Patent Application
20180178061
Rehabilitation healthcare providers, such as physical therapists and athletic trainers, prescribe certain rehab exercises to patients and work with the patients during visits to educate them on how to properly perform the exercises. The patients are then expected to complete those exercises between visits as part of their rehabilitation program. One particular challenge faced by rehabilitation healthcare providers is the lack of some patients' compliance with the exercises. It's difficult for the rehabilitation healthcare providers to ascertain: (1) whether the exercises are actually performed; and (2) if the exercises are performed, whether the exercises are performed correctly. While rehabilitation healthcare providers can pose specific questions and track a patient's progress during visits, this is insufficient to adequately assess the patient's compliance.
Embodiments of the present invention relate to, among other things, a tracking and compliance system that includes devices to track fitness activity and determine compliance with a rehab program. The tracking and compliance system includes at least one biometric sensor for tracking biometric data from a patient and at least one motion sensor for tracking motion data while a fitness activity is being performed by the patient. The biometric data and motion data are correlated over time to generate activity data for the fitness activity. The activity data can then be compared against a biometric signature for the patient for that type of fitness activity to determine compliance. The biometric signature comprises correlated biometric data and motion data from the fitness activity being previously performed by the patient, for instance, in the presence of a rehabilitation healthcare. A biometric signature can be provided for each of a number of different fitness activities for a given patient.
Accordingly, in one aspect, an embodiment of the present invention is directed to one or more computer storage media storing computer-useable instructions that, when executed by a computing device, cause the computing device to perform operations. The operations include identifying a type of fitness activity to be performed by a user. The operations also include receiving biometric data from one or more biometric sensors while a user performs the fitness activity. The operations further include receiving motion data from one or more motion sensors while the user performs the fitness activity. The operations also include generating activity data for the fitness activity by correlating the biometric data with the motion data over time. The operations still further include generating compliance data by comparing the activity data for the fitness activity with a biometric signature for the user for the type of fitness activity.
In another embodiment, an aspect is directed to a computer-implemented method. The method includes identifying a type of fitness activity to be performed by a user. The method also includes receiving biometric data with time data, the biometric data from one or more biometric sensors while a user performs the fitness activity. The method also includes receiving motion data with time data, the motion data from one or more motion sensors while the user performs the fitness activity. The method further includes generating activity data for the fitness activity by correlating the biometric data with the motion data using the time data associated with biometric data and the time data associated with the motion data. The method still further includes generating compliance data by comparing the activity data for the fitness activity with a biometric signature for the user for the type of fitness activity.
A further embodiment is directed to a computer system that includes a biometric sensor, a motion sensor, an activity tracking module, and a compliance module. The biometric sensor collects biometric data from a user during a fitness activity. The motion sensor collects motion data during the fitness activity. The activity tracking module generates activity data for the fitness activity using the biometric data from the biometric sensor and the motion data from the motion sensor. The compliance module generates compliance data based on the activity data and a biometric signature for the user for a type of fitness activity corresponding to the fitness activity.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
The present invention is described in detail below with reference to the attached drawing figures, wherein:
The subject matter of the present invention is described with specificity herein to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the terms “step” and/or “block” may be used herein to connote different elements of methods employed, the terms should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly described.
As noted in the Background, it's difficult for rehabilitation healthcare providers to determine patients' compliance with rehab exercise programs. While it's possible for rehabilitation healthcare providers to question patients and track progress, such manual assessment is not particularly precise and becomes a bit of a guessing game for the rehabilitation healthcare providers. A potential approach to try to better track patients' exercises would be through the use of “smart” devices. One type of “smart device” is activity trackers, which are commonly used by individuals to monitor fitness-related activities. These include dedicated activity trackers (e.g., the FITBIT activity tracker) as well as smart watches and smartphones with activity tracking capabilities. However, such activity trackers are very limited in the types of activities that can be tracked. Often, they only track number of steps or distance traveled. Therefore, the devices are not useful for other types of activities often used in rehab exercise programs, such as weightlifting or other strength training. Moreover, there's nothing preventing someone else from performing the exercise on behalf of the patient using the patient's activity tracker or the patient from otherwise tricking the activity tracker in believing an activity has been performed (e.g., shaking a step counter to add more steps).
Some “smart” fitness equipment are currently available that allow individuals to identify themselves to the fitness equipment to allow the fitness equipment to track their exercise. For instance, some fitness equipment use a key to identify an individual and track a particular exercise. As with activity trackers, “smart” fitness equipment is limited in the types of activities that can be tracked. Additionally, nothing prevents someone else from performing the exercise for a patient using that patient's key or the patient taking other actions to deceive the system. Moreover, “smart” fitness equipment is not readily available to many patients, who instead use “dumb” fitness equipment (e.g., free weights) with no ability to track fitness activities.
Embodiments of the present invention address the challenge of ensuring compliance with rehab exercise programs by providing a tracking and compliance system that includes devices to track fitness activity and determine compliance with a rehab program. The tracking and compliance system includes at least one biometric sensor for tracking biometric data from a patient while a fitness activity is being performed. The biometrics could include, for instance, heart rate or breathing rate. The tracking and compliance system also includes at least one motion sensor for tracking motion data while a fitness activity is being performed.
Initially, a biometric signature is generated for the patient for a specific fitness activity. A biometric signature comprises correlated biometric data and motion data for a given fitness activity. Each fitness activity has its own biometric signature for a given patient. The biometric signature for a fitness activity could be generated while a rehabilitation healthcare provider observes and instructs the patient on performing the fitness activity correctly.
When the patient subsequently performs a fitness activity, for instance, while at home or otherwise away from the rehabilitation healthcare provide, the tracking and compliance system captures biometric data using the biometric sensor and motion data using the motion sensor. The biometric data and motion data are correlated to generate activity data. The activity data can then be compared against the biometric signature for the patient for that type of fitness activity to determine compliance.
As will be described in further detail below, the devices used to capture the biometric data and motion data can be portable. In some instances, a device is affixed to the patient to collect biometric and/or motion data. In other instances, a device is embedded in or affixed to fitness equipment to collect motion data. If not embedded, the device can be moved from one fitness equipment to another.
Accordingly, embodiments of the present invention provide a solution that addresses the shortcomings of currently available technology, including activity trackers and “smart” fitness equipment. The tracking and compliance system can be used for numerous different types of activities. Additionally, the use of biometric signatures prevents fraud in situations in which another performs exercises for a patient or the patient tries to fake exercise activity. Further, the patient doesn't need access to “smart” fitness equipment. Instead, inexpensive devices can be used that can be placed on the patient and/or fitness equipment. Additionally, the devices can be portable so they can be moved from one piece of fitness equipment to another.
The tracking and compliance system described herein can be used for a number of different purposes. By way of example, the system can be used to record patient compliance to prescribed rehab exercises, detect attempts to cheat or deceive the rehabilitation healthcare provider, provide real-time feedback to the rehabilitation healthcare provider, prevent insurance fraud, provide evidence of correct billing for rehabilitation services, perform timely feedback on whether rehab exercises are being performed correctly (e.g., “you are swinging your leg too fast”), and improve rehab outcomes.
With initial reference to
The one or more biometric sensor(s) 102 track biometrics from the user. In some configurations, a biometric sensor 102 included in the tracking and compliance system 100 is a heart rate monitor that measures the user's heart rate. Known heart rate monitoring technology can be employed. For instance, the heart rate monitor can be a sensor that detects electrical signals (i.e., electrocardiogram signals) transmitted through heart muscle and detected through the user's skin, such as that used in chest strap-type heart rate monitors. As another example, the heart rate monitor can employ optics to measure heart rate based on a temporary darkening due to increased blood amount resulting from a user's pulse. Accordingly, the heart rate monitor can be a sensor that measures an amount of infrared or other light absorbed by blood in order to detect the user's pulse and measure the user's heart rate. These and other heart rate monitors are known to those skilled in the art and therefore will not be discussed in further detail herein.
The one or more biometric sensor(s) 102 can additionally or alternatively include a breathing rate monitor that measures the user's breathing rate. Known breathing rate monitoring technology could be employed. For instance, the breathing rate monitor can be an acoustic sensor that detects the user's breathing rate. As another example, the breathing rate monitor could be a chest or waist strap that measures the user's breathing rate based on girth expansion. Such breathing rate monitors are known to those skilled in the art and therefore will not be discussed in further detail herein.
The one or more motion sensor(s) 104 track movements during exercises. The motion sensor(s) 104 can measure and record, for instance, angular velocity (change in rotational speed), vertical and horizontal accelerations, and g-forces. Any of a variety of motion tracking devices could be employed within the scope of embodiments of the present invention. By way of example only and not limitation, an accelerometer can be used to measure motion via acceleration. As another example, a gyroscope can be used for the determination of orientation and rotation to provide recognition of movement in 3D space (e.g., rotation). In some configurations, an inertial measurement unit (IMU) can be used. It should be understood that multiple types of motion sensors can be employed in conjunction with one another to track motion during fitness activities. These and other motion tracking devices are known to those skilled in the art and therefore will not be discussed in further detail herein.
The activity tracking module 106 collects data from fitness activities performed by the user based on biometric data from the biometric sensor(s) 102 and motion data from the motion sensor(s) 104. In some configurations, the activity tracking module 106 is initially used to generate biometric signatures for the user, for instance, using the method 400 discussed below with reference to
During normal operation, the activity tracking module 106 collects data for fitness activities performed by the user that can then be compared against the user's biometric signatures for those activities. The activity tracking module 106 can collect activity data 116, for instance, using the method 500 described below with reference to
The compliance module 108 compares activity data 116 against biometric signatures 118 for the user. The comparison is specific to a given fitness activity. In particular, activity data 116 for a given fitness activity is compared against a biometric signature 118 for the user for the same fitness activity. The comparison performed by the compliance module 108 can be performed, for instance, user the method 600 described below with reference to
The UI component 110 includes one or more input/output components that enable the user to interact with the tracking and compliance system 100. For instance, the UI component 110 can be used to input information, such as the type of fitness activity that the user will be performing. The UI component 110 can also be used to output information, such as biometric data, motion data, activity data, biometric signatures, and/or compliance data regarding the comparison of activity data to biometric signatures. The UI component 110 can include, for instance, a touch screen, a display screen and input buttons, or other input/output components such as the input/output components 520 described below with reference to
The communication component 112 is an interface that allows for communication of data with other devices. This may include the communication of: biometric data from the biometric sensor(s) 102; motion data from the motion sensor(s) 104; biometric signatures; activity data; and/or compliance data. By way of example only and not limitation, the communication component 112 can be a transceiver that wirelessly communicates data with other devices via radio frequency (RF) signals in accordance with any of a number of different wireless technology standards, such as Bluetooth, WiFi, Zigbee, GSM, CDMA, or LTE. The communication component 112 could alternatively be a hardware component that enables wired communication, such as, for instance, a network interface card, an Ethernet port, or a USB port.
As previously noted, the tracking and compliance system 100 can be implemented on a single device or can be distributed across multiple devices. By way of example to illustrate,
The personal device 202 is a device that is worn by the user. At a minimum, the personal device 202 includes at least one biometric sensor 102 to collect biometric data from the user. The personal device 202 can be worn by the user, for instance, using an adjustable strap or band.
The equipment device 204 is a device that is attached to fitness equipment. At a minimum, the equipment device 204 includes at least one motion sensor 104 to collect motion data during fitness activities. The equipment device 204 can be attached to fitness equipment in any of a variety of different manners. By way of example only and not limitation, the equipment device 204 can be attached to fitness equipment using an adjustable strap or a magnet (e.g., for attaching to equipment made from magnetic metal). In some configurations, a hook-and-loop fastener (e.g., a VELCRO fastener) or a bracket configured to receive the equipment device 204 can be provided on the fitness equipment. In any case, the equipment device 204 can be moved from one fitness equipment to another to allow the user to perform different fitness activities and collect motion data for each of those fitness activities using the equipment device 204.
The user device 206 is a user-owned device, such as the user's smartphone or personal computer. The user device 206 can be owned by the user performing the fitness activity or another person, such as the rehabilitation healthcare provider. In some configurations, the user device 206 can provide the UI component 110 to allow the user to interact with the tracking and compliance system 100. In some configurations, the user device 206 can provide the activity tracking module 106 and/or the compliance module 108. In such configurations, the user device 206 can receive biometric and motion data or activity data from the personal device 202 and/or the equipment device 204 and process the data using the activity tracking module 106 and/or the compliance module 108.
The server device 208 is a remote server that can be configured to provide the activity tracking module 106 and/or the compliance module 108. As such, the server device 208 can receive biometric and motion data or activity data from the personal device 202 and/or the equipment device 204 and process the data using the activity tracking module 106 and/or the compliance module 108.
With initial reference to
While
Turning next to
As shown at block 402, a type of fitness activity is initially identified. A fitness activity type may be identified in a variety of different manners in accordance with different configurations of the present technology. For instance, in some configurations, the UI component 110 presents a list of available fitness activities, and the user manually selects a fitness activity from the list. For example, the user could select a fitness activity corresponding with a particular type of curl at a particular weight. In other configurations, fitness equipment can include identification tags that are detected by the UI component 110. For instance, fitness equipment can be tagged with an RFID tag that identifies a specific fitness activity associated with the fitness equipment, and the UI component 110 can include an RFID reader for detecting the RFID tag and thereby identifying a specific fitness activity. As another example, fitness equipment could be tagged with a bar code or QR code that identifies a specific fitness activity, and the UI component 110 could include a camera for detecting the code so the code can be processed to identify the specific fitness activity.
After identifying a particular type of fitness activity, the fitness activity is performed by the user. While the fitness activity is performed by the user, biometric data is received from the biometric sensor(s) 104, as shown at block 404. Additionally, motion data is received from the motion sensor(s) 106, as shown at block 406.
A biometric signature for the identified type of fitness activity is generated for the user based on the biometric data and the motion data, as shown at block 408. The biometric signature is generated by correlating the biometric data to the motion data over time. In particular, the biometric data can comprise a time series of biometric data collected over a time period Likewise, the motion data can comprise a time series of motion data collected over the same or similar time period. The biometric data and motion data each include time data that provides information regarding the timing at which the data was collected. By way of example only and not limitation, the biometric data and motion data can be continuous and the time data can comprise an initial start time and an indication of time lapse over the course of the data. As another example, the biometric data and motion data can comprise data points, each with a corresponding indication of time. Accordingly, to generate the biometric signature, the biometric data and motion data are correlated to one another based on their time data. As such, the biometric signature comprises an indication of the biometric data occurring simultaneously with the motion data over a time period.
By way of example, suppose that only heart rate (biometric) and acceleration (motion) data points are collected. If biometric data was Y, and motion data was X, then using nonlinear regression, a polynomial could be formed which could predict Y given any X. Thus, the polynomial describes the relationship between biometric and motion data. This is only one exemplary approach for deriving the relationship. In some implementations, there can be more attributes to both the biometric data (e.g., respiration, skin conductivity, and electromyography (EMG) measurements) and to the motion data (e.g., altitude and angular velocity). Also note that using nonlinear regression is only one example, and other approaches can be used to correlate the data.
The generated biometric signature is stored, for instance, in a storage device 114, as shown at block 410. The biometric signature is stored with information (e.g., metadata) identifying the specific fitness activity corresponding to the biometric signature. As such, the biometric signature can be used to assess activity data, for instance, using the compliance module 108 as described in further detail below with reference to
With reference now to
After a particular type of fitness activity has been identified, the fitness activity is performed by the user. While the fitness activity is performed by the user, biometric data is received from the biometric sensor(s) 104, as shown at block 504. Additionally, motion data is received from the motion sensor(s) 106, as shown at block 506.
Activity data for the fitness activity is generated based on the biometric data and the motion data, as shown at block 508. The activity data is generated similar to the generation of the biometric signature discussed above. In particular, the activity data is generated by correlating the biometric data to the motion data over time. As noted above, the biometric data can comprise a time series of biometric data collected over a time period Likewise, the motion data can comprise a time series of motion data collected over the same or similar time period. The biometric data and motion data each include time data that provides information regarding the timing at which the data was collected. By way of example only and not limitation, the biometric data and motion data can be continuous and the time data can comprise an initial start time and an indication of time lapse over the course of the data. As another example, the biometric data and motion data can comprise data points, each with a corresponding indication of time. Accordingly, to generate the activity data, the biometric data and motion data are correlated to one another based on their time data. As such, the activity data comprises an indication of the biometric data occurring simultaneously with the motion data over a time period.
Similar to the example provided above for biometric signature, suppose that only heart rate (biometric) and acceleration (motion) data points are collected. If biometric data was Y, and motion data was X, then using nonlinear regression, a polynomial could be formed which could predict Y given any X. Thus, the polynomial describes the relationship between biometric and motion data. This is only one exemplary approach for deriving the relationship. In some implementations, there can be more attributes to both the biometric data (e.g., respiration, skin conductivity, and electromyography (EMG) measurements) and to the motion data (e.g., altitude and angular velocity). Also note that using nonlinear regression is only one example, and other approaches can be used to correlate the data.
The activity data is stored, for instance, in a storage device 114, as shown at block 510. The activity data is stored with information (e.g., metadata) identifying the specific fitness activity corresponding to the activity data. As such, the fitness activity can be assessed by comparing the activity data to a biometric signature for the type of fitness activity, for instance, using the compliance module 108 as described in further detail below with reference to
Compliance data for the fitness activity is generated, as shown at block 606. The compliance data is generated by comparing the activity data against the biometric signature. By way of example to illustrate, each of the activity data and biometric signature comprises biometric data correlated to motion data and each could be represented using a polynomial that describes the relationship between the biometric data and motion data. A statistical approach, such as R-squared can then be used to determine the goodness of fit to the polynomials to determine how well the activity data matched the biometric signature. This is only one exemplary approach for deriving the comparison between the activity data and the biometric signatures, other approaches can be used to make the comparison.
The compliance data is outputted, as shown at block 608. This allows the rehabilitation healthcare provider or another person to review the compliance data for compliance and other purposes.
Having described implementations of the present disclosure, an exemplary operating environment in which embodiments of the present invention may be implemented is described below in order to provide a general context for various aspects of the present disclosure. Referring initially to
The invention may be described in the general context of computer code or machine-useable instructions, including computer-executable instructions such as program modules, being executed by a computer or other machine, such as a personal data assistant or other handheld device. Generally, program modules including routines, programs, objects, components, data structures, etc., refer to code that perform particular tasks or implement particular abstract data types. The invention may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, more specialty computing devices, etc. The invention may also be practiced in distributed computing environments where tasks are performed by remote-processing devices that are linked through a communications network.
With reference to
Computing device 700 typically includes a variety of computer-readable media. Computer-readable media can be any available media that can be accessed by computing device 700 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer-readable media may comprise computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, 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 computing device 700. Computer storage media does not comprise signals per se. Communication media typically embodies computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of any of the above should also be included within the scope of computer-readable media.
Memory 712 includes computer storage media in the form of volatile and/or nonvolatile memory. The memory may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disc drives, etc. Computing device 700 includes one or more processors that read data from various entities such as memory 712 or I/O components 720. Presentation component(s) 716 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc.
I/O ports 718 allow computing device 700 to be logically coupled to other devices including I/O components 720, some of which may be built in. Illustrative components include a microphone, joystick, game pad, satellite dish, scanner, printer, wireless device, etc. The I/O components 720 may provide a natural user interface (NUI) that processes air gestures, voice, or other physiological inputs generated by a user. In some instance, inputs may be transmitted to an appropriate network element for further processing. A NUI may implement any combination of speech recognition, touch and stylus recognition, facial recognition, biometric recognition, gesture recognition both on screen and adjacent to the screen, air gestures, head and eye-tracking, and touch recognition associated with displays on the computing device 700. The computing device 700 may be equipped with depth cameras, such as, stereoscopic camera systems, infrared camera systems, RGB camera systems, and combinations of these for gesture detection and recognition. Additionally, the computing device 700 may be equipped with accelerometers or gyroscopes that enable detection of motion.
As described above, implementations of the present disclosure relate to devices for, among other things, assessing compliance with rehabilitation exercise programs. The present invention has been described in relation to particular embodiments, which are intended in all respects to be illustrative rather than restrictive. Alternative embodiments will become apparent to those of ordinary skill in the art to which the present invention pertains without departing from its scope.
From the foregoing, it will be seen that this invention is one well adapted to attain all the ends and objects set forth above, together with other advantages which are obvious and inherent to the system and method. It will be understood that certain features and subcombinations are of utility and may be employed without reference to other features and subcombinations. This is contemplated by and is within the scope of the claims.
