimum or maximum analysis, neural networks trained with curvature maps, raw 3D data, or 2D projections, or other related algorithms. In one or more embodiments, these methods may then export precise labels and information about the exterior surface, underlying bone or muscle structures, or limbs of the subject for subsequent use in the process400. In various embodiments, this information may take the form of 3D curves, points, vectors, planes, spheres, cylinders, meshes, point clouds, or orthographic projections that can correspond to bones, joints, protrusions, or surface contours.

At box406, the process400includes creating boundaries and 3D sketches. In various embodiments, the data processing console142uses the data produced after orienting and locating the relevant features. In some embodiments, the shape of the customized protective device151may be a parametric function determined from standardized measurements or metrics taken directly from the patient data. The shape, form, and function of the customized protective device151may be based on functionally or clinically relevant inputs instead of pre-determined dimensions. For example, one feature of a disclosed thumb guard design is that it may extend across the surface of the subject's hand to the midline between the subject's middle and ring fingers. In various embodiments, this is opposed to a traditional approach of setting devices dimensions to have a fixed width and curvature for a given size.

In some embodiments, 3D sketches or boundaries can also be used to demarcate certain relevant features of the final customized protective device151, such as lofted bumps, channels, and cutouts. In some embodiments, the data processing console142may create a 3D device boundary by moving points orthogonal to relevant anatomical landmarks along a polygon mesh of the subject data. The data processing console142may find a tangent vector of a 3D curve at a relevant position and calculating the cross-product of that vector with the normal of a polygon mesh at the closest position. In some embodiments, the vector may also be re-calculated at discrete increments to maintain consistency. In at least one embodiment, a two-dimensional (2D) sketch of a device may be projected onto a polygon mesh of the subject's data from a locally defined plane or surface. In one or more embodiments, a human user may also alter the location of the landmarks or device boundary to suit the particular specifications of a subject or validate results given automatically by the data processing console142.

At box408, the process400can include rendering surfaces. In at least one embodiment, the data processing console142can create a continuous surface of geometry that fits, at least in part, to the subject data136at the relevant locations marked by the 3D curves created in the boundary creation. In some embodiments, the subject data136is represented in a discretized format such as a polygon mesh or point cloud. In some embodiments, continuous geometries have many benefits over discrete representations including reduced file sizes, greater case and freedom when performing CAD modeling operations, mathematical smoothness, and greater control of tolerance.

In some embodiments, the process of generating this piece of continuous geometry involves first creating 3D curves that fit on the polygon mesh and then subsequently generating a Non-uniform rational B-spline (NURBS) surface from those curves. In some embodiments, the subject polygon mesh can first be sectioned to isolate the minimum area to create the customized protective device151corresponding to the boundary of the customized protective device151. In various embodiments, the data processing console142isolates the minimum area of the polygon mesh by referencing the boundary of the customized protective device151. In some embodiments, the data processing console142creates new boundaries for the polygon mesh by expanding the boundary of the customized protective device151by a predetermined factor. In various embodiments, the data processing console142decreases computational stress by redefining the rendering surfaces of the polygon mesh. By reducing the target location for rendering, the data processing console142reduces the computational stress on the computing environment102. For example, if the data processing console142renders a customized protective device151for a shoulder, the data processing console142can reduce the computational stress on the computing environment by removing unnecessary chest, neck, and head data from the rendering. Oftentimes, a series of planes or surfaces spaced at discrete intervals may be generated and used to intersect the mesh, resulting in polylines or curves. A polyline may be defined as a line created by connecting a set of points with consecutive lines. In some embodiments, the process of plane spacing can be more simply described as sampling the shape and curvature of the mesh at discrete intervals. In other embodiments, curves or curve networks may be generated directly from the principal curvature of the mesh and optimized for flow direction.

For some customized protective devices151that have features that deviate from the subject data136, the curves may be deformed using vector fields, simulated forces, or intersecting geometries, among other curve deformation techniques. Deviations may occur in the customized protective device151when a patient has recently had surgery and the customized protective device151is designed to avoid stiches. In one or more embodiments, the exact deformation may be based on the function of the customized protective device151and the specific specifications of the patient. These curves, deformed or not, may be used to create a surface or series of surfaces, using loft, network surface, or other relevant CAD operations, that fit to the polygon mesh at least in part with a defined tolerance. In various embodiments, the surface may be first generated from the curves before being deformed by a simulated force, vector field, or simulated collision with geometry.

In some embodiments, the data processing console142offsets data points relative to the body part of interest. The data processing console142may determine offset data point locations by placing the point a certain distance away from the polygon mesh data. In particular embodiments, the data processing console142connects offset points to form a curve a certain distance above the body part of interest. In some embodiments, the data processing console142incorporates this raised curve to reduce contact between the body part of interest and the customized protective device151. In at least one embodiment, by adding a raised portion to the customized protective device151above the injured body part, the customized protective device151can distribute force through other parts of the customized protective device151and away from the body part of interest.

At box410, the process400includes smoothing rendered surfaces. In some embodiments, the quality of the surface created directly from a set of curves can fall short of standards such as smoothness or fairness. Because of this, the data processing console142, in at least one embodiment, uses an optimization algorithm to correct these errors without losing fit to the measured subject data136. In some embodiments, the surface is the direct input to the algorithm while other embodiments might leverage conversion to a quadrangulate mesh. In either format, competing forces may be applied to the input, which converge to an equilibrium that accomplishes smoothening of the rendered surfaces.

In some embodiments, the system attempts to a balance smoothness and fit to the mesh. In various embodiments, one of the competing forces may be a Laplacian smoothing method that recalculates the position of each vertex based on information from its neighboring vertices. The Laplacian smoothing method may result in shrinkage of the surface and cause a loss of toleranced fit to the subject data136. In one or more embodiments, another such force used to address the shrinkage of the surface is an attraction force algorithm from the polygon mesh of the subject data136. In some embodiments, the data processing console142can add additional forces to, for example, limit stress concentrations, create features, and smooth transitions between features. In some embodiments, adding additional forces by the data processing console142may be run iteratively until the surface meets the goals. In some embodiments, the data processing console142converts the mesh surface output from the smoothing process to a NURBS surface or polysurface. By converting the output of the smoothing process from a mesh surface to a NURBS surface or polysurface, the data processing console142may reduce the processing demands of the computing environment102. A reduction in processing demands may occur when the data processing console142simplifies or removes more complicated data points generated by the smoothing algorithm.

At box412, the process400includes processing additional features. Additional features may include a thickness of the customized protective device151, customization of markings on the customized protective device151, a composition of the material or layers of the customized protective device151, or any other additional features. In some embodiments, the 3D curve marking the boundary of the customized protective device151is projected from the subject mesh or pulled onto the surface. In various embodiments, the curve is directly used to split the surface at the relevant location. In one or more embodiments, the curve may be used to create a surface or body to accomplish the splitting. In some embodiments, the trimmed surface is thickened into a solid body with a thickness determined by the use case and material. In one or more embodiments, the thickness of the customized protective device151may vary, being thicker in areas with higher stress concentrations. In particular embodiments, the data processing console142uses Finite Element Analysis or topology optimization methods to optimize the strength and weight of the customized protective device151.

In some embodiments, various functional features including hinges, strap connectors, and screw holes may be added to the design. In at least one embodiment, non-functional features such as subject specific information including name and sports number as well as company or team branding information are added to the surface of the customized protective device151in order to increase the level of customization. In some embodiments, the additive manufacturing device106rounds or fillets the edges of the customized protective device151to enhance the fit of the customized protective device151for the subject. In some embodiments, lattice structures may be added to decrease the weight, achieve energy absorption characteristics specified, or optimize bending/splinting properties for a specific use case. The actions performed in the process400may be accomplished in different orders depending on the specific specifications of the customized protective device151.

Referring now toFIGS.5A-D, illustrated is an exemplary modeling data134for producing a customized protective device for an acromioclavicular joint, according to one embodiment of the present disclosure. In some embodiments, the subject data capturing device108captures subject data136of the particular patient. For example, the subject data capturing device108captures subject data136in the form of a polygon mesh by a 3D scanner, as described above with respect to the box302of process300. In an embodiment, the position of the injured joint is marked by a 3D tracking dot adhered to the joint before the 3D scan is taken. In various embodiments, the data processing console142properly aligns the polygon mesh of the subject data136to a consistent position in 3D digital space determined by a second reference anatomy. In an embodiment, the data processing console142aligns the reference anatomy with the sagittal plane on an XY-plane of the 3D coordinate system, and the coronal plane aligned with the XZ-plane. In various embodiments, the chin is pointed towards the negative y-axis and the base of the sternum is aligned on the XY-plane. This process may be performed by the data processing console142, as described above with respect to the box402of the process400.

In particular embodiments, once aligned, the data processing console142or trained user of the program can locate relevant anatomical features. In various embodiments, an input for the data processing console142or a trained user for locating relevant anatomical features is a roughly circular mesh501B centered on the 3D tracking dot that marks the location of the AC Joint.

In one or more embodiments, the subject data136is processed by the data processing console142, which generates three individual planes. In some embodiments, the data processing console142uses the individual planes to crop the polygon mesh down the midline of the chest, at the apex of the armpit and midway along the front of the neck perpendicular to the local surface normal.

In various embodiments, the data processing console142creates a bounding box501C from the plane corresponding to the midline of the chest. In various embodiments, the bounding box501C is used to measure the approximate chest depth (back of the chest to the front) and the shoulder width (from the midline of the sternum to the furthest point on the shoulder). The data processing console142may create the bounding box501C to define the area in which the customized protective device1200is created. The data processing console142may store this data in the modeling data134for further processing, such as the processing that results inFIGS.6A-6Fdescribed below.

Referring now toFIGS.6A-F, illustrated is exemplary modeling data134for producing a customized protective device for the acromioclavicular joint, according to one embodiment of the present disclosure. In particular embodiments, the data processing console142processes the subject data136to refine the location of rendering and model creation. In some embodiments, the polygon mesh501B of the joint outline, the cropped polygon mesh, a Boolean value for right or left shoulder, and the corresponding measurements (e.g., the chest depth and shoulder width) are processed by the data processing console142, which generates an outline of a shape602B of a customized protective device1200, which is described below with respect toFIGS.12A-B. In some embodiments, and referring toFIG.6B, the data processing console142finds the arithmetic mean vertex location and surface normal vector of the joint polygon mesh501B. In one or more embodiments, the data processing console142uses the joint polygon mesh501B to create a plane601B perpendicular to the vector. With respect toFIG.6A, the data processing console142may use the plane601B to create a bounding box601A around the joint mesh outline, where a top surface of the bounding box601A is the location of the plane601B and a bottom surface of the bounding box601A is a location of a lower-most location of the shape602B. In various embodiments, the data processing console142translates the plane601B along the average normal vector by a distance equal to three times the height of the bounding box601A. In particular embodiments, the data processing console142aligns the local x-axis of the created plane with the direction of the world x-axis, thus aligning the y-axis with the axis of the shoulder.

In one or more embodiments, and referring now toFIGS.6C-F, the data processing console142creates a standardized sketch shape601C on the world XY plane by interpolating points moved from the origin by defined distances. In various embodiments, the data processing console142uses the standardized sketch shape601C to determine the polygon mesh dimensions along with providing the dimensionality of the customized protective device1200. For example, the standardized sketch shape601C and size has been experimentally determined to fit a 200 lb, 5′10″ male college football player with a 250 mm chest width and 265 mm chest depth as measured using methods described above. Continuing this example, the width of the shape601C is 80 mm (0.3-0.35 of the chest width), and the length of the standardized sketch shape601C is 115 mm (0.40-0.45 of the chest depth). In one or more embodiments, the data processing console142scales the size of the standardized sketch shape601C based on the measurements of the subject. The data processing console142may accomplish the scaling by dividing each of the measurements by the dimensions used to determine the standardized sketch shape601C. In some embodiments, the data processing console142uses a factor of change to scale the size of the standard shape601C so that it fits the subject data136. In various embodiments, once the data processing console142scales the measurements of the subject, a rectangular box601E is used to demarcate the region that is lofted above the skin surface to distribute force away from the injured joint. In one or more embodiments, the data processing console142sets the width of the rectangular box601E to a factor of 0.5 times the sketch width, and the length is set to be 0.4 of the sketch length. In some embodiments, the data processing console142creates a 2D bounding box around the sketch shape. Bounding curves601F and602F that are parallel with the length midline are isolated and moved away from the origin 0.2 times the width of the sketch. If the subject specifies a device for their opposite shoulder, or any other body part that is symmetrical, the data processing console142may mirror the shape601C about the middle axis.

Referring now toFIGS.7A-E, illustrated is exemplary modeling data134for producing a customized protective device for the acromioclavicular joint, according to one embodiment of the present disclosure. In various embodiments, the standardized sketch shape601C, rectangular box601E, and bounding curves601F and602F are translated from the world coordinate system to the local coordinate system described by the plane601B created above the joint outline. In some embodiments, the data processing console142projects the standardized sketch shape601C and the lofted rectangular box601E onto the polygon mesh. In some embodiments, the data processing console142extrudes the bounding curves601F and602F along the same projection vector into cutting surfaces. In one or more embodiments, the data processing console142generates a third surface703C perpendicular to a first surface701C and a second surface702C. In various embodiments, the third surface703C is 1.2 times below the distance between the plane and the furthest point on the standardized sketch shape601C. In particular embodiments, the data processing console142or a trained user varies the shape of the outline and/or lofted boundary to ensure the product is suited for the particular specifications of the subject depending on factors such as injury severity, preference, and sport prerequisites. In one or more embodiments, the data processing console142takes the information from the sketch alignment and creates a minimally sized bounding space on the subject polygon mesh that a continuous surface is fit to in future steps. In various embodiments, the data processing console142creates a minimally sized bounding space by reducing the area and volume of the polygon mesh while still containing every point of the continuous surface. In one or more embodiments, the data processing console142preserves accuracy and reduces computational effort by reducing the bounding space of the subject polygon mesh.

Referring now toFIGS.8A-D, illustrated is exemplary modeling data134for producing a customized protective device for the acromioclavicular joint, according to one embodiment of the present disclosure. Once the minimum polygon mesh surface is isolated, the data processing console142segments a mesh801B using evenly spaced perpendicular surfaces. In various embodiments, the data processing module142segments the mesh801B to facilitate faster processing and to allow line manipulation when defining particular features. For example, the data processing console142manipulates the line segments when a bump is defined (seeFIGS.9A-C). The two boundary surfaces may be parallel with the shape of the projected sketch601C and the rectangular box601E. In some embodiments, the mesh801B is used to create a smooth flowing surface that accurately fits the customized protective device1200tolerances. In various embodiments, the spacing between the surfaces or planes is set at 1 mm for the particular customizable protective device1200. When intersected with the mesh, the data processing console142may create 2D polylines that sample the mesh shape and curvature to a very fine tolerance. The resulting polylines may then be divided into 1 mm long segments and the evenly spaced points are used to interpolate smooth, continuous NURBS curves. In various embodiments, the data processing console142selects a curve801C that comes closest to intersecting the middle of the joint. In at least one embodiment, the rectangular curve used to mark the lofting area is extruded into a solid body801D that will be used to isolate the relevant curves.

Referring now toFIGS.9A-C, illustrated is exemplary modeling data134for producing a customized protective device for the acromioclavicular joint, according to one embodiment of the present disclosure. In some embodiments, the data processing console142manipulates the curves to create particular features. In particular embodiments, the curves are shattered or split at the boundaries of the extruded box and isolated for manipulation. In some embodiments, the data processing console142re-parameterizes the curves, divides them into equally-spaced segments, and the calculates their normal vectors to the polygon mesh. In some embodiments, the data processing console142applies a function, including but not limited to a sigmoid, Bezier, or Arc, to the magnitude of the normal vector. In at least one embodiment, the maximum vector is set by the data processing console142and can be altered by the user or the data processing console142for the specifications of a specific subject. In various embodiments, the data processing console142produces an arched curve901C that fits the end tangents of the non-segmented curves. In particular embodiments, the height of the middle of this arched curve901C is calculated from the base of the 3D tracking dot and is equal to 0.2 times the width of the bounding box in this case.

Referring now toFIGS.10A-D, illustrated is exemplary modeling data134for producing a customized protective device for the acromioclavicular joint, according to one embodiment of the present disclosure. In one or more embodiments, the data processing console142manipulates the surrounding curves to standardize the adjustments of the arched curve901C created for accommodating particular new features. In particular embodiments, the data processing console142adjusts the arched curve901C and other corresponding curves to produce a bump (pocket of air above the body part of interest) used to protect the AC joint of the subject against impact. For example, once the data processing console142lofts the arched curve901C into the desired shape, the data processing console142also lofts the surrounding curves with a parametrically graphed falloff using a Bezier Curve or other similar function. In at least one embodiment, the data processing console142deforms the curves closest to the middle curve the most and the ones closest to the rectangular boundary are hardly deformed. In some embodiments, the data processing console142creates the set of curves that define the bump used to protect the subject's AC joint against impact. In particular embodiments, the data processing console142joins the deformed curve segments to the full-length section curves. In one or more embodiments, the data processing console142fits a NURBS surface through these toleranced curves by a loft or network surface (or other suitable functions).

Referring now toFIGS.11A-D, illustrated is exemplary modeling data134for producing a customized protective device for the acromioclavicular joint, according to one embodiment of the present disclosure. In some embodiments, the surface created by the data processing console142may have defects in surface smoothness that can result in higher stress concentrations or poor product visual quality. In various embodiments, the data processing module employs smoothing techniques to account for discrepancies in the surface. In an embodiments, the data processing console142employs an optimization algorithm, which finds the equilibrium point between competing forces. In some embodiments, the data processing console142converts the surface to a quadrangulate mesh and a Laplacian smoothing force is exerted across all vertices. In various embodiments, selected vertices can have a competing force pulling them to the polygon mesh of the subject data136or fixing them in their original position. The quadrangulate mesh may be converted back to a NURBS surface. In at least one embodiments, the data processing console142produces a surface that is smooth and still accomplishes the tolerance for fitting the subject data136. For example, a maximum deviation of the surface to the subject data may be 0.5 mm in relevant locations.

After the surface shape is suitable, the 3D bounding curve created by the data processing console142may be projected or pulled onto the surface and used to separate the desired region. In some embodiments, branding, names, and numbers may be projected onto the surface and used to customize the customized protective device1200for the subject. In particular embodiments, the data processing console142thickens the surface to an appropriate thickness for the application, and the branding or subject information may be embossed or extruded into the final customizable protective device1200. In various embodiments, all sharp edges may be rounded or filleted to ensure proper fit of the product. In at least one embodiment, the thickness of the customized protective device1200is set to 3.5 mm, the top and bottom edges are filleted with a 1.5 mm radius, and the branding or subject information is extruded to 0.5 mm above the top surface. The edges and intersections with the body may also be filleted to reduce stress concentrations.

Referring now toFIGS.12A-B, illustrated is a rendered customized protective device1200for the acromioclavicular joint, according to one embodiment of the present disclosure. After the data processing console142creates the customizable protective device1200, the data processing console142may export the modeling data134to an online digital rendering service and send to the subject or a medical professional for review. Changes may be requested based on the use case, and the parameters of the customized protective device1200may be altered to best fit the specifications of the subject. Once the final customized protective device1200design is confirmed, the computing environment102exports the customized protective device1200model to a suitable 3D printing format. Suitable 3D printing file formats may include but are not limited to standard triangle language (STL), OBJ file type, or 3D manufacturing format (3MF). In some embodiments, the computing environment102performs slicing on the customized protective device1200model to formulate 3D printing instructions. In one or more embodiments, the computing environment102uploads the customized protective device1200model to a 3D printer that uses SLA technology. The 3D printer discussed herein may print the customized protective device1200. During, before, or after the printing process, the data processing console142may be employed to orient the customized protective device1200, such that the surface area per slice is minimized and no support structures are generated on the top surface.

In particular embodiments, the additive manufacturing device106prints the customized protective device1200and energy absorbent foam is adhered to the subject-facing side of the customized protective device1200with a rectangular or circular cutout around the joint. In alternative embodiments, the additive manufacturing device106prints 3D lattice structures to obtain the specified energy absorption characteristics. These lattice structures may be added as an additional feature to the customized protective device1200and may be 3D printed all at once in the same material as the entire device or adhered to the bottom like the foam.

Referring now toFIGS.13A-C, illustrated is exemplary modeling data134for producing a customized protective device for a thumb, according to one embodiment of the present disclosure. In particular embodiments, the subject data capture device108performs a substantially similar capturing technique as describe herein inFIG.5A-D. In some embodiments, relevant anatomical features may be marked by 3D curves. These curves may be generated by the data processing console142. In various embodiments, such as for creating a thumb guard, the data processing console142creates four curves1301B,1302B,1303B, and1304B that correspond to the bottom line of the knuckles, the web of the hand, the top of the thumb, and the palm profile of the thumb.

Referring now toFIGS.14A-D, illustrated is exemplary modeling data134for producing a customized protective device for the thumb, according to one embodiment of the present disclosure. In some embodiments, the data processing console142projects points orthogonally to the four reference curves to form the shape of the thumb guard. The data processing console142may find the tangent vector of a 3D curve at a relevant position and calculate the cross-product of that vector with the normal of a polygon mesh at the closest position. In various embodiments, the data processing console142recalculates the vector at discrete increments to maintain consistency.

For example, 15 points may be used to create a shape. In one or more embodiments, the shape is a parametric function of the subject's hand. For example, points0and15correspond to the width of the customized protective device1800and are located halfway between the middle and ring fingers. Continuing this example, the orthogonal distance between the bottom of the knuckles and bony protrusion of the ulnar styloid process is measured by the data processing console142. Continuing this example, point0is projected orthogonally 0.1-0.15 times the calculated distance. Continuing this example, point15is projected orthogonally 0.4-0.6 times the calculated distance. Continuing this example, points6,7, and8are on the same plane orthogonal to the thumb proximal phalanx axis and are located halfway between the thumb metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints. In some embodiments, a planar circle is used to approximate the shape of the thumb at points6,7, and8. In at least one embodiments, point7is located on the fingernail side of the thumb and points6and8are a 90-degree distance away from point7on the circle. In various embodiments, point12corresponds to the palm-side protrusion of the thumb metacarpal bone. In particular embodiments, point9corresponds to the thumb MCP joint. The data processing console142may calculate the distance between points9and12and use the distance to determine the offset from the curve of points10and11. In at least one embodiment, points13and14follow along just above the base of the hand metacarpals. The desired shape may be altered to meet the specific specifications of the subject. In some embodiments, a brace is used to prevent or support various injuries to the thumb including the thumb ulnar collateral ligament (UCL).

Referring now toFIGS.15A-C, illustrated is exemplary modeling data134for producing a customized protective device for the thumb, according to one embodiment of the present disclosure. In some embodiments, once the shape of the customized protective device1800is finalized, then two boundary surfaces are generated that follow the natural curvature of the hand and fit outside of the curve boundary of the customized protective device1800shape. In various embodiments, the data processing console142creates a boundary curve that follows the shape of the customized protective device1800on the palm. In one or more embodiments, the data processing console142uses the rendered shapes to generate the NURBS surface.

Referring now toFIGS.16A-D, illustrated is exemplary modeling data134for producing a customized protective device for the thumb, according to one embodiment of the present disclosure. In particular embodiments, the data processing console142generates a series of surfaces between the two surfaces. For example, the spacing between the surfaces or planes may be set at 1 mm. In some embodiments, when intersected with the mesh, the data processing console142creates 2D polylines that sample the mesh shape and curvature to a very fine tolerance, such as a maximum distance between the mesh shape and the curvature of 1 mm. In one or more embodiments, the data processing console142divides the resulting polylines into 1 mm long segments and the evenly spaced points are used to interpolate smooth, continuous NURBS curves. In at least one embodiment, the data processing console142groups the curves based on their positions on the hand. Grouping the curves may be accomplished by finding the first intersection curve that is periodic. In various embodiments, the data processing console142finds the first surface in the series that results in two continuous segments longer than the mean length of the curves minus two standard deviations. In some embodiments, the data processing console142find a point corresponds to the beginning of the web of the hand. In one or more embodiments, the curves are split at the web and the offset palm curve. In particular embodiments, the data processing console142splits the curves corresponding to the thumb and the hand above the web and interpolates to form a single continuous curve. In some embodiments, the data processing console142preforms the curve spilt as it is much simpler computationally to create one four-sided NURBS surface than a patchwork of surfaces. In at least one embodiment, after the smooth curves are created, the data processing console142joins the curves into a NURBS surface by means of a loft or network surface CAD operation.

Referring now toFIGS.17A-D, illustrated is exemplary modeling data134for producing a customized protective device for the thumb, according to one embodiment of the present disclosure. In some embodiments, the data processing console142converts the NURBS surface into a quadrangulate mesh1701B, optimized for smoothness, and fits to the subject data136using the defined methods. In various embodiments, the final surface fits the subject data136to a defined tolerance of 0.25 mm at all areas outlined by the 3D curve boundary. Once the data processing console142finalizes the surface, the data processing service142projects or pulls the 3D boundary onto the surface to isolate the desired shape. In some embodiments, the additive manufacturing device106projects branding and subject-specific information onto the surface of the customized protective device1800, as described below with respect toFIG.18, to increase the level of customization. In an embodiment, the surface may be thickened to an appropriate thickness and all sharp edges may be rounded. In various embodiments, the thickness of the customized protective device1800is set to 2 mm, the top and bottom edges are filleted with a 0.85 mm radius, and the branding or subject information is extruded to 0.25 mm above the top surface.

Referring now toFIGS.18A-C, illustrated is a rendered customized protective device1800for the thumb, according to one embodiment of the present disclosure. In various embodiments, the data processing console142exports the rendered customized protective device1800, the data processing console142sends the file to the subject or medical professional for review. In several embodiments, changes may be requested based on the use case and the parameters of the customized protective device1800are altered to best fit the specifications of the subject. In some embodiments, once the final customized protective device1800design is confirmed, the computing environment102exports the customized protective device1800model to a suitable 3D printing format. Suitable 3D printing file formats may include but are not limited to standard triangle language (STL), OBJ file type, or 3D manufacturing format (3MF). In some embodiments, the computing environment102performs slicing on the customized protective device1800model to formulate 3D printing instructions. In one or more embodiments, the computing environment102uploads the customized protective device1800model to a 3D printer that uses SLA technology. The 3D printer discussed herein may print the customized protective device1800. During, before, or after the printing process, the data processing console142or the additive manufacturing device106may orient the customized protective device1800, such that the surface area per slice is minimized and no support structures are generated on the bottom surface that may contact the subject's hand.

Referring now toFIGS.19A-B, illustrated is exemplary modeling data134for producing a customized protective device for a clavicle, according to one embodiment of the present disclosure. In particular embodiments, the subject data capture device108performs a substantially similar capturing technique as describe herein inFIGS.5A-D. In various embodiments, a customized protective device2600is produced for the clavicle, as described below with respect toFIGS.26A-B. The subject data capture device108may capture the subject data similarly toFIG.5A-D, but for a different area of the body. For example, the subject data capture device108may measure a 3D scan of the clavicle of a particular user. The subject data capture device108may scan the area and may produce a polygon mesh stored as subject data136. Before the scan, tracking dots may be added to accentuate the injured area when scanning with the subject data capture device108.

Referring now toFIGS.20A-C, illustrated is exemplary modeling data134for producing a customized protective device for the clavicle, according to one embodiment of the present disclosure. In various embodiments, the data processing console142locates relevant anatomical features from the subject data136. In particular embodiments, the data processing console142employs inputs that are a roughly circular mesh centered on the 3-dimensional tracking dot that marks the location of the AC Joint and a 3D curve created from interpolated points located on the mesh at the apex of the 3D tracking dots to locate relevant anatomical features, such as a path2001A of the collarbone. In various embodiments, the data processing console142creates a 3D curve2001C at the inflection point of curvature where the neck connects to the shoulder and chest.

Referring now toFIG.21A-C, illustrated is exemplary modeling data134for producing a customized protective device for the clavicle, according to one embodiment of the present disclosure. In some embodiments, the data processing console142uses these inputs to generate three planes and use them to crop the polygon mesh down the midline of the chest, at the apex of the armpit and midway along the front of the neck perpendicular to the local surface normal. In at least one embodiment, the data processing console142creates a bounding box2101C from the plane corresponding to the midline of the chest. The bounding box may be used to measure the approximate chest depth (back of the chest to the front) and the shoulder width (from the midline of the sternum to the furthest point on the shoulder). The measurements may be stored in the computing environment102for further processing. The data processing console142may store this data in the modeling data134for further processing, such as the processing that results inFIGS.22A-22Cdescribed below.

Referring now toFIGS.22A-C, illustrated is exemplary modeling data134for producing a customized protective device for the clavicle, according to one embodiment of the present disclosure. In some embodiments, the curve corresponding to the bone and neck shapes, a polygon mesh of the joint outline, the cropped polygon mesh, a Boolean value for right or left shoulder, and the corresponding measurements are fed into the data processing console142that generates an outline of the shape of the protective device. In some embodiments, the data processing console142finds the tangent vector of a 3D curve at a relevant position and calculates the cross-product of the vector with the normal of a polygon mesh at the closest position. The vector may also be re-calculated at discrete increments to maintain consistency. In particular embodiments, 12 points are used to create the shape. In various embodiments, the shape is a parametric function of the shape and size of the subject's torso as well as the length and diameter of their clavicle bone.

In a particular example, point0may be located just beyond the second tracking dot from the SC joint, although this may vary based on the location of the injury. Continuing this example, point10is located just below the highest point on the trap. Continuing this example, points11and12are interpolated between points0and10following the curvature of the neck. Continuing this example, points7and8may be positioned on either side of the bone and mark the clavicle bone width. In some embodiments, the data processing console142places the points at a distance 0.1 times the length of the clavicle bone curve from the AC joint endpoint. Continuing the previous example, the data processing console142parametrically determines points1-6based off the size of the subject. For the furthest point down the chest, point3may be set at between 0.6 and 0.75 times the height of the chest bounding box. In one or more embodiment, the data processing console142configures points5and6to decrease impingement with the shoulder during movement.

Referring now toFIGS.23A-G, illustrated is exemplary modeling data134for producing a customized protective device for the clavicle, according to one embodiment of the present disclosure. In some embodiments, the data processing console142creates 3D curves corresponding to the area of the torso using a series of surfaces or manual manipulation of the surfaces themselves. In particular embodiments, once these curves are created, the data processing console142uses the reference curve for the clavicle bone to separate segments evenly spaced with lengths 1.3 times the diameter of the bone. In some embodiments, this is accomplished by extracting several evenly spaced points from the clavicle curve and calculating the closest 10-200 vertices of the mesh.

In one or more embodiments, the data processing console142uses the average position and normal of the mesh vertices to offset the points from the mesh by a defined distance. In at least one embodiment, the data processing console142uses the average, instead of the vector at a specific point, to account for irregularities in mesh quality and the distortions caused by the tracking dots. In some embodiments, the offset points are interpolated into a curve that is then lofted into a surface and used to split the curves. In some embodiments, the data processing console142determines the intersection point of the surface with each curve to be the center of the clavicle bone. In various embodiments, the data processing console142multiplies the width of the clavicle by a factor of 1.3 and the resulting value is used to determine the length of each curve segment. The data processing console142may project the center point of each segment corresponding to the center of the clavicle onto the offset clavicle curve. In one or more embodiments, the data processing console142calculates the distance of this projection and uses this distance as the maximum magnitude for further processing. In some embodiments, the curves are re-parameterized, divided into equally spaced segments, and their normal vectors to the polygon mesh are calculated.

In particular embodiments, the data processing console142applies a function including but not limited to a sigmoid, Bezier, or Arc to the magnitude of the normal vector at each point along the segment. In at least one embodiment, the maximum vector is set by the height of the offset clavicle curve and can be altered by the user or the data processing console142for the specifications of a specific subject but is commonly set at 13 mm above the maximum point of the clavicle. In some embodiments, data processing console142produces a smooth, arched curve that fits the end tangents of the non-segmented curves. The separated segments may then be replaced with the lofted segments and joined back into their full-length counterparts.

Referring now toFIGS.24A-C, illustrated is exemplary modeling data134for producing a customized protective device for the clavicle, according to one embodiment of the present disclosure. In some embodiments, a second set of curves are formed corresponding to the outer surface of a customized protective device2600that have wider arches over the bone. In particular embodiments, the curves are 1.2-1.5 times the length of the inner curves. In some embodiments, using the outer curvature length of 1.2-1.5 times the length of the inner curvature is done to reduce stress concentrations of the customized protective device2600during impact by adding additional thickness at the areas of highest stress.

Referring now toFIGS.25A-E, illustrated is exemplary modeling data134for producing a customized protective device for the clavicle, according to one embodiment of the present disclosure. In some embodiments, once the set of curves corresponding to the top and bottom of the customized protective device2600are generated, the data processing console142uses the curves to create NURBS surfaces with the same shape using common CAD operations, such as a loft or network surface. The data processing console142may project or pull the 3D sketch of the boundary onto both surfaces and may use the 3D sketch to isolate the relevant shape. The top surface may then be offset by a defined distance and a closed surface may be used to connect the two surfaces a body. In some embodiments, the additive manufacturing device106may round or fillet the edges and add subject-specific information or branding to the customized protective device2600. In an embodiment, the thickness of the customized protective device2600is set to 4 mm, the top and bottom edges are filleted with a 1.5-2.0 mm radius, and the branding or subject information is extruded to 0.5 mm above the top surface. In some embodiments, the data processing console142sets the fit of the customized protective device2600to a maximum of 0.5 mm at the contact regions. In various embodiments, the customized protective device2600fits to the subject data at defined points on the chest and trap, but retains an arch shape to protect the clavicle from direct impacts.

Referring now toFIGS.26A-B, illustrated is a rendered customized protective device2600for the clavicle, according to one embodiment of the present disclosure. In some embodiments, after the data processing console142renders the customized protective device2600, it exports the customized protective device2600to the subject or medical professional for review. Changes may be requested based on the use case of the customized protective device2600, and the parameters of the customized protective device2600may be altered to best fit the specifications of the user. Once the final customized protective device2600design is confirmed, the computing environment102exports the customized protective device2600model to a suitable 3D printing format. Suitable 3D printing file formats include but are not limited to standard triangle language (STL), OBJ file type, or 3D manufacturing format (3MF). In some embodiments, the computing environment102performs slicing on the customized protective device2600model to formulate 3D printing instructions. In one or more embodiments, the computing environment102uploads the customized protective device2600model to a 3D printer that uses SLA technology. The 3D printer discussed herein may print the customized protective device2600. During, before, or after the printing process, the data processing console142or the additive manufacturing device106may be used to orient the customized protective device2600, such that the surface area per slice is minimized and no support structures are generated on the top surface.

In some embodiments, the additive manufacturing device106can print the customized protective device2600and an energy absorbent foam may be adhered to the subject-facing side of the customized protective device2600with a cutout around the maximum height of the channel. In particular embodiments, the additive manufacturing device106uses 3D printed lattice structures to obtain the specified energy absorption characteristics. In various embodiments, the lattice structures may be added as an additional feature to the customized protective device2600and may be 3D printed all at once in the same material as the entire device or adhered to the bottom like the foam, as described in detail below with respect toFIGS.32A-E. In some embodiments, the lattice structure reduces stress on the injured body part.

Referring now toFIG.27, illustrated is exemplary modeling data134for producing a customized protective device for an ankle, according to one embodiment of the present disclosure. In some embodiments, anatomical data is captured of the subject's foot using the subject data capture device108. In some embodiments, the subject data capture device108captures subject data136in the form of a polygon mesh by a 3D scanner. In some embodiments, the polygon mesh of the subject data136is properly aligned to a consistent position in 3D digital space determined by a second reference anatomy. This process may be accomplished completely by the data processing console142. In various embodiments, the reference anatomy is aligned with the base of the heel at the origin. In one or more embodiments, the sole of the foot is aligned flat on the XY plane and the axis of the foot is aligned with the positive X-axis.

Referring now toFIG.28A-D, illustrated is exemplary modeling data134for producing a customized protective device for the ankle, according to one embodiment of the present disclosure. In some embodiments, a series of surfaces are created at 1 mm intervals. When intersected with the mesh, the data processing console142may create 2-dimensional polylines, which may sample the mesh shape and curvature to a very fine tolerance. In particular embodiment, the resulting polylines are then divided into 1 mm long segments and the evenly spaced points are used to interpolate smooth, continuous, and periodic NURBS curves. In various embodiments, a spheroid is fit to each of the malleoli center points with a radius equal to ⅙ of the width of the shin at the high ankle. In one or more embodiments, the data processing console142moves the spheroid by a defined distance away from the mesh. In various embodiments, the intersecting curves are then split and deformed to fit over the spheroid. The same process may be repeated for both malleoli and the 5th metatarsal base. In at least one embodiment, the data processing console142generates a second set of curves for the shin portion of the brace using similar methods. In various embodiments, the data processing console142uses the curves to create two surfaces using loft, network surface, or other related CAD methods.

Referring now toFIG.29A-B, illustrated is exemplary modeling data134for producing a customized protective device for the ankle, according to one embodiment of the present disclosure. In some embodiments, once the surface has been created, the surface can be input into the data processing console142. The data processing console142may select points closest to the spheroids and apply a force pulling them onto the surface. The data processing console142may select and pull a random selection of points toward the subject mesh. In various embodiments, the data processing console142applies a smoothing force and the system is allowed to converge to a surface that fits the defined tolerance of 0.5 mm, is smooth, and fits well to the spheroids.

Referring now toFIG.30A-H, illustrated is exemplary modeling data134for producing a customized protective device for the ankle, according to one embodiment of the present disclosure. In some embodiments, the data processing console142creates the parametrically defined cutting curves. In one or more embodiments, the data processing console142removes some material of the shin portion of the brace around the Achilles tendon in order to increase the comfort and functionality. In at least one embodiment, the material is removed 10-60% of the length from the base of the malleolus spheroid to the top of the brace. In particular embodiments, the data processing console142removes the middle 5-30% of the front of the shin so that it can easily be put on and taken off by the subject. In various embodiments, the data processing console142creates the foot portion of the brace by finding the inflection points of the back of the heel and top of the foot. In some embodiments, the data processing console142breaks the spheroid curve at the closest points to inflection points and a smooth curve is constructed between the segments. A plane may be rendered perpendicular to the foot past the 5th metatarsal base. In particular embodiments, the data processing console142creates a curve at this intersection and two points are selected around 20% of the curve length from the center of the sole. In at least one embodiment, the data processing console142smoothly interpolates the points and connects the points to the malleolus curve. In various embodiments, the resulting curves are used to split each of the two surfaces.

Referring now toFIG.31A-D, illustrated a customized protective device3100for the ankle, according to one embodiment of the present disclosure. After the data processing console142creates a digital rendering, the data processing console142exports the rendering to the subject or medical professional for review. Changes may be requested based on the use case of the customized protective device3100, and the parameters of the customized protective device3100may be altered to best fit the specifications of the user. Once the final customized protective device3100design is confirmed, the computing environment102exports the customized protective device3100model to a suitable 3D printing format. Suitable 3D printing file formats include but are not limited to standard triangle language (STL), OBJ file type, or 3D manufacturing format (3MF). In some embodiments, the computing environment102performs slicing on the customized protective device3100model to formulate 3D printing instructions. In one or more embodiments, the computing environment102uploads the customized protective device3100model to a 3D printer that uses SLA technology. The 3D printer discussed herein may print the customized protective device3100. During, before, or after the printing process, the data processing console142or the additive manufacturing device106may be employed to orient the customized protective device3100, such that the surface area per slice is minimized and no support structures are generated on the inner surface.

Referring now toFIG.32A-E, illustrated are customized protective devices3200A,3200B,3200C,3200D, and each of their corresponding lattice structures, according to one embodiment of the present disclosure. In particular embodiments, the customized protective devices3200A-D employ lattice structures to absorb energy during use. In one or more embodiments, the lattice structures fit custom to the individual's anatomy to a specific degree of tolerance. The unit cells of the lattice structures may include but are not limited to the TPMS, Kelvin, and Octet unit cells. The customized protective device3200A may use TPMS unit cells; the customized protective device3200B may use Kelvin unit cells; the customized protective device3200C may use an octet unit cell; and the customized protective device3200D may use the TPMS unit cell for a clavicle device. In various embodiments, the lattice structures have variable thicknesses, strut sizes, or unit cell sizes to minimize translated energy to the patient. In some embodiments, the lattice structure translates energy by buckling or deforming in a variety of methods. In some embodiments, the 3D printing of the additive manufacturing device106prints the lattice structures using an elastomeric material with a comfortable hardness value between 20 and 80 Shore A. In some embodiments, the additive manufacturing device106can print the customized protective devices3200in a stiffer material. In at least one embodiment, the additive manufacturing device106prints the customized protective devices3200using the same material, where a bottom portion is printed in a lattice structure and the top portion is a solid body. In various embodiments, the customized protective devices3200include solid bottom sections that contours to the subject's body, a lattice layer for energy absorption, and a solid layer that may act as a shell.

In particular embodiments, lattice structures may be used to decrease the weight of specific products or to allow a degree of flexion in specific customized protective devices3200. In one or more embodiments, the lattice structure is used in splinting devices that benefit from a greater range of flexibility or motion.

Referring now toFIGS.33A-U, illustrated are various types of customized protective devices151, according to various embodiment of the present disclosure. In particular embodiments, the customized protective device151can be designed for any particular body part. In one or more embodiments, the customized protective device151ofFIG.33Acovers the acromioclavicular (AC) joint. In some embodiments, the customized protective device151ofFIG.33Acontours to the top of the shoulder, distributes impacts away from the AC joint and pain points, and allows full range of motion. In one or more embodiments, the customized protective device151ofFIG.33Ais used to protect Grades I-III and V AC joint separations.

In one or more embodiments, the customized protective device151ofFIG.33Bcovers a collarbone. In various embodiments, the customized protective device151ofFIG.33Bforms a bridge over the clavicle, distributes load away from the clavicle, and allows full range of motion. In some embodiments, the customized protective device151ofFIG.33Bminimizes contact points with the neck and shoulder during arm abduction, flexion, and extension.

In one or more embodiments, the customized protective device151ofFIG.33Ccovers a sternoclavicular joint. In one or more embodiments, the customized protective device151ofFIG.33Cforms a bridge over the clavicle, distributes all load away from the clavicle, and allows full range of motion. In some embodiments, the customized protective device151ofFIG.33Cminimizes contact points with the neck and shoulder during arm abduction, flexion, and extension.

In one or more embodiments, the customized protective device151ofFIG.33Dcovers a sternum. In some embodiments, the customized protective device151ofFIG.33Dcontours to the torso, distributes load away from the sternum, and rests on the pectoral muscles.

In various embodiments, the customized protective device151ofFIG.33Ecovers a thigh. In some embodiments, the customized protective device151ofFIG.33Econtours to the thigh, distributes load away from the injured area, and allows full range of motion. In particular embodiments, the customized protective device151ofFIG.33Eis low profile and hardly noticeable by the user.

In at least one embodiment, the customized protective device151ofFIG.33Fcovers a hip pointer. In various embodiments, the customized protective device151ofFIG.33Fcontours to the hip, distributes load away from the iliac crest, and allows full range of motion.

In particular embodiments, the customized protective device151ofFIG.33Gpartially covers the thumb. In one or more embodiments, the customized protective device151ofFIG.33Gsupports the thumb metacarpophalangeal (MCP) joint against hyperextension and hyperabduction. In various embodiments, the customized protective device151ofFIG.33Gextends from the third metacarpal on the back of the hand around the thumb MCP joint and wraps partially onto the palm.

In some embodiments, the customized protective device151ofFIG.33Hcovers a thumb. In one or more embodiments, the customized protective device151ofFIG.33Hwith closed ring around the thumb restricts hyperextension and hyperabduction of the thumb MCP joint as well as impact to the inside of the palm.

In some embodiments, the customized protective device151ofFIG.33Ipartially covers the thumb. In various embodiments, the customized protective device151ofFIG.33Ihelps the thumb with various degrees of thumb ulnar collateral ligament (UCL) injuries. In particular embodiments, the customized protective device151ofFIG.33Irestricts thumb hyperabduction while allowing full range of motion.

In at least one embodiment, the customized protective device151ofFIG.33Jpartially covers half of a hand. In some embodiments, the customized protective device151ofFIG.33Jis designed to immobilize the wrist, ring finger, and pinky following a fracture of the 4th metacarpal. In various embodiments, the customized protective device151ofFIG.33Jextends from proximal forearm past the tips of the ring finger and pinky and fully restricts motion of the wrist and both fingers.

In at least one embodiment, the customized protective device151ofFIG.33Kpartially covers a wrist. In one or more embodiments, the customized protective device151ofFIG.33Kis designed for an athlete to return to physical activity following a scaphoid fracture. The customized protective device151ofFIG.33Kmay fully immobilize the wrist, may extend from the forearm to the knuckles, and may fully encapsulate the thumb.

In at least one embodiment, the customized protective device151ofFIG.33Lpartially covers a finger. In various embodiments, the customized protective device151ofFIG.33MandFIG.33Ncovers the wrist. In one or more embodiments, the customized protective device151ofFIG.33Ocovers the ankle.

In one or more embodiments, the customized protective device151ofFIG.33Pcovers a portion of a shoe. In some embodiments, the customized protective device151ofFIG.33Qcovers the forearm. In various embodiments, the customized protective device151ofFIG.33Rcovers the bicep. The customized protective device151ofFIG.33Smay cover a shin. The customized protective device151ofFIG.33Tmay cover the top of a foot.

In some embodiments, the customized protective device151ofFIG.33Ucovers at least one rib. In various embodiments, the customized protective device151ofFIG.33Ucontours to the torso and distributes load away from the rib bone with minimal interference to normal shoulder pads and the overall comfort of the user.

From the foregoing, it will be understood that various aspects of the processes described herein are software processes that execute on computer systems that form parts of the system. Accordingly, it will be understood that various embodiments of the system described herein are generally implemented as specially configured computers including various computer hardware components and, in many cases, significant additional features as compared to conventional or known computers, processes, or the like, as discussed in greater detail herein. Embodiments within the scope of the present disclosure also include computer-readable media for carrying or having computer-executable instructions or data structures stored thereon. Such computer-readable media can be any available media, which can be accessed by a computer, or downloadable through communication networks. By way of example, and not limitation, such computer-readable media can comprise various forms of data storage devices or media such as RAM, ROM, flash memory, EEPROM, CD-ROM, DVD, or other optical disk storage, magnetic disk storage, solid-state drives (SSDs) or other data storage devices, any type of removable non-volatile memories such as secure digital (SD), flash memory, memory stick, etc., or any other medium which can be used to carry or store computer program code in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose computer, special purpose computer, specially-configured computer, mobile device, etc.

When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or a combination of hardwired or wireless) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such a connection is properly termed and considered a computer-readable medium. Combinations of the above should also be included within the scope of computer-readable media. Computer-executable instructions comprise, for example, instructions and data, which cause a general-purpose computer, special purpose computer, or special purpose processing device such as a mobile device processor to perform one specific function or a group of functions.

Those skilled in the art will understand the features and aspects of a suitable computing environment in which aspects of the disclosure may be implemented. Although not required, some of the embodiments of the claimed systems and methods may be described in the context of computer-executable instructions, such as program modules or engines, as described earlier, being executed by computers in networked environments. Such program modules are often reflected and illustrated by flow charts, sequence diagrams, exemplary screen displays, and other techniques used by those skilled in the art to communicate how to make and use such computer program modules. Generally, program modules include routines, programs, functions, objects, components, data structures, application programming interface (API) calls to other computers whether local or remote, etc. that perform particular tasks or implement particular defined data types, within the computer. Computer-executable instructions, associated data structures and/or schemas, and program modules represent examples of the program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps.

Those skilled in the art will also appreciate that the claimed and/or described systems and methods may be practiced in network computing environments with many types of computer system configurations, including personal computers, smartphones, tablets, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, networked PCs, minicomputers, mainframe computers, and the like. Embodiments of the claimed system and method are practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination of hardwired or wireless links) through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

An exemplary system for implementing various aspects of the described operations, which is not illustrated, includes a computing device including a processing unit, a system memory, and a system bus that couples various system components including the system memory to the processing unit. The computer will typically include one or more data storage devices for reading data from and writing data to. The data storage devices provide nonvolatile storage of computer-executable instructions, data structures, program modules, and other data for the computer.

Computer program code that implements the functionality described herein typically comprises one or more program modules that may be stored on a data storage device. This program code, as is known to those skilled in the art, usually includes an operating system, one or more application programs, other program modules, and program data. A user may enter commands and information into the computer through keyboard, touch screen, pointing device, a script containing computer program code written in a scripting language, or other input devices (not shown), such as a microphone, etc. These and other input devices are often connected to the processing unit through known electrical, optical, or wireless connections.

The computer that affects many aspects of the described processes will typically operate in a networked environment using logical connections to one or more remote computers or data sources, which are described further below. Remote computers may be another personal computer, a server, a router, a network PC, a peer device or other common network node, and typically include many or all of the elements described above relative to the main computer system in which the systems and methods are embodied. The logical connections between computers include a local area network (LAN), a wide area network (WAN), virtual networks (WAN or LAN), and wireless LANs (WLAN) that are presented here by way of example and not limitation. Such networking environments are commonplace in office-wide or enterprise-wide computer networks, intranets, and the Internet.

When used in a LAN or WLAN networking environment, a computer system implementing aspects of the system and method is connected to the local network through a network interface or adapter. When used in a WAN or WLAN networking environment, the computer may include a modem, a wireless link, or other mechanisms for establishing communications over the wide-area network, such as the Internet. In a networked environment, program modules depicted relative to the computer, or portions thereof, may be stored in a remote data storage device. It will be appreciated that the network connections described or shown are exemplary and other mechanisms of establishing communications over wide area networks or the Internet may be used.

While various aspects have been described in the context of a preferred embodiment, additional aspects, features, and methodologies of the claimed systems and methods will be readily discernible from the description herein, by those of ordinary skill in the art. Many embodiments and adaptations of the disclosure and claimed systems and methods other than those herein described, as well as many variations, modifications, and equivalent arrangements and methodologies, will be apparent from or reasonably suggested by the disclosure and the foregoing description thereof, without departing from the substance or scope of the claims. Furthermore, any sequence(s) and/or temporal order of steps of various processes described and claimed herein are those considered to be the best mode contemplated for carrying out the claimed systems and methods. It should also be understood that, although steps of various processes may be shown and described as being in a preferred sequence or temporal order, the steps of any such processes are not limited to being carried out in any particular sequence or order, absent a specific indication of such to achieve a particular intended result. In most cases, the steps of such processes may be carried out in a variety of different sequences and orders, while still falling within the scope of the claimed systems and methods. In addition, some steps may be carried out simultaneously, contemporaneously, or in synchronization with other steps.

The embodiments were chosen and described in order to explain the principles of the claimed systems and methods and their practical application so as to enable others skilled in the art to utilize the systems and methods and various embodiments and with various modifications as are suited to the particular use contemplated. Alternative embodiments will become apparent to those skilled in the art to which the claimed systems and methods pertain without departing from their spirit and scope. Accordingly, the scope of the claimed systems and methods is defined by the appended claims rather than the foregoing description and the exemplary embodiments described therein.