US20160059077A1 - Exercise therapy and rehabilitation system and method - Google Patents

Exercise therapy and rehabilitation system and method Download PDF

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Publication number
US20160059077A1
US20160059077A1 US14/837,509 US201514837509A US2016059077A1 US 20160059077 A1 US20160059077 A1 US 20160059077A1 US 201514837509 A US201514837509 A US 201514837509A US 2016059077 A1 US2016059077 A1 US 2016059077A1
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physical
metric
psychophysical
metric data
user
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Seth Paul
Andrew Merryweather
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University of Utah Research Foundation (UURF)
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University of Utah Research Foundation (UURF)
University of Utah
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Publication of US20160059077A1 publication Critical patent/US20160059077A1/en
Assigned to UNIVERSITY OF UTAH reassignment UNIVERSITY OF UTAH ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: MERRYWEATHER, ANDREW, PAUL, SETH
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Assigned to NATIONAL INSTITUTES OF HEALTH reassignment NATIONAL INSTITUTES OF HEALTH CONFIRMATORY LICENSE (SEE DOCUMENT FOR DETAILS). Assignors: UNIVERSITY OF UTAH
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Abstract

A method is provided for performing exercise therapy and rehabilitation. A first therapy module can be performed. The first therapy module comprises at least one first physical metric for rotating, by a resistance device, at least one joint of a limb of a user. At least one psychophysical metric and at least one physical metric of the user can be monitored while performing the first therapy module. Psychophysical metric data for the at least one psychophysical metric and physical metric data for the at least one physical metric can be received. Based on at least one of the psychophysical metric data and the physical metric data, the at least one first physical metric for rotating the at least one joint of the limb by the resistance device while performing the first therapy module can be modified.

Description

    CROSS REFERENCE TO RELATED PATENT APPLICATION
  • This application claims priority to U.S. Provisional Application No. 62/070,550 filed Aug. 27, 2014, herein incorporated by reference in its entirety.
  • BACKGROUND
  • Musculoskeletal disorders affect millions of people worldwide. Some musculoskeletal disorders can include tendinopathies. Examples tendinopathies include medial epicondylitis (golfer's elbow), lateral epicondylitis (tennis elbow), tendinitis, and the like. Eccentric exercise therapy/training; (EET) can be used to treat tendinopathies. However, there exists difficulty in assessing how to administer the EETs to maximize their benefits. These and other shortcomings of the prior art are identified and addressed by the present disclosure.
  • SUMMARY
  • It is to be understood that both the following general description and the following detailed description are exemplary and explanatory only and are not restrictive. Provided are methods and systems to assess functional capabilities and generate an effective treatment protocol for exercise therapy and rehabilitation. In an aspect, a method is provided for exercise therapy and rehabilitation. A first therapy module can be performed. The first therapy module can comprise at least one first physical metric for rotating, by a resistance device, at least one joint of a limb of a user. At least one psychophysical metric and at least one physical metric of the user can be monitored while performing the first therapy module. Psychophysical metric data for the at least one psychophysical metric and physical metric data for the at least one physical metric can be received. Based on at least one of the psychophysical metric data and the physical metric data, the at least one first physical metric for rotating the at least one joint of the limb by the resistance device while performing the first therapy module can be modified.
  • In an aspect, a system is provided for performing exercise therapy and rehabilitation. The system can comprise a resistance device configured to rotate at least one joint of a limb of a user according to a therapy module that comprises at least one physical metric. The system can comprise a psychophysical sensor configured to monitor a psychophysical metric of the user and a physical sensor configured to monitor a physical metric of the user. The system can further comprise a controller in communication with the resistance device, the psychophysical sensor, and the physical sensor. The controller can comprise a memory comprising computer readable instructions, and a processor that, when executing the computer readable instructions, can be configured to perform a first therapy module. The first therapy module comprises at least one first physical metric for rotating, by the resistance device, the at least one joint of the limb of the user. The processor can be further configured to receive psychophysical metric data for the at least one psychophysical metric from the psychophysical sensor and receive physical metric data for the at least one physical metric from the physical sensor. The processor can be further configured to modify the at least one first physical metric for rotating the at least one joint of the limb while performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data.
  • In a further aspect, a computer readable medium is provided for performing exercise therapy and rehabilitation. The computer readable medium can be a non-transitory computer readable medium comprising a program that when executed by a computer perform the method described above.
  • Additional advantages will be set forth in part the description which follows or may be learned by practice. The advantages will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments and together with the description, serve to explain the principles of the methods and systems:
  • FIG. 1 is a block diagram of an example system;
  • FIG. 2 is a diagram of an example system;
  • FIG. 3 is an example graph illustrating results of a therapy module;
  • FIG. 4 is an example graph illustrating results of a therapy module;
  • FIG. 5 is a flowchart illustrating an example method; and
  • FIG. 6 is a block diagram of an example computing device.
  • DETAILED DESCRIPTION
  • Before the present methods and systems are disclosed and described, it is to be understood that the methods and systems are not limited to specific methods, specific components, or to particular implementations. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.
  • As used in the specification and the appended claims, the singular forms “a,” “an” and “the” include plural referents unless the context clearly dictates otherwise. Ranges may be expressed herein as from “about” one particular value, and/or to “about” another particular value. When such a range is expressed, another embodiment includes from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent “about,” it will be understood that the particular value forms another embodiment. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint.
  • “Optional” or “optionally” means that the subsequently described event or circumstance may or may not occur, and that the description includes instances where said event or circumstance occurs and instances where it does not.
  • Throughout the description and claims of this specification, the word “comprise” and variations of the word, such as “comprising” and “comprises,” means “including but not limited to,” and is not intended to exclude, for example, other components, integers or steps. “Exemplary” means “an example of” and is not intended to convey an indication of a preferred or ideal embodiment. “Such as” is not used in a restrictive sense, but for explanatory purposes.
  • Disclosed are components that can be used to perform the disclosed methods and systems. These and other components are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these components are disclosed that while specific reference of each various individual and collective combinations and permutation of these may not be explicitly disclosed, each is specifically contemplated and described herein, for all methods and systems. This applies to all aspects of this application including, but not limited to, steps in disclosed methods. Thus, if there are a variety of additional steps that can be performed it is understood that each of these additional steps can be performed with any specific embodiment or combination of embodiments of the disclosed methods.
  • The present methods and systems may be understood more readily by reference to the following detailed description of preferred embodiments and the examples included therein and to the Figures and their previous and following description.
  • As will be appreciated by one skilled in the art, the methods and systems may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the methods and systems may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions (e.g., computer software) embodied in the storage medium. More particularly, the present methods and systems may take the form of web-implemented computer software. Any suitable computer-readable storage medium may be utilized including hard disks, CD-ROMs, optical storage devices, or magnetic storage devices.
  • Embodiments of the methods and systems are described below with reference to block diagrams and flowchart illustrations of methods, systems, apparatuses and computer program products. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create a means for implementing the functions specified in the flowchart block or blocks.
  • These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including computer-readable instructions for implementing the function specified in the flowchart block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions that execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.
  • Accordingly, blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions or steps, or combinations of special purpose hardware and computer instructions.
  • The present disclosure relates to a system and a method for exercise therapy and rehabilitation. The exercise therapy and rehabilitation can be used to treat musculoskeletal disorders such as tendinopathies. Examples of tendinopathies include, but are not limited to, medial epicondylitis (golfers elbow), lateral epicondylitis (tennis elbow), tendinitis, and the like. The focus of this disclosure is based on tendinopathies and more specifically lateral epicondylalgia (LE) for clarity. However, it will be apparent to one of ordinary skill in the art that the method and system disclosed herein can be used for many other musculoskeletal disorders, exercise therapy, rehabilitation, muscle training and the like. In an aspect, a system to improve treatment for a tendinopathy can comprise a controller and a resistance device such as a force-feedback robotic interface that provides users with the ability to identify eccentric exercise protocols that maximize the benefits of eccentric exercise therapy/training (EET) for the tendinopathy. The system can comprise sensors to monitor psychophysical metrics (e.g., pain level) and physical metrics (e.g., limb angle, torque, motion, angular velocity, number of repetitions, number of sets, combinations thereof, and the like) of a user of the system. Psychophysical metric data and physical metric data can be used to create a patient-specific eccentric exercise therapy/training protocol/module to elicit a progressive tendon response.
  • As an example, LE or “tennis elbow” is the most common elbow disorder and affects 1-3% of the general population. The majority of patients are ages 35 to 54, LE involves pathological changes at the insertion of the extensor carpi radialis brevis and extensor digitorum.
  • Disagreement exists among professionals about specific diagnoses and treatment. Approximately 22 treatment methods have been investigated through randomized clinical trials (RTC). Common conservative treatment methods include NSAIDs, steroid injections, sonic therapies, stretching, exercise, acupuncture, and wait-and-see approaches. Most treatments have little or weak evidence supporting the methods as successful approaches to treating LE. In addition to negative results, some treatments result in adverse side-effects. More recently, loading the muscle-tendon unit via eccentric contractions has gained attention as a potentially beneficial treatment for tendinopathies, including tendinitis in the lower extremity. Many studies have found exercise and specifically eccentric loading beneficial to reducing upper extremity LE pain and reducing lost work days. Eccentric exercises are effective in the treatment of tendinopathies at various locations of the body such as the Achilles tendon, patellar tendon, lateral elbow, and rotator cuff.
  • Both healthy and unhealthy tendons respond to controlled progressive stress resulting in increases in tensile strength. Eccentric contractions constitute an ideal mode of progressively stressing tendons. Eccentric contractions occur when muscle-tendon units actively lengthen under stress, producing “negative work.” More force can be generated on a tendon using eccentric contraction compared with concentric contractions. Three beliefs that govern eccentric exercise program benefits include: muscle length, ii) load, and iii) speed of contraction. The majority of methods available for upper extremity rehabilitation and eccentric exercise utilize modified strength training equipment, free weights, or elastic members. These loading methods have differing characteristics, each with its own advantages and disadvantages.
  • In an aspect, the methods and systems disclosed can provide full control over the presentation of eccentric loading to the user. Tendons can become stronger as fibroblast activity increases and an appropriate collagen reaction accelerates. The system and method are tunable for each individual to elucidate a more precise and ultimately optimal therapy/training to promote a mechanobiological response of tendon fibroblasts during repetitive loading.
  • In an aspect, the methods and systems disclosed can generate customizable treatment protocols (e.g., therapy modules and assessment modules including a variable resistance function that complements the muscles' natural torque-posture relationships. The methods and systems disclosed can comprise a resistance device that can provide users with directly controllable resistance to maximize the benefit of eccentric exercise. The methods and systems disclosed can augment treatment, reduce clinical contact hours, and balance the levels of exertion with a patient's capability. Customizable treatment protocols including a variable resistance, individualized model that complements the person's muscles' natural torque-angle relationships can be considered. The methods and systems disclosed can be capable of accurately measuring and quantifying precision resistance protocols during rehabilitation. The methods and systems disclosed may offer therapists and healthcare providers with a treatment tool to design a patient-specific protocol and track changes in real-time. The methods and systems disclosed can allow more specific research on the effects of eccentric loading on tendinopathy. Researchers and clinicians can have the ability to evaluate exercise levels and record perceived discomfort from a user. The combination of this data along with precise information about magnitude, duration, speed, and muscle length can support future research to identify optimal protocols to maximize patient outcomes. The data gained can be used to generate beneficial rehabilitation protocol for LE and other common tendinopathies. The methods and systems disclosed may also improve early diagnosis of LE and assist in the prevention of LE.
  • FIG. 1 illustrates a block diagram of a system 100 for providing exercise therapy and rehabilitation, according to various aspects. In an aspect, the system 100 can comprise a controller 105 in communication with a resistance device 110 and a display 115. In an aspect, the controller 105 can comprise a control unit 120 and a data acquisition unit 125. In an aspect, the controller 105, through the display 115, can provide a graphical user interface to input physical metrics. The controller 105 can construct a therapy module from the physical metrics and the control unit 120 can control the resistance device 110 through an output command voltage based on the therapy module. The data acquisition unit 125 can receive data from one or more sensors for dynamically adjusting the therapy module while therapy is taking place on a user 130. The resistance device 110 can comprise a motor and gear assembly 135 configured to rotate a limb positional unit 140. The resistance device 110 can convert the output command voltage from the control unit 120 to a torque output applied by the motor and gear assembly 135 to the limb positional unit 140, which applies the torque to the user 130 that is in contact with the limb positional unit 140. In exemplary aspects, a hand of the user 130 can be positioned in contact with the limb positional unit 140, which can optionally, as illustrated in FIG. 2, comprise a handle and/or grip 205. Optionally, as shown in FIG. 2, the limb positional unit 140 can comprise a support element 210 that is configured to support a limb of the user 130 in a desired operative position relative to the handle and/or grip. In exemplary aspects, as shown in FIG. 2, the limb positional unit 140 can comprise at least one restraint element 212 (e.g., at least one strap) that is configured to secure the limb of the user 130 in the desired operative position. In further exemplary aspects, the limb positional unit 140 can be configured for rotation relative to a plurality of axes (e.g., two perpendicular axes or three perpendicular axes). However, it is contemplated that, in some configurations, the limb positional unit 140 can be configured for rotation relative to a single axis. It is further contemplated that, relative to each respective axis for rotation of the limb positional unit 140, the limb positional unit 140 can be configured for rotation within an angular range of about 0 degrees to about 360 degrees, 0 degrees to about 270 degrees, 0 degrees to about 180 degrees, 0 degrees to about 90 degrees, and the like. In an aspect, the motor and gear assembly 135 can apply a torque ranging from about 1 Nm to about 40 Nm, including exemplary torques of 1 Nm, 5 Nm, 10 Nm, 20 Nm, 25 Nm, and the like, to the limb positional unit 140 at rotational speed ranging from about 1 degree/second to about 190 degrees/second, including exemplary rotational speeds of 1 degree/second, 10 degrees/second, 25 degrees/second, 100 degrees/second, 180 degrees/second, and the like. An amplifier (not illustrated) can do the conversion of the output command voltage to power the motor and gear assembly 135. The resistance device 110 can have a power supply 145 that can be in electrical communication with a power source 150 to supply power to components of the resistance device 110.
  • In an aspect, the resistance device 110 can comprise at least one physical sensor 155 (e.g., torque sensor, force sensor, strain sensor, position sensor, potentiometer, camera, encoder, torque transducer, and the like, a physiological sensor 160 (e.g., electromyography (EMG), electroencephalography (EEG), heart rate monitor, skin water content monitor, skin softness monitor, and the like.), and a psychophysical sensor 165 (e.g., pain input device, pressure transducer, variable resistor, exertion measurement device, and the like). In an aspect, the physical sensor 155, the psychophysical sensor 160, the physiological sensor 165, combinations thereof, and the like can be standalone devices separate from the resistance device 110 and in communication with the controller 105. In an aspect, one or more of the sensors 155, 160, and 165 can communicate to the controller 105 through the data acquisition unit 125. The physical sensor 155 can monitor a physical metric and gather physical metric data. For example, the physical sensor 155 can monitor limb angle, torque, motion, angular velocity, number of repetitions, number of sets of repetitions, combinations thereof, and the like. The physical sensor 155 can send respective data to the data acquisition unit 125. The physiological sensor 160 can monitor a physiological metric and gather physiological metric data. For example, the physiological sensor 160 can monitor muscle contractions through electromyography and send EMG data to the data acquisition unit 125. The psychophysical sensor 165 can monitor a psychophysical metric and gather psychophysical metric data. For example, the psychophysical sensor 165 can monitor a pain level of the user 130. Optionally, as illustrated in FIG. 2, the psychophysical sensor 165 can be a pain input device 215 that the user 130 can interact with while a module is being performed on the user to send pain level data to the data acquisition unit 125.
  • The pain input device 215 can be an electronic device such as a computer, a smartphone, a laptop, a tablet, a set top box, a display device, or other device capable of communicating with the controller 105. In another aspect, the pain input device 215 can be an input device that the user can enter commands and information into the controller 105 via an input device Examples of such input devices comprise, but are not limited to, a keyboard, pointing device (e.g., a “mouse”), a microphone, a joystick, a scanner, tactile input devices such as gloves, and other body coverings, and the like. In an aspect, the pain input device 215 can be positioned to permit the user 130 to interact with it while the user is performing a module.
  • In an aspect, the system 100 can comprise one or more safety units 170 for the system 100 to be safe for the user 130. The safety unit 170 can be metric monitoring for determining whether a metric has reached a virtual wall/threshold, mechanical stops, and unexpected input physical metric warnings, combinations thereof, and the like. The safety unit 170 can be located on one or more of the controller 105, the resistance device 110, or as a standalone device of the system 100. Optionally, as illustrated in FIG. 2, the safety unit 170 can comprise an emergency stop switch 220 located on the pain input device 215.
  • In an aspect, the controller 105 and/or resistance device 110 can be remotely accessed by a second controller or other computing device over a network. Remote access by the second controller over the network can allow for remote access to data to track progress of the user 130. In an aspect, remote access can also allow for a therapist to conduct an exercise therapy and rehabilitation session at a separate location than that of the system 100.
  • In an aspect, a limb of a user 130 can be in contact with the limb positional unit 140 of the resistance device 110. A module stored on the controller 105 can be initiated by the user 139. The controller 105 can store an assessment module, a therapy module, and a support module. The assessment module can be used to assess the user's 130 current abilities. The therapy module can apply a therapy/training session to user 130 with the resistance device 110. The therapy module can use data gathered by the assessment module to customize the therapy applied to the user 130. The support module can be used to interface the assessment module with the therapy module. The support module can also be used for record management and review.
  • In an aspect, the user 130 can select the assessment module to begin the overall therapy/training. The assessment module can generate data for the controller 105 to determine the baseline capabilities of the user 130 so as to allow the controller 105 to generate a customized therapy module. The assessment module can comprise one or more of an active range of motion module, a passive range of motion module, an isometric fatigue module, an isometric break test module, a pain or discomfort intensity module, an isokinetic strength module, an isotonic strength module, and the like. The active range of motion module can utilize a zero desired torque control allowing the user 130 to move to the extent of their active range of motion in flexion and extension through their own volition and capability. Neutral posture is recorded from user's 130 inputs. The passive range of motion module can be conducted similar to the active range of motion but the resistance device 110 can rotate the limb positional unit 140 into flexion and extension at an adjustable velocity. The rotation can stop if a measured physical metric exceeds an adjustable physical metric threshold or a psychophysical metric exceeds a psychophysical metric threshold. For example, if a measured torque exceeds a torque threshold or a pain level exceeds a pain level threshold then the rotation can stop. Neutral posture is recorded similar to the active range of motion module. The isometric fatigue module can allow the user 130 to apply a maximum flexion and extension at selected limb positions in the limb positional unit 140. A maximum voluntary contraction (MVC) can be recorded. The isometric break test module can start as a zero torque and can increase according to an adjustable rate in the direction selected by the user 130. The user 130 is meant to keep the limb positional unit 140 stationary as long as possible, Upon deviating from a set angle by more than a threshold (e.g., one degree, five degrees, and ten degrees), the isometric break test module ends and the maximum torque is presented for the tested angle.
  • In an aspect, after the user 130 has completed the assessment module, the user 130 can select the therapy module. The therapy module can be generated by the controller 105 based on one or more physical metrics monitored during the assessment module and inputs from the user 130 or a therapist. In an aspect, the therapy module can comprise one or more of a torque controlled therapy module, a velocity controlled therapy module, a pain or discomfort module and the like. The torque controlled therapy module can supply an adjustable torque for extensor eccentric contraction and can assist the user 130 back to a maximal extension position when maximal flexion is reached. The user 130 is to resist the extensor elongation according to the effort prescribed by the therapy module. If the controller 105 determines psychophysical metric data or physiological metric data exceeds a threshold, the controller 105 can adjust the therapy module. For example, if the user 130 inputs a pain level higher than a predetermined pain level threshold, the controller 105 can shut down the resistance device 110 or adjust the therapy module. For example, the controller 105 can modify a maximum torque value for the angle at which the pain level threshold is satisfied. This module can also be reversed to supply a torque for the flexor eccentric contraction and can assist the user 130 back to a maximal flexion position when maximal extension is reached.
  • In an aspect, the velocity-controlled therapy module can supply an adjustable velocity for extensor eccentric contraction and can assist the user 130 back to a maximal extension position when maximal flexion is reached. The user 130 is to resist the extensor elongation according to the effort prescribed by the velocity controlled therapy module. Similar to the torque control module, if the controller 105 determines psychophysical metric data or physiological metric data exceeds a threshold, the controller 105 can adjust the therapy module. For example, if the user 130 inputs a pain level higher than a predetermined pain level threshold, the controller 105 can shut down the resistance device 110 or adjust the therapy module. For example, the controller 105 can modify a maximum velocity value for the angle at which the pain level threshold was satisfied. More advanced velocity-defined stimuli customization can be available to advanced users 130.
  • In an aspect, as the therapy module is being performed, one or more sensors, (e.g., physical sensor 145, the physiological sensor 150 and the psychophysical sensor 155 can monitor at least one physical metric, at least one physiological metric, and/or at least one psychophysical metric, respectively. The data acquisition unit 125 of the controller 105 can receive physical metric data, physiological metric data, and/or psychophysical metric data gathered by the one or more sensors. The controller 105 can modify a first physical metric of the therapy module based on the physical metric data, the physiological metric data, and/or the psychophysical metric data received.
  • In an aspect, the controller 105 can generate a second therapy module based on one or more of the physical metric data, physiological metric data, and/or psychophysical metric data. The second therapy module can comprise at least one second physical metric to be performed by the resistance device 110. The controller 105 can perform the second therapy module for the at least one joint of the limb of the user. For example, if the first therapy module resulted in psychophysical metric data reaching a threshold (e.g., high pain level), then the controller 105 can adjust physical metrics (e.g., limb angle, torque, motion, angular velocity, number of repetitions, number of sets, combinations thereof, and the like) of the first therapy module to create the second therapy module. For example, if the pain level of the user 130 increases from the third repetition to the fourth repetition, the controller 105 can cause the second therapy module to decrease the number of repetitions or decrease the torque on the fourth repetition. In another example, if during repetitions the user 130 indicates a pain level greater than a pain level threshold at a certain angle or range of angles, then the controller 105 can adjust the physical metric of torque at that angle or range of angles to lower torque value. Likewise, if a user 130 successfully completes the first therapy module without the user's pain level satisfying a pain level threshold, then the controller 105 can adjust physical metrics (e.g., increasing torque and/or velocity) of the second therapy module to further challenge the user 130.
  • The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how the compounds, compositions, articles, devices and/or methods claimed herein are made and evaluated, and are intended to be purely exemplary and are not intended to limit the scope of the methods and systems. Efforts have been made to ensure accuracy with respect to numbers (e.g., amounts, temperature, etc.), but some errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, temperature is in ° C. or is at ambient temperature, and pressure is at or near atmospheric.
  • FIG. 3 illustrates an example graph 300 outputted on the display 115 of a psychophysical metric (e.g., a pain level) of a user 130 versus a physical metric (e.g., joint angle). To evaluate the pain level feedback system's effectiveness in representing real time perceived pain, specific exercise profiles derived from physical and psychophysical metrics can be tested. First, the controller 105 can generate baseline torque profiles with regard to a user's % MVC over their range of motion to determine a target torque profile as indicated by line 305 of graph 300. Next, the controller 105 can execute an algorithm using a fading memory filter to adjust the target torque profile based on feedback of changes in perceived pain. A fading memory filter can adjust the target torque profile based on:

  • τi+1=(1−ni−1 −k(n)p i
  • where: τi+1 is the future target torque, τi−1 is the previous target torque, pi is the present pain level from 0 (none) to 10 (maximum), k is a gain to adapt the pain level to a corresponding target torque, and n is percentage of the present target torque to be used in calculating the future target torque.
  • The fading memory filter can prevent rapid changes in the target torque profile by balancing the weighting of the history of perceived pain with the current value of perceived pain. Real-time input of perceived “pain” can be recorded and displayed to the user 130 through a Graphical User Interface (GUI) as shown in FIG. 3. The recorded “pain” data can then be compared to the simulated pain profiles and the effects of lag in response time, range scaling, and offsets between the actual and perceived pain profiles can be quantified and integrated into the therapy module. The controller 105 can then execute the updated therapy module with the future target torque profile as indicated by line 310 of graph 300 to decrease the pain level for the user 130.
  • FIG. 4 illustrates example graphs 400 outputted on the display 115. The system 100 can assess and record a user's physical capabilities and perceived discomfort during an exertion, System classification of the user's volitional limb posture can be used to compare unaffected to affected limbs. This data can provide users with a method to track progress and tune the therapy module to generate a user specific therapy module. In graph 405, maximum voluntary contraction (MVC) can be recordable through several assessment modules according to the user's selection. For example, the assessment module can include isometric strength at up to six postures across the range of motion, concentric strength at various angular velocities, eccentric strength at various angular velocities, combinations thereof, and the like. A pain level input device can allow continuous readings of pain level measurements to be recorded by the user through the range of motion generated by the assessment modules. The pain level measurements can help to inform the user while creating the user specific therapy module, The system 100 can also allow for the unaffected arm to be tested and provide the unaffected arm's values as a comparison. Assortment of measurements can allow users to more effectively track and analyze the user's condition particularly in response to a selected therapy module. The recorded values will be available for review and comparison over the history of therapy modules.
  • As illustrated in graph 405, the assessment module can indicate the user's measured MVC in Nm versus an angle of the joint, Pain levels can also be recorded during the assessment module. As indicated in graph 405, the user can experience high pain levels from 0 degrees to 60 degrees. The controller 105 can use the physical metric data and the psychophysical metric data obtained by performing the assessment module to determine the user specific therapy module. As illustrated in graph 410, the user specific therapy module can be customized to have an eccentric torque as a percentage of the MVC. The controller 105 can adjust the eccentric torque to a lesser percentage of MVC at the joint angle where the user began to experience the most pain and extend the range of motion at the adjusted eccentric torque. The reduction of eccentric torque can help reduce the pain level of the user at those joint angles that were painful during the assessment but also provide therapeutic benefit of performing the eccentric exercise at the joint angles that were painful. Graph 415 illustrates an assessment after a user specific therapy module is performed. The user can experience a reduction in pain, greater range of motion, and greater strength when performing the assessment module for a second time.
  • FIG. 5 illustrates a flowchart of a method 500 of exercise therapy and rehabilitation, according to various aspects. In step 502 a first therapy module can be performed. The first therapy module can be executed by a controller such as controller 105 of FIG. 1. In an aspect, the first therapy module can comprise at least one first physical metric for rotating, by a resistance device (e.g., resistance device 115), at least one joint of a limb of a user. Examples of the at least one first physical metric comprise limb angle, torque, motion, angular velocity, number of repetitions, number of sets, combinations thereof, and the like.
  • In an aspect, the first therapy module can be an assessment module. The assessment module can generate data for the controller 105 to determine the baseline capabilities of the user 130 so as to form a more customized therapy module. The assessment module can comprise one or more of an active range of motion module, a passive range of motion module, an isometric fatigue module, an isometric break test module, a pain or discomfort intensity module, an isokinetic strength module, an isotonic strength module, and the like.
  • In an aspect, the therapy module can comprise one or more of a torque controlled therapy module, a velocity controlled therapy module, a pain or discomfort intensity module, and the like. The torque controlled therapy module can supply an adjustable torque to the resistance device 110 for extensor eccentric contraction. The velocity-controlled therapy module can supply an adjustable velocity to the resistance device 110 for extensor eccentric contraction.
  • In step 504, at least one psychophysical metric and at least one physical metric of the user can be monitored while the first therapy module is performed. In an aspect, at least one physical sensor can monitor for at least one physical metric. In an aspect, at least one psychophysical sensor (e.g., pain level input device, pressure transducer, variable resistor, exertion measurement device, and the like) can monitor for at least one psychophysical metric (e.g., pain level). In another aspect, a physiological sensor (e.g., electromyography (EMG), electroencephalography (EEG), heart rate monitor, skin water content monitor, skin softness monitor, and the like.) can monitor for at least one physiological metric (e.g., muscle activity, heart rate, heart pulse, moisture level, and the like).
  • In step 506, psychophysical metric data tor the at least one psychophysical metric and physical metric data for the at least one physical metric can be received. In an aspect, the controller 105 can receive the psychophysical metric data and the physical metric data. In an aspect, the controller 105 can also receive physiological metric data from the physiological sensor.
  • In step 508, the at least one first physical metric for rotating the at least one joint of the limb by the resistance device 110 can be modified while performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data. In an aspect, the controller 105 can modify the at least one first physical metric. In an aspect, the at least one first physical metric can be modified based on physiological metric data. In an aspect, modifying the at least one first physical metric can be determined based on whether at least one of the psychophysical metric data and the physical metric data has satisfied a threshold.
  • In an aspect, the controller 105 can generate a second therapy module comprising at least one second physical metric for rotating the at least one joint of the limb based on the at least one first physical metric and at least one of the psychophysical metric data or the physical metric data. The controller 105 can cause the resistance device 110 to perform the second therapy module on the at least one joint of the limb of the user. In an aspect, psychophysical metric data and physical metric data can be received from a second user. The controller 105 can receive psychophysical metric data and physical metric data from the second user over a network. The controller 105 can modify the first therapy module for the first user based on the psychophysical metric data and the physical metric data from the second user. The methods and systems can employ Artificial Intelligence techniques such as machine learning and iterative learning to modify the first therapy module for the first user based on the psychophysical metric data and the physical metric data from the second user. Examples of such techniques include, but are not limited to, expert systems, case based reasoning, Bayesian networks, behavior based AI, neural networks, fuzzy systems, evolutionary computation (e.g. genetic algorithms), swarm intelligence (e.g. ant algorithms), and hybrid intelligent systems (e.g. Expert inference rules generated through a neural network or production rules from statistical teaming).
  • In an exemplary aspect, the methods and systems can be implemented on a computer 601 as illustrated in FIG. 6 and described below. By way of example, controller 105 of FIG. 1 can be a computer as illustrated in FIG. 6. Similarly, the methods and systems disclosed can utilize one or more computers to perform one or more functions in one or more locations. FIG. 6 is a block diagram illustrating an exemplary operating environment for performing the disclosed methods. This exemplary operating environment is only an example of an operating environment and is not intended to suggest any limitation as to the scope of use or functionality of operating environment architecture. Neither should the operating environment be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment.
  • The present methods and systems can be operational with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known computing systems, environments, and/or configurations that can be suitable for use with the systems and methods comprise, but are not limited to, personal computers, server computers, laptop devices, and multiprocessor systems. Additional examples comprise set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that comprise any of the above systems or devices, and the like.
  • The processing of the disclosed methods and systems can be performed by software components. The disclosed systems and methods can be described in the general context of computer-executable instructions, such as program modules, being executed by one or more computers or other devices. Generally, program modules comprise computer code, routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The disclosed methods can also be practiced in grid-based and distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in both local and remote computer storage media including memory storage devices.
  • Further, one skilled in the art will appreciate that the systems and methods disclosed herein can be implemented via a general-purpose computing device in the form of a computer 601. The components of the computer 601 can comprise, but are not limited to, one or more processors 603, a system memory 612, and a system bus 613 that couples various system components including the one or more processors 603 to the system memory 612. The system can utilize parallel computing.
  • The system bus 613 represents one or more of several possible types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, or local bus using any of a variety of bus architectures. By way of example, such architectures can comprise an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, an Accelerated Graphics Port (AGP) bus, and a Peripheral Component Interconnects (PCI), a PCI-Express bus, a Personal Computer Memory Card Industry Association (PCMCIA), Universal Serial Bus (USB) and the like. The bus 613, and all buses specified in this description can also be implemented over a wired or wireless network connection and each of the subsystems, including the one or more processors 603, a mass storage device 604, an operating system 605, therapy software 606, therapy data 607, a network adapter 608, the system memory 612, an Input/Output Interface 610, a display adapter 609, a display device 611, and a human machine interface 602, can be contained within one or more remote computing devices 614 a,b,c at physically separate locations, connected through buses of this form, in effect implementing a fully distributed system.
  • The computer 601 typically comprises a variety of computer readable media.
  • Exemplary readable media can be any available media that is accessible by the computer 601 and comprises, for example and not meant to be limiting, both volatile and non-volatile media, removable and non-removable media. The system memory 612 comprises computer readable media in the form of volatile memory, such as random access memory (RAM), and/or non-volatile memory, such as read only memory (ROM). The system memory 612 typically contains data such as the therapy data 607 and/or program modules such as the operating system 605 and the therapy software 606 that are immediately accessible to and/or are presently operated on by the one or more processors 603.
  • In another aspect, the computer 601 can also comprise other removable/non-removable, volatile/non-volatile computer storage media. By way of example, FIG. 6 illustrates the mass storage device 604 which can provide non-volatile storage of computer code, computer readable instructions, data structures, program modules, and other data for the computer 601. For example and not meant to be limiting, the mass storage device 604 can be a hard disk, a removable magnetic disk, a removable optical disk, magnetic cassettes or other magnetic storage devices, flash memory cards, CD-ROM, digital versatile disks (DVD) or other optical storage, random access memories (RAM), read only memories (ROM), electrically erasable programmable read-only memory (EEPROM), and the like.
  • Optionally, any number of program modules can be stored on the mass storage device 604, including by way of example, the operating system 605 and the therapy software 606. Each of the operating system 605 and the therapy software 606 (or some combination thereof; can comprise elements of the programming and the therapy software 606. The therapy data 607 can also be stored on the mass storage device 604. The therapy data 607 can be stored in any of one or more databases known in the art. Examples of such databases comprise, DB2®, Microsoft® Access, Microsoft® SQL Server, Oracle®, mySQL, PostgreSQL, and the like. The databases can be centralized or distributed across multiple systems.
  • In another aspect, the user can enter commands and information into the computer 601 via an input device (not shown). Examples of such input devices comprise, but are not limited to, a keyboard, pointing device (e.g., a “mouse”), a microphone, a joystick, a scanner, tactile input devices such as gloves, and other body coverings, and the like These and other input devices can be connected to the one or more processors 603 via the human machine interface 602 that is coupled to the system bus 613, but can be connected by other interface and bus structures, such as a parallel port, game port, an IEEE 1394 Port (also known as a Firewire port), a serial port, or a universal serial bus (USB).
  • In yet another aspect, the display device 611 can also be connected to the system bus 613 via an interface, such as the display adapter 609. It is contemplated that the computer 601 can have more than one display adapter 609 and the computer 601 can have more than one display device 611 For example, the display device 611 can be a monitor, an LCD (Liquid Crystal Display), or a projector. In addition to the display device 611, other output peripheral devices can comprise components such as speakers (not shown) and a printer (not shown) which can be connected to the computer 601 via the Input/Output Interface 610. Any step and/or result of the methods can be output in any form to an output device. Such output can be any form of visual representation, including, but not limited to, textual, graphical, animation, audio, tactile, and the like. The display device 611 and computer 601 can be part of one device, or separate devices.
  • The computer 601 can operate in a networked environment using logical connections to one or more remote computing devices 614 a,b,c. By way of example, a remote computing device can be a personal computer, portable computer, smartphone, a server, a router, a network computer, a peer device or other common network node, and so on. Logical connections between the computer 601 and a remote computing device 614 a,b,c can be made via a network 615, such as a local area network (LAN) and/or a general wide area network (WAN). Such network connections can be through the network adapter 608. The network adapter 608 can be implemented in both wired and wireless environments. Such networking environments are conventional and commonplace in dwellings, offices, enterprise-wide computer networks, intranets, and the Internet.
  • For purposes of illustration, application programs and other executable program components such as the operating system 605 are illustrated herein as discrete blocks, although it is recognized that such programs and components reside at various times in different storage components of the computing device 601, and are executed by the one or more processors 603 of the computer. An implementation of the therapy software 606 can be stored on or transmitted across some form of computer readable media. Any of the disclosed methods can be performed by computer readable instructions embodied on computer readable media. Computer readable media can be any available media that can be accessed by a computer. By way of example and not meant to be limiting, computer readable media can comprise “computer storage media” and “communications media.” “Computer storage media” comprise volatile and non-volatile, removable and non-removable media implemented in any methods or technology for storage of information such as computer readable instructions, data structures, program modules, or other data. Exemplary computer storage media comprises, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical 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 a computer.
  • While the methods and systems have been described in connection with preferred embodiments and specific examples, it is not intended that the scope be limited to the particular embodiments set forth, as the embodiments herein are intended in all respects to be illustrative rather than restrictive.
  • Unless otherwise expressly stated, it is in no way intended that any method set forth herein be construed as requiring that its steps be performed in a specific order. Accordingly, where a method claim does not actually recite an order to be followed by its steps or it is not otherwise specifically stated in the claims or descriptions that the steps are to be limited to a specific order, it is in no way intended that an order be inferred, in any respect, This holds for any possible non-express basis for interpretation, including: matters of logic with respect to arrangement of steps or operational flow; plain meaning derived from grammatical organization or punctuation; the number or type of embodiments described in the specification.
  • Throughout this application, various publications are referenced. The disclosures of these publications in their entireties are hereby incorporated by reference into this application in order to more fully describe the state of the art to which the methods and systems pertain.
  • It will be apparent to those skilled in the art that various modifications and variations can be made without departing from the scope or spirit. Other embodiments will be apparent to those skilled in the art from consideration of the specification and practice disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit being indicated by the following claims.

Claims (20)

What is claimed is:
1. A method, comprising:
performing a first therapy module, wherein the first therapy module comprises at least one first physical metric for rotating by a resistance device, at least one joint of a limb of a user;
monitoring at least one psychophysical metric and at least one physical metric of the user while performing the first therapy module;
receiving psychophysical metric data for the at least one psychophysical metric and physical metric data for the at least one physical metric; and
modifying the at least one first physical metric for rotating the at least one joint of the limb by the resistance device while performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data.
2. The method of claim 1, further comprising generating a second therapy module comprising at least one second physical metric for rotating the at least one joint of the limb based on the at least one first physical metric and at least one of the psychophysical metric data or the physical metric data.
3. The method of claim 2, further comprising performing the second therapy module on the at least one joint of the limb of the user.
4. The method of claim 1, wherein modifying the at least one first physical metric for rotating the at least one joint of the limb by the resistance device while performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data comprises determining whether at least one of the psychophysical metric data and the physical metric data has satisfied a threshold.
5. The method of claim 1, further comprising,
receiving psychophysical metric data and physical metric data from a second user; and
modifying the first therapy module for the first user based on the psychophysical metric data and the physical metric data from the second user.
6. The method of claim 1, wherein the psychophysical metric data comprises a subjective pain level.
7. The method of claim 1, wherein the physical metric data comprises a torque of a percentage of maximum voluntary contraction (MVC) of the limb.
8. A system comprising:
a resistance device configured to rotate at least one joint of a limb of a user according to a therapy module that comprises at least one physical metric;
a psychophysical sensor configured to monitor a psychophysical metric of the user;
a physical sensor configured to monitor a physical metric of the user; and
a controller in communication with the resistance device, the psychophysical sensor, and the physical sensor, the controller comprising:
a memory comprising computer readable instructions, and
a processor that, when executing the computer readable instructions, is configured to:
perform a first therapy module, wherein the first therapy module comprises at least one first physical metric for rotating, by the resistance device, the at least one joint of the limb of the user,
receive psychophysical metric data for the at least one psychophysical metric from the psychophysical sensor,
receive physical metric data for the at least one physical metric from the physical sensor, and
modify the at least one first physical metric for rotating the at least one joint of the limb While performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data.
9. The system of claim 8, wherein the processor is further configured to generate a second therapy module comprising at least one second physical metric for rotating the at least one joint of the limb based on the at least one first physical metric and at least one of the psychophysical metric data or the physical metric data.
10. The system of claim 9, wherein the processor is further configured to perform the second therapy module on the at least one joint of the limb of the user.
11. The system of claim 8, further comprising a physiological sensor configured to monitor a physiological metric of the user.
12. The system of claim 8, wherein the processor is further configured to,
receive psychophysical metric data and physical metric data from a second user, and
modify the first therapy module for the first user based on the psychophysical metric data and the physical metric data from the second user.
13. The system of claim 8, wherein the psychophysical metric data comprises a subjective pain level.
14. The system of claim 8, wherein the physical metric data comprises a torque of a percentage of maximum voluntary contraction (MVC) of the limb.
15. A non-transitory computer readable storage medium comprising a program which, when executed, causes a computer to perform a method, comprising:
performing a first therapy module, wherein the first therapy module comprises at least one first physical metric for rotating, by a resistance device, at least one joint of a limb of a user;
monitoring at least one psychophysical metric and at least one physical metric of the user while performing the first therapy module;
receiving psychophysical metric data for the at least one psychophysical metric and physical metric data for the at least one physical metric; and
modifying the at least one first physical metric for rotating the at least one joint of the limb by the resistance device while performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data.
16. The non-transitory computer readable medium of claim 15, further comprising generating a second therapy module comprising at least one second physical metric for rotating the at least one joint of the limb based on the at least one first physical metric and at least one of the psychophysical metric data or the physical metric data.
17. The non-transitory computer readable medium of claim 16, further comprising performing the second therapy module on the at least one joint of the limb of the user.
18. The non-transitory computer readable medium of claim 15, wherein modifying the at least one first physical metric for rotating the at least one joint of the limb by the resistance device while performing the first therapy module based on at least one of the psychophysical metric data and the physical metric data comprises determining whether at least one of the psychophysical metric data and the physical metric data has satisfied a threshold.
19. The non-transitory computer readable medium of claim 15, further comprising,
receiving psychophysical metric data and physical metric data from a second user, and
modifying the first therapy module for the first user based on the psychophysical metric data and the physical metric data from the second user.
20. The non-transitory computer readable medium of claim 15, wherein the psychophysical metric data comprises a subjective pain level.
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