Patent Publication Number: US-2021183504-A1

Title: Patient bed exit prediction

Description:
BACKGROUND 
     Patients in care facilities, such as hospitals, clinics, nursing homes and the like, are often in compromised medical conditions. Injuries sustained by patients due to falls in care facilities result in significant healthcare costs. In an effort to prevent such injuries, various protocols are implemented to mitigate the risks. For example, patients who are likely to fall when moving unassisted may be identified as being a higher risk, and certain protocols may be implemented to reduce the opportunity for the patients to move about unassisted. However, some patients will attempt to get out of bed without assistance, despite receiving instructions to wait for a caregiver. This results in increased fall risk for those patients. 
     SUMMARY 
     Embodiments of the disclosure are directed to predicting exits from patient support systems in order to mitigate injuries associated with patient falls. Sensors embedded in covers of the patient support system and/or attached to the patient detect movement indicative of the patient removing the covers in preparation to exit the patient support system. Alerts to caregivers can help mitigate falls from patients exiting the patient support system unassisted. 
     In one aspect, a method of predicting exit of a patient support system comprises: establishing a connection between a patient monitoring computing device and at least one radio frequency identification (RFID) reader positioned proximate the patient support system; establishing a connection between the at least one RFID reader and at least one RFID sensor associated with one or more of a blanket, a sock, a bracelet, and an anklet placed on a patient in the patient support system; monitoring, with the patient monitoring computing device, movement on the patient support system using data from the RFID reader, the data indicating a distance between the at least one RFID sensor and the at least one RFID reader; and determining when the data indicates that the patient is exiting the patient support structure. 
     In another aspect, a system for monitoring patient movements on a bed comprises: a bed configured to support a patient while under medical care; at least one RFID reader positioned proximate the bed; two or more RFID sensors embedded in covers configured to cover a patient on the bed; and a patient monitoring computing device comprising a processor and a memory comprising instructions. When the instructions are executed, the processor operates a patient monitoring system configured to perform a series of operations comprising: establishing a connection between the patient monitoring computing device and the at least one RFID reader; establishing a connection between the at least one RFID reader and the two or more RFID sensors; associating the RFID sensors with a patient at the patient monitoring computing device; monitoring patient movements on the bed based on signals from the RFID reader measuring a distance between the two or more RFID sensors and the at least one RFID reader; detecting patient movements indicating that the patient is exiting the bed; and issuing an alert to a caregiver call system. 
     In yet another aspect, one or more computer-readable media having computer-executable instructions embodied thereon that, when executed by one or more computing devices, cause the computing devices to: establish a connection between a patient monitoring computing device and at least one radio frequency identification (RFID) reader positioned proximate a patient bed; establish a connection between the at least one RFID reader and at least two RFID transponders embedded in one or more of a blanket and a sock placed on a patient in the patient bed; associate the at least one RFID transponder with the patient at a patient monitoring computing device; monitor, with the patient monitoring computing device, patient movements on the bed based on signals from the RFID reader measuring a distance between the RFID transponders and the at least one RFID reader; detect patient movements indicating that the patient is going to exit the bed, the patient movements being determined based on the speed at which the distance between the two or more RFID sensors and the at least one RFID reader changes; and issue an alert to a caregiver call system. 
     The details of one or more techniques are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of these techniques will be apparent from the description, drawings, and claims. 
    
    
     
       DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic diagram illustrating an example system for predicting patient bed exit. 
         FIG. 2  is a detailed schematic diagram illustrating the patient monitoring system of  FIG. 1 . 
         FIG. 3  is a flow chart illustrating an example method of monitoring a patient to mitigate a risk of falling. 
         FIG. 4  is a flow chart illustrating an example method of setting up a patient monitoring system with patient movement detecting devices. 
         FIG. 5  is a flow chart illustrating an example method of monitoring a patient to mitigate a risk of falling. 
         FIG. 6  is a block diagram illustrating example components of a computing device usable in the system of  FIG. 1 . 
         FIG. 7  is a schematic diagram illustrating an example implementation of the system of  FIG. 1 . 
         FIG. 8  is a schematic diagram illustrating alternative example implementations of the system of  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION 
     The present disclosure is directed to systems and methods for predicting when a patient will exit a patient support system, such as a bed, chair, lift, surgical table, etc. (reference will be made to a “bed” herein for ease of description). Many patients in a hospital are prone to falling due to age, medications, surgery, and medical equipment. In order to mitigate fall risk, a caregiver may assist at-risk patients to exit the bed and walk. However, patients often do not wait for a caregiver and instead leave the bed without assistance. 
       FIG. 1  is a schematic diagram illustrating an example system  100  for predicting patient bed exit. The system can be implemented, for example, at a hospital, clinic, or other healthcare facility. Patients that are at risk of falling should have caregiver assistance when getting out of bed. The system  100  operates to detect movements of a patient indicating that the patient is about to exit the bed to stand up. The system  100  can alert caregivers when a patient with high fall risk is about to exit his or her bed unattended. 
     One of the earliest and most prevalent signs of an upcoming bed exit is removal of covers. This often occurs even before a patient sits up or begins to shift his or her weight in preparation to get out of bed. A patient typically uses his or her feet to kick off the covers. In some instances, the patient uses his or her hands instead of or in addition to kicking to remove the covers. The term “covers” as used herein includes refers to a piece of cloth or fabric used as a body covering. The term “covers” can refer to one or more of a blanket, a sheet, a duvet, a comforter, or a quilt. 
     The embodiments described herein use sensors to detect movement of a patient&#39;s feet, covers on the patient bed, or both. The sensors could be one or more of Radio-Frequency Identification (RFID) sensors (tags), infrared motion detection, video motion detection, accelerometers, and load sensors in the bed. An algorithm generated from training data obtained in controlled experiments is used to analyze the sensor information to determine when patient movements indicate that covers are being removed by a patient in a bed. 
     In the example of  FIG. 1 , the system  100  for predicting patient bed exit includes a patient bed  102  in communication with a patient monitoring computing device  104 . A patient monitoring system  106  operates on the patient monitoring computing device  104 . The patient monitoring computing device  106  communicates via a network  108  with other computing systems including an electronic medical record (EMR) system  112 , a hospital information system  114 , and a caregiver call system  116 . 
     The patient bed  102  operates to provide a surface for a patient P to rest upon while under medical care. In some embodiments, the patient bed  102  is equipped with one or more RFID readers  120 . The RFID readers  120  can be configured to communicate with a network enabled smart bed  102 , a patient monitoring computing device  104 , or through the network  108  to other computing systems such as an EMR system  112 . 
     The patient bed  102  is equipped with a blanket  122  to cover the patient P. The blanket  122  includes one or more RFID sensors  124 . In the example of  FIG. 1 , four RFID sensors  124  are embedded in the blanket  122  proximate to each of the four corners of the blanket. The RFID sensors  124  send signals that are detected by the RFID antennas  120 . Movement of the RFID sensors  124  relative to the RFID readers  120  is analyzed to determine if the patient P is moving in a way that indicates that the patient P is getting out of the bed  102 . This process is described in greater detail with respect to  FIG. 5 . 
     In some embodiments, the patient bed  102  is a smart bed equipped with a memory device and a processing device. The smart bed can include various functionalities to monitor a patient, entertain a patient, and make a patient more comfortable. In some embodiments, the patient bed  102  is in communication with one or more patient monitoring devices via wireless or wired connections. In some embodiments, the patient bed  102  includes load sensors and/or motion sensors to monitor patient movements on the bed. One example of a smart hospital bed is the Advanta™ 2 Med Surg Bed manufactured by Hill-Rom of Batesville, Ind. 
     The RFID sensors  124  function in conjunction with an RFID reader  120  to communicate via radio frequency signals. The RFID sensors may also be referred to as chips, tags, or transponders. RFID sensors generally include an integrated circuit, a means of collecting power, and an antenna. The antenna receives and transmits radio-frequency signals. The integrated circuit the stores and process information. The integrated circuit also functions to modulate and demodulate radio-frequency signals. The RFID sensors also includes a means for collecting power from the RFID reader. The RFID readers may also be referred to as RFID interrogators or antennas. 
     The RFID readers  120  transmit encoded radio signals to interrogate the RFID sensors  124 . In response, the RFID sensors send their identification and other information such as a unique tag serial number. In some embodiments, the RFID readers are active readers and the RFID sensors are passive tags. Generally, the RFID readers are in a fixed location with an interrogation zone on the patient bed. This reduces the likelihood of accidentally communicating with RFID sensors of other patients. 
     In some embodiments, more than one RFID reader  120  is used to validate direction of movement of one or more RFID sensors  124 . In some embodiments, multiple RFID sensors may be needed to accurately detect movement, particularly if there is only one RFID reader. In some embodiments, 13.56 MHz RFID sensors are used. In some embodiments, there are at least two RFID sensors placed apart from one another on a patient. In some embodiments, there are four RFID sensors positioned proximate to each of four corners of a blanket. In some embodiments, at least one RFID sensor is embedded in a sock worn by the patient. In some embodiments, the RFID sensors are flimsy, inexpensive and are integrated into disposable sheets. In other embodiments, the RFID sensors are more sturdy and expensive in order to withstand washing in reusable blankets and sheets. 
     The patient monitoring computing device  104  operates to receive and record data for a particular patient from one or more patient monitoring devices. The patient monitoring devices are in communication with the patient monitoring computing device  104  through a wired or wireless connection. Examples of patient monitoring devices include heart rate monitors, pulse oximeters, etc. In some embodiments, the patient monitoring devices can include RFID sensors  124  and RFID readers  120  as well as the patient support system (bed) itself  102 . 
     In some embodiments, the patient monitoring computing device  104  includes a processor and memory device. The memory device can include instructions for the processor to analyze data received from patient monitoring devices. In some embodiments, the memory device can also store patient data locally. The patient monitoring computing device  104  can include a display with a user interface that allows a caregiver to easily access patient data. In some embodiments, patient monitoring computing device  104  communicates patient data to one or more of the patient monitoring system  106 , EMR system  112 , hospital information system  114 , and caregiver call system  116  through the network  108 . The patient monitoring computing device  104  can also include one or more input devices such as a keyboard, mouse, or touchscreen that receives input from a caregiver or other user. 
     The patient monitoring system  106  operates on the patient monitoring computing device  104 . In some embodiments, the patient monitoring system  106  is hosted on a remote server that is accessed by the patient monitoring computing device  104  through the network  108 . The patient monitoring system  106  is described in greater detail in  FIG. 2 . 
     The network  108  operates to mediate communication of data between network-enabled computing systems. In various embodiments, the network  108  includes various types of communication links. For example, the network  108  can include wired and/or wireless links, including cellular, Bluetooth, ultra-wideband (UWB), 802.11, ZigBee, and other types of wireless links. The network  108  can include one or more routers, switches, mobile access points, bridges, hubs, intrusion detection devices, storage devices, standalone server devices, blade server devices, sensors, desktop computers, firewall devices, laptop computers, handheld computers, mobile telephones, vehicular computing devices, and other types of computing devices. 
     The electronic medical record (EMR) system  112  operates to record information relevant to the medical history of each patient. Examples of information that might be stored in a patient&#39;s EMR includes lab results, surgical history, family medical history, current medications, and previous medical diagnoses. A patient&#39;s fall risk score (as determined by e.g. Morse Fall Scale, Johns Hopkins Fall Risk Assessment Tool, etc.) or sub-score (as determined by Get Up and Go test) are other pieces of information that could be added to an EMR. Examples of electronic medical records systems  112  include those developed and managed by Epic Systems Corporation, Cerner Corporation, Allscripts, and Medical Information Technology, Inc. (Meditech). 
     The hospital information systems  114  operate to record, store, and communicate information about patients, caregivers, and hospital facilities. Hospital information systems  114  general handle administrative information for a hospital or clinic. Examples of hospital information systems  114  include admit/discharge/transfer (ADT) systems, laboratory information systems (LIS), and clinical decision support (CDS) systems. 
     The caregiver call systems  116  operate to generate alerts that are triggered by one or more rules. The alerts are disseminated to caregivers that need to perform critical tasks. The alerts can be generated based on data from the vital signs monitoring devices or updates to patient information that are received at the EMR system  116 . As an illustrative example, patient fall risk scores, when above a predetermined threshold, trigger an alert from caregiver call system  118  that is sent to a computing device  128  associated with a caregiver C so that the caregiver is notified of the need to perform critical tasks based on the patient&#39;s fall risk. In the example of  FIG. 1 , the caregiver C is a nurse operating a tablet computing device  128 . Other examples include smartphones, desktop computers, laptops, pagers, and other network enabled devices. In some embodiments, the alert is delivered in any suitable form, including audible, visual, and textual such as a message on a display or a pager message. 
       FIG. 2  is a more detailed schematic diagram of the patient monitoring system  106  of  FIG. 1 . In some embodiments, the patient monitoring system  106  operates on the patient monitoring computing device  104 . In other embodiments, the patient monitoring system  106  operates on a remote server that is in communication with one or more patient monitoring devices. In the example of  FIG. 2 , the patient monitoring system  106  includes a motion analyzer  152 , a vitals monitor  154 , a patient pairing module  156 , and an alert system  158 . 
     The motion analyzer  152  operates to receive data from one or more devices that record patient movements. For example, in some embodiments, the motion analyzer  152  receives data from an RFID reader  120  about how far away one or more RFID sensors are from the RFID reader and whether the RFID sensors are moving. The motion analyzer  152  analyzes the data to discern particular patterns of movement indicative of a patient preparing to exit a bed. One such pattern of movement is associated with a patient removing the covers of a bed. RFID sensors embedded in a blanket change their distance from an RFID reader at an acceleration that is consistent with a patient removing the blanket in preparation to get out of bed. In some embodiments, the motion analyzer  152  receives signals based on RFID sensors placed in a patient&#39;s sock. 
     The motion analyzer  152  can receive data from other devices associated with a patient bed. For example, load sensors in a bed  102  can record changes in the weight present on the bed. Multiple load sensors can indicate shifts in weight as well. The load sensors can detect patient movements that are analyzed by the motion analyzer  152  to determine that a patient is about to get out of bed  102 . In some embodiments, the load sensors are used in conjunction with RFID sensors to confirm that a patient is preparing to exit a bed. Other devices that can capture patterns of patient movement include infrared motion detectors  172 , video motion sensors, and accelerometers  170  placed on the patient. 
     The vitals monitor  154  operates to receive and analyze data from one or more vitals monitoring devices associated with a patient. In some embodiments, the vitals monitoring devices monitor one or more of a patient&#39;s body temperature, blood pressure, heart rate, blood oxygen level, and respiration rate. As shown in  FIG. 2 , the vitals monitor  154  can receive data from one or more of a blood pressure monitor  174 , a heart rate monitor  176 , a pulse oximeter  178 , and a thermometer  180 . Other vitals monitors are possible. In some embodiments, the vitals monitor  154  operates to analyze data received from vitals monitoring devices to determine when an alert needs to be issued for the patient. The alert can be communicated to a caregiver through, for example, the caregiver call system  116 . 
     The patient pairing module  156  operates to set up a patient support system  102  with accompanying monitoring devices and computing devices for a particular patient. The patient&#39;s ID and EMR is associated with the patient monitoring computing device  104  to ensure that the correct patient information is displayed and that the data being recorded by monitoring devices is recorded to the correct patient EMR in the EMR system  112 . Any motion detecting devices are paired to the patient monitoring computing device  104  via wired or wireless connections. In some embodiments, the patient pairing module  156  ensures that RFID sensors  124  in a patient&#39;s covers  122  or socks are properly paired with the RFID readers  120  at the patient&#39;s bed  102  as well as the patient monitoring computing device  104 . Any RFID sensors  124  are thus associated with the correct patient. 
     The alert system  158  operates to communicate alarms or alerts to computing systems in communication with the patient monitoring computing device  104  or patient bed  102 . For example, the alert system  158  can communicate alerts to caregiver call systems  116  to notify caregivers of the imminent risk of a patient fall. The alerts can be disseminated to a status board or caregiver mobile devices. The alert system  158  can also activate an alert response at the patient bed  102 . 
     If the patient bed  102  is equipped with safety devices to mitigate falls, those devices can be automatically activated to provide one or more fall risk mitigation actions. For instance, some patient beds are equipped with side rails that can automatically be locked and/or moved up or down (e.g., motorized). In such an alert situation, the side rails can be locked (if already in the up position) and/or moved to an up position to further minimize the likelihood of the patient exiting the patient bed  102 . 
     The alert system  158  can also communicate a visual or audible alert at the patient monitoring computing device  104  or bed  102 . In some embodiments, the alert at the patient bed instructs the patient to stay in bed or to wait for a caregiver to arrive. This alert could be a voice command delivered over a speaker at the patient bed  102  or placed elsewhere near the patient bed. In other examples, alerts are provided to the caregiver as well, such as at a central station and/or mobile device of the caregiver. 
     In the example of  FIG. 1 , when the patient P is removing the covers  122 , the RFID sensors (or tags) move closer to or further away from an RFID reader  120 . The RFID reader  120  communicates the distance and speed at which the distance is changing to the patient monitoring computing device  104 , where the motion analyzer  152  processes the data to determine whether the patient&#39;s patterns of movement indicate that the patient is about to get out of the bed. When such patterns of movement are recognized, this is communicated to the alert system  158 . The alert system  158  determines which other computing systems need to be notified for that particular patient P. This determination can be informed by data received from the vitals monitor  154  as well as the patient&#39;s EMR. The alert system  158  can communicate alerts to a caregiver call system  116  through the network  108  as well as other hospital information systems  114 . In turn, the caregiver call system  116  disseminates alerts to one or more caregiver computing devices  128  to notify particular caregivers C responsible for the patient P. At the same time, the alert system  158  communicates an order to the patient bed  102  to project a visual warning on the floor next to the bed so that the patient is reminded not to get out of bed unattended. Any caregivers passing by the patient&#39;s bed will notice that the patient should not be getting out of bed unattended and can come to aid the patient. 
       FIG. 3  is a flow chart illustrating an example method  200  of monitoring a patient to mitigate a risk of falling. In some embodiments, one or more aspects of this method are performed by the patient monitoring system  106  of  FIGS. 1 and 2 . 
     At operation  202 , a link is established between the RFID devices (readers and sensors), patient monitoring computing device, and patient identifier. In some embodiments, this is performed by the patient pairing module  156  of  FIG. 2 . This occurs when the patient is set up in a bed  102  to be monitored by a patient monitoring computing device  104 . The linking process ensures that the correct patient data is retrieved from the EMR system and that any data recorded on patient monitoring devices (including the bed itself) are recorded with the correct patient&#39;s EMR. Further, this step ensures that any RFID sensors on the patient or the patient&#39;s blanket are being read by the correct RFID reader associated with the patient&#39;s bed. It is possible that without proper pairing, a RFID reader at a first patient&#39;s bed could receive signals from RFID sensors on a second patient, if the second patient is within range of the RFID reader. 
     At operation  204 , the patient is monitored using the patient monitoring computing device  104  in communication with vitals sign monitoring devices and motion detecting devices. In some embodiments, the motion detecting devices include at least one RFID reader  120  and at least one RFID sensor  124  embedded in covers placed over the patient. In some embodiments, patient movement data is analyzed by the motion analyzer  152  of  FIG. 2 . In some embodiments, vital signs are monitored by the vitals monitor  154 . 
     At operation  206 , patient movements indicative of an impending bed exit are detected. In some embodiments, this operation is performed by the motion analyzer  152 . When such movements are detected, the motion analyzer  152  communicates that information to the alert system  158 . In some embodiments, the patient movements are determined based on readings of distance between RFID sensors embedded in a patient&#39;s blanket or sock and an RFID reader mounted on or near the patient&#39;s bed. Changes in that distance can indicate that a patient is removing the covers in preparation to get out of bed. Alternatively, or in addition to the RFID readings, other motion detection methods can be used. For example, infrared motion detection, load sensors in the bed, and computer vision can also detect patient movements. Algorithms in the motion analyzer  152  determine which patterns of movement are most likely to precede a patient getting out of bed. 
     At operation  208 , an alert is issued indicating that the patient is at risk of falling. In some embodiments, this operation is performed by the alert system  158  of  FIG. 2 . Alerts can be communicated to caregivers to notify them of an impending risk of a patient fall. Alerts can also be communicated to a patient monitoring computing device  104  near the patient&#39;s bed that can automatically implement fall risk mitigation actions. 
       FIG. 4  illustrates a flow chart of a more detailed example method  300  of setting up a patient monitoring system with patient movement detecting devices. In some embodiments, this method  300  is performed by the patient pairing module  156  of  FIG. 2 . 
     At operation  302 , a connection is established between a patient monitoring computing device and at least one RFID reader positioned proximate a patient bed. The connection can be a wired or wireless connection. In some embodiments, the RFID reader  120  is paired to the patient monitoring computing device  106  through a short-range wireless communication connection such as Bluetooth. In some embodiments, the RFID reader  120  is connected to the patient bed  102 , which in turn communicates with the patient monitoring computing device  106 . 
     At operation  304 , a connection is established between the RFID reader and at least one RFID sensor placed on a patient in the patient bed. In some embodiments, the RFID sensor  124  is embedded in one or more of a blanket, a sock, a bracelet, and an anklet placed on the patient such that the RFID sensor  124  moves in a predictable manner when the patient removes the covers of the bed to exit the bed. 
     At operation  306 , the patient&#39;s EMR is paired to the patient monitoring computing device and associated RFID devices. In some embodiments, the patient monitoring computing device  106  communicates with an EMR system  112  to access a patient&#39;s EMR when prompted by a caregiver. The RFID reader  120  transmits information about the status of connected RFID sensors  124  to the patient monitoring computing device  106 , which then can record information to the patient&#39;s EMR. 
     At operation  308 , connections between vital signs monitoring devices and the patient monitoring computing device are established. In some embodiments, the vitals monitor  154  of the patient monitoring computing device  106  receives data from one or more of an infrared motion detector  172 , blood pressure monitor  174 , heart rate monitor  176 , pulse oximeter  178 , and thermometer  180 . The vital signs monitoring devices can be connected to the patient monitoring computing device  106  via wired or wireless connections. For example, the vital signs monitoring devices could plug into the patient monitoring computing device  106  or to the patient bed  102 . In other examples, the vital signs monitoring devices could communicate with the patient monitoring computing device  106  via Bluetooth, Wi-Fi, NFC, etc. 
     At operation  310 , connections between additional movement detecting devices and the patient monitoring computing device are established. Other movement detecting devices can include infrared motion sensors and video motion sensors that can communicate via wired or wireless connections. 
       FIG. 5  is a flow chart illustrating a more detailed example method  350  of monitoring a patient to mitigate falls. In some embodiments, this method  350  is performed by the patient monitoring system  106  of  FIGS. 1 and 2 . 
     At operation  352 , the distance between one or more RFID readers  120  and one or more RFID sensors  124  is measured. In some embodiments, this operation is performed by the motion analyzer  152  of  FIG. 2 . Measurements of the distance between each RFID reader  120  and RFID sensor  124  at a patient bed  102  is measured over time. Changes in the distance indicates that the patient or a blanket  122  covering the patient has moved. The changes in distance can be used to infer movement of the patient. 
     At operation  354 , the rate at which the distance between the RFID readers  120  and RFID sensors  124  changes over time is measured. Slow changes in the distance between RFID readers  120  and RFID sensors  124  embedded in the covers  122  may mean that a blanket is simply slipping down or a patient is getting warm. However, quick changes in the distance between RFID sensors and RFID readers on a patient bed could indicate that the patient is removing the covers in preparation for exiting the bed. Also, in situations where there are multiple RFID readers  120  and multiple RFID sensors  124 , the particular combinations of tags and readers and how the distance change can be analyzed to infer particular types of movement that occur when a patient is preparing to exit a bed  102 . 
     At operation  356 , motion data from other movement detectors is optionally recorded. In some embodiments, additional data can be used to aid in assessing whether a patient is about to exit a bed. For example, the motion analyzer  152  could receive load sensor data from the patient bed  102  to determine how the patient&#39;s weight is shifting on the bed. In another example, an accelerometer  170  in a wristband worn by the patient could record movements consistent with a patient removing the covers. An infrared motion detector  172  or video motion detector could record patient movements that can be analyzed to determine if a patient is about to get out of bed. 
     At operation  358 , the measured and recorded information is analyzed to identify patterns of patient movements. In some embodiments, this operation is performed by the motion analyzer  152 . In some embodiments, the motion analyzer  152  employs a machine learning generated model to analyze patient movement data. The machine learning model is generated by training a machine learning algorithm with patient movement data from controlled experiments. Patient bed exits are identified in the experimental data and the corresponding patient movements are identified by the algorithm. The resulting machine learning model is used to classify patterns of patient movements measured from RFID sensors and other motion detectors. 
     At operation  360 , patient movements are identified that indicate imminent bed exit. In some embodiments, the motion analyzer  152  operates to identify the patterns of patient movements indicative of imminent bed exit using the machine learning model. When patient movements indicating imminent bed exit are detected, a message can be communicated to the alert system  158  of  FIG. 2  for processing. 
     In some embodiments, the algorithm for detecting imminent bed exit relies upon measurements of distance between RFID sensors and RFID readers at the patient&#39;s bed. One example of such an algorithm is: 
       change in distance between tag and reader/time=rate of distance change         where rate of distance change&gt;x indicates patient is removing covers       
       FIG. 6  is a block diagram illustrating an example of the physical components of a computing device  400 . The computing device  400  could be implemented in various aspects of the system  100  for predicting bed exit. Components of the computing device  400  can also be incorporated into other devices described herein, such as the patient monitoring computing device  104  or a computing device integrated into the bed  102 . 
     In the example shown in  FIG. 6 , the computing device  400  includes at least one central processing unit (“CPU”)  402 , a system memory  408 , and a system bus  422  that couples the system memory  408  to the CPU  402 . The system memory  408  includes a random access memory (“RAM”)  410  and a read-only memory (“ROM”)  412 . A basic input/output system that contains the basic routines that help to transfer information between elements within the computing device  400 , such as during startup, is stored in the ROM  412 . The computing system  400  further includes a mass storage device  414 . The mass storage device  414  is able to store software instructions and data such as movement data received from the RFID readers  120  or patient bed  102 . 
     The mass storage device  414  is connected to the CPU  402  through a mass storage controller (not shown) connected to the system bus  422 . The mass storage device  414  and its associated computer-readable storage media provide non-volatile, non-transitory data storage for the computing device  400 . Although the description of computer-readable storage media contained herein refers to a mass storage device, such as a hard disk or solid state disk, it should be appreciated by those skilled in the art that computer-readable data storage media can include any available tangible, physical device or article of manufacture from which the CPU  402  can read data and/or instructions. In certain embodiments, the computer-readable storage media comprises entirely non-transitory media. 
     Computer-readable storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable software instructions, data structures, program modules or other data. Example types of computer-readable data storage media include, but are not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROMs, digital versatile discs (“DVDs”), other optical storage media, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computing device  400 . 
     According to various embodiments, the computing device  400  can operate in a networked environment using logical connections to remote network devices through a network  106 , such as a wireless network, the Internet, or another type of network. The computing device  400  may connect to the network  108  through a network interface unit  404  connected to the system bus  422 . It should be appreciated that the network interface unit  404  may also be utilized to connect to other types of networks and remote computing systems. The computing device  400  also includes an input/output controller  406  for receiving and processing input from a number of other devices, including a touch user interface display screen, or another type of input device. Similarly, the input/output controller  406  may provide output to a touch user interface display screen or other type of output device. 
     As mentioned briefly above, the mass storage device  414  and the RAM  410  of the computing device  400  can store software instructions and data. The software instructions include an operating system  418  suitable for controlling the operation of the computing device  400 . The mass storage device  414  and/or the RAM  410  also store software instructions, that when executed by the CPU  402 , cause the computing device  400  to provide the functionality discussed in this document. For example, the mass storage device  414  and/or the RAM  410  can store software instructions that, when executed by the CPU  402 , cause the computing system  400  to analyze movement data received from motion detectors at a patient&#39;s bed. 
       FIGS. 7 and 8  illustrate examples of how patient movements could be recorded with RFID devices.  FIG. 7  illustrates examples of patient movements when a patient P is lying on a bed  102  under covers  511  having two RFID sensors  124  embedded therein. An RFID reader  120  is positioned at the head of the bed and two RFID sensors  124  are embedded in the top of the covers  511 , nearest the head of the bed  102 . 
     In the first view  500 , the patient P is lying under a blanket  122  on the bed  102 . The RFID sensors  124  are approximately equal distances from the RFID reader  120 . The distance  501   a  between the first RFID sensor  124   a  and the RFID reader  120  is greater than the distance  501   b  between the second RFID sensor  124   b  and the RFID reader  120 . 
     In the second view  502 , the patient P has grasped one corner of the blanket  122  and moved it to the opposite side of the bed to remove the blanket. This movement has shifted the second RFID sensor  124   b  further from the RFID reader  120  so that the distance  124   b  is greater. The first RFID sensor  124   a  has remained the same distance  124   a  from the RFID reader  120 . 
     These changes in distance between the RFID sensors  124  and RFID reader  120  occur quickly enough to indicate that the patient is deliberately moving the blanket  122 . The patient monitoring system  106  would analyze these changes in distance and determine that the patient is about to get out of bed. In this example, if load sensors were in the bed reading changes in load, they would indicate a shift in weight as the patient sat up. This would supplement the RFID data to confirm that the patient is preparing to get out of bed. In some instances, the RFID sensors alone might provide ambiguous indications about the patient&#39;s movements, but additional motion detecting devices could confirm the movements as being precursors to bed exit. For instance, a video motion detector could confirm that the patient is moving to exit the bed. 
     The third view  504  shows another way that the patient P might move to remove the blanket  122  in preparation for exiting the bed  102 . Here, the patient is still lying down, but is kicking off the blanket  122 . Both RFID sensors  124   a,    124   b  are quickly moved away from the RFID reader  120 . The patient monitoring system  106  would analyze this rapid increase of distances  501   a,    501   b  and identify it as being consistent with an imminent patient bed exit. The patient monitoring system  106  would issue an alert to nearby caregivers to prompt them to come aid the patient in getting out of bed. 
       FIG. 8  illustrates examples of patient movements on a bed  102  with RFID sensors  124  embedded in articles of clothing that the patient is wearing. In these examples, the RFID sensors  124  are in a wristband  512  or socks  520 . 
     In the top left view  510 , the patient P is lying on the bed  102 . An RFID reader  120  is positioned at the center of the head of the bed. The patient is wearing a bracelet  512  with an RFID sensor embedded inside. Additionally, a single RFID sensor  124  is embedded in the top center of the covers  511 . The distance  513  between the RFID sensor  124  and the RFID reader  120  is slightly less than the distance  514  between the bracelet  512  and the RFID reader  120 . 
     In the top center view  515 , the patient P is reaching with his right hand to grasp the covers  511  at his left side. As the patient P makes this movement, the RFID sensor  124  moves slightly away from the RFID reader  120  and the bracelet  512  moves slightly closer to the RFID reader  120 . The RFID reader  120  also records the speed at which the bracelet  512  moves, which indicates a deliberate movement. However, without more, an alert is not triggered for the patient. 
     In the top right view  516 , the patient P has moved his right arm back to the right side of the bed  102 , pulling the covers  511  off of himself and he is starting to get off of the bed  102 . The bracelet  512  has moved to the right and thus the distance  514  between it and the RFID reader  120  has increased again. Additionally, the RFID reader  120  records how quickly the bracelet  512  is moving. The RFID sensor  124  embedded in the covers  511  has moved further from the RFID reader  120 , increasing the distance  513 . The combination of the changes in distances as well as the speed at which those changes occurred would prompt the motion analyzer  152  to determine that the patient P is about to exit the bed  102 . 
     In the lower left view  518 , the patient P is lying in the bed  102 , wearing socks  520  having RFID sensors embedded therein. While the patient is lying on the bed, the distance  514  between the RFID sensors in the socks  520  and the RFID reader  120  is about the same and does not change very much or very quickly. The distance  513  between the RFID sensor  124  in the covers  511  and the RFID reader  120  is much less than the distance  514  between the socks  520  and the RFID reader  120 . 
     In the lower center view  522 , the patient P is kicking off the covers  511 . While this is occurring, the distance  514  between the socks  520  and the RFID reader  120  is fluctuating quickly. Additionally, the distance  513  between the RFID sensor  124  and the RFID reader  120  is growing larger. In some instances, this is enough for the motion analyzer  152  to determine that the patient P is attempting to exit the bed  102 . 
     In the lower right view  524 , the patient P has kicked the covers  511  completely off and is starting to exit the bed. The distance  513  between the RFID sensor  124  and the RFID reader  120  is even greater. The distance  514  between the socks  520  and the RFID reader  120  is still fluctuating. These measurements provide further information to the motion analyzer  152  to support a finding that the patient P is attempting to exit the bed  102 . 
     Although various embodiments are described herein, those of ordinary skill in the art will understand that many modifications may be made thereto within the scope of the present disclosure. Accordingly, it is not intended that the scope of the disclosure in any way be limited by the examples provided.