Sensor-based real-time tracking game (SRT)

Abstract

A method and associated system of assessing and improving proprioceptive performance in a subject are provided. The method includes measuring motion of a subject's extremity with an inertial sensing device affixed to the subject's extremity, and presenting on a display a first target representing an aimpoint for the subject, and a second target representing the motion of the subject's extremity. The method further includes causing motion of the first target on the display according to a selected trajectory, prompting the subject to perform a tracking task by moving the extremity to track the motion of the first target, with the second target representing the motion of the subject's extremity, and capturing performance data representative of the subject's ability to track the first target. The method further includes determining a tracking metric from the performance data, the tracking metric being indicative of proprioceptive performance of the subject.

Description

SENSOR-BASED REAL-TIME TRACKING GAME (SRT)RELATED APPLICATION

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 665,952, filed on June 28, 2024. The entire teachings of the above application are incorporated herein by reference.BACKGROUND

[0002] Falls are the primary cause of traumatic injury in older adults, and tripping is the leading cause of falls [1-3], A robust method for measuring and improving aging-related proprioceptive deficits (i.e., deficits in perception of muscle / joint position, movement, and tension) is lacking, while strong evidence shows that proprioception deficits are highly associated with poor balance recovery from tripping [4-8],SUMMARY

[0003] Embodiments of methods and systems provided herein relate to a sensor-based approach to measure and improve proprioceptive deficits and reduce the number of preventable falls among the growing older adult population.

[0004] A method of assessing and improving proprioceptive performance in a subject includes measuring motion of an extremity of the subject with an inertial sensing device affixed to the extremity of the subject. The method also includes presenting on a digital display a first target representing an aimpoint for the subject, and a second target representing the motion of the subject’s extremity as measured by the inertial sensing device. The method further includes causing motion of the first target on the digital display according to a selected trajectory, prompting the subject to perform a tracking task by moving the extremity to track the motion of the first target on the digital display with the second target representing the motion of the subject’s extremity, and capturing tracking performance data representative of the subject’s ability to track the motion of the first target with the second target. A tracking metric is determined from the tracking performance data, the tracking metric being indicative of proprioceptive performance of the subject.

[0005] According to an embodiment, the extremity is a lower extremity, e.g., including an ankle joint, and measuring the motion of the extremity includes measuring the angular rotation (e.g., dorsiflexion / plantarflexion, inversion / eversion, abduction / adduction) of theextremity of the subject via the inertial sensing device as the subject moves (e.g., articulates) the extremity. While methods and systems disclosed herein refer to an ankle joint, the methods and systems may also be applicable to any joint such as a knee, shoulder, elbow, wrist, hip or ankle joint.

[0006] Another embodiment includes selecting the trajectory from a group of trajectories having a tiered difficulty. This embodiment includes a low difficulty trajectory comprising a slow speed of movement of the first target, and a small number of direction changes of the first target, a moderate difficulty trajectory comprising a moderate speed of movement of the first target, and a moderate number of direction changes of the first target, and a high difficulty trajectory comprising a fast speed of movement of the first target, and a large number of direction changes of the first target.

[0007] In an embodiment, the tracking metric further includes an assessment of fall risk for the subject.

[0008] According to an embodiment, capturing tracking performance data further includes measuring the angular rotation, angular velocity, and angular acceleration of the extremity, and converting the angular rotation, angular velocity, and angular acceleration into a two-dimensional plane.

[0009] An embodiment further includes performing a calibration procedure prior to prompting the subject. The calibration procedure includes prompting the subject to perform a maximum articulation in a first direction and a maximum articulation in a second direction opposite of the first direction, and identifying a maximum range of possible motion for the subject to be used as a calibration of motion of the first target, e.g., based on the indication of maximum articulation in the first direction and the indication of maximum articulation in the second direction.

[0010] In an embodiment, the range of possible motion, e.g., the maximum range of possible motion identified, is reduced by a predetermined percentage, the reduced range of possible motion defining the maximum boundary of required articulation by the subject during the assessment, e.g. during the tracking task.

[0011] In another embodiment, determining the tracking metric includes determining the absolute distance between the first target and the second target during the duration of the tracking task.

[0012] In another embodiment, capturing the tracking performance data further includes calculating a percentage of time the second target is within a proximity to the first target.

[0013] An embodiment further includes calculating the proximity by utilizing a bell curve that includes data from healthy subjects performing the tracking task and considering any proximity within one or two standard deviations of the data to be considered within a proximity to the first target.

[0014] Another embodiment includes isolating the subject’s extremity movements by restraining a portion, e.g., at least one body segment, of the subject.

[0015] In an embodiment, the inertial sensing device is a gyroscope, motion tracking device, a suitable smart device, a suitable fitness device, or any combination thereof, capable of measuring angle or angular velocity.

[0016] Another embodiment further includes providing visual feedback to the subject on the digital display.

[0017] Another embodiment is directed toward a system for assessing proprioceptive performance in a subject. The system includes a processor, a memory with computer code instructions stored thereon. The processor, a memory with computer code instructions stored thereon are configured to cause the system to measure motion of an extremity of the subject with an inertial sensing device affixed to the extremity of the subject, present on a digital display a first target representing an aimpoint for the subject, and a second target representing the motion of the subject’s extremity as measured by the inertial sensing device, cause motion of the first target on the digital display according to a selected trajectory, prompt the subject to perform a tracking task by moving the extremity to track the motion of the first target on the digital display with the second target representing the motion of the subject’s extremity, capture tracking performance data representative of the subject’s ability to track the motion of the first target with the second target, and determine a tracking metric from the tracking performance data, the tracking metric being indicative of proprioceptive performance of the subject.

[0018] An embodiment further includes an inertial sensing device and a digital display.

[0019] In embodiments of the method or system, the steps of presenting, causing, prompting, capturing, and determining can be repeated over time, to improve proprioceptive performance in the subject.

[0020] Without being bound by a particular theory, repeating the assessment over time is thought to improve proprioceptive performance. This can enable a rehabilitation process that can, for example, be implemented among high fall risk older adults, those with injuries like ankle sprain, and specific diseases like spinal cord injuries.BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The patent or application file contains at least one drawing executed in color.Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.

[0022] The foregoing will be apparent from the following more particular description of example embodiments, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating embodiments.

[0023] FIG. l is a diagram showing example movements of the participant to control an on-screen target via joint movement, according to an embodiment.

[0024] FIGs. 2A - 2C show sensor placement for measuring ankle rotations, horizontal and vertical movement based on rotations around a Y-axis and Z-axis for three task difficulties and the actual tracking information for the sensor, according to an embodiment.

[0025] FIG. 3 is a flow diagram illustrating a method for assessing and improving proprioceptive performance in a subject, according to an embodiment.

[0026] FIG. 4 illustrates a system for assessing and improving proprioceptive performance in a subject, according to an embodiment.

[0027] FIGs. 5A and 5B are graphs showing amplitude accuracy data and a directional accuracy data, respectively, for dominant and non-dominant feet, for young adults and older adults, obtained utilizing embodiments disclosed herein.

[0028] FIGs. 6A and 6B are graphs showing amplitude accuracy data and a directional accuracy data, respectively, for SRT test and re-test.

[0029] FIG. 7 shows a table illustrating example clinical measures to be considered, according to an embodiment.

[0030] FIG. 8 shows an image depicting a JPS test being administered for the ankle joint, according to an embodiment.

[0031] FIG. 9 shows a balance recovery setup testing environment, according to an embodiment.

[0032] FIG. 10 shows a table illustrating a summary of outcome parameters for SRT, joint position test (JPS), postural balance, and balance recovery, according to an embodiment.

[0033] FIG. 11 shows a chart illustrating an application of a personalized SRT intervention utilizing embodiments disclosed herein.

[0034] FIG. 12 is a simplified block diagram of a computer system in which embodiments may be implemented.

[0035] FIG. 13 is a simplified block diagram of a computer network environment in which embodiments may be implemented.DETAILED DESCRIPTION

[0036] A description of example embodiments follows.

[0037] Disclosed herein is a sensor-based approach to measure and improve proprioceptive deficits and reduce the number of preventable falls among the growing older adult population.

[0038] Each year 30% of elderly individuals will experience a fall, which can be attributed to a decline in proprioceptive function due to age. While there are testing regiments that can be used to assess function, most fall into the category of psychophysics and rely on subjective user feedback which can be skewed by conscious motifs. Embodiments disclosed herein relate to a Sensor-based Real-time Tacking-game (SRT), a novel, dynamic, and quantitative means to assess proprioceptive performance. Embodiments use a gyroscope attached to a participant’s ankle and an on-screen program that tasks the user to follow a target, e.g., via ankle movement, around a screen using fine ankle angular movements.

[0039] Further, disclosed herein is evidence of SRT application for improving proprioceptive performance within a 6-week training program, by assessing pre- vs. posttraining balance improvements. These embodiments may be expanded to other joints (e.g., upper-extremity and neck) for several different disease-related applications (e.g., stroke, Huntington’s disease, and diabetes), as well as treatment efficacy assessment (e.g., sprained ankle treatment and knee replacement).

[0040] Proprioceptive feedback from muscle spindles provides information regarding the orientation of the limbs, which activate the parent muscles to restore joint position in a shortlatency reflexive mechanism [9], Proprioceptive feedback from muscle spindles also provides information regarding the orientation of the limbs, which is processed in the central nervous system [10, 11], With aging, the efficacy of muscle spindles declines, due to the natural decline in neural fibers and demyelinization [12-15], leading to a gradual decline in proprioceptive performance

[0016] , Deterioration in proprioceptive performance leads to an elevated risk of fall in older adults

[0017] , Therefore, it is critical to accurately measureproprioceptive performance for identifying high fall risk older adults and to identify those who can potentially benefit from rehabilitation programs targeting proprioceptive deficits.

[0041] Two factors associated with balance recovery deterioration among older adults are delayed placement of the recovery leg and delayed moment generation in the stance leg [4], In both factors, proprioception from the ankle joint muscles has the critical role for feedback (reactive) and feedforward (preparatory) control, and the regulation of muscle stiffness, to achieve specific movement acuity, co-ordination, balance, and eventually a quick and efficient recovery response to balance perturbations [2, 18-20], More recently, it has been argued that although several cardiovascular training exercises exist to enhance strength, flexibility, and balance, research on the independent effects of proprioceptive exercises on balance, especially among high fall risk and institutionalized older adults, remains inadequate

[0021] , Embodiments, i.e., SRT, disclose methods and systems to measure and improve proprioception, thereby providing a feasible tool for high fall risk older adults.

[0042] Embodiments provide adjustable difficulty using sensor-based feedback, applicable for a targeted joint which is practical for older adults who are not able to perform conventional balance trainings.

[0043] Although the importance of assessing and improving ankle proprioception is evident, there are limitations for the current approaches. By implementing sensor-based measurements, embodiments provide an accurate and accessible approach for both assessing and improving proprioceptive performance.

[0044] Most widely used methods for assessing ankle proprioceptive performance are joint position sense (JPS) that actively or passively replicates the ankle joint position based on a previously perceived angle, kinesthesia (i.e., perception of passive movement), and force sense (i.e., replicating a previously perceived ankle moment). These tests involve the subject being tested (referred to as the “participant”) to use information coming from sensory receptors such as muscle spindles and Golgi tendon organs to replicate a certain joint angle, force, or sense passive joint movements

[0022] , Embodiments provide for improvements over legacy platforms that have been said to be not sensitive enough to capture minor deficits in proprioception, not strongly associated with balance performance, are partially subjective, require customized platforms for assessments (e.g., Biodex and robotic devices), and are highly influenced by the attention level of the participant [23-25], Embodiments provide an accurate, reliable, quick, engaging, and standard test, incorporating visuo-proprioceptive sensor-based feedback, without the need for any specific equipment rather than acommercially available gyroscope sensor, for example, available within most smart watch platforms.

[0045] Four categories of proprioceptive trainings exist, including active movement / balance training (e.g., wobble board and Biodex balance training), passive movement (e.g., robotic arms), somatosensory stimulation (e.g., whole body vibration), and meditation (e.g., Tai Chi and Yoga)

[0025] , Several of these measurements require trained staffs, are not applicable for a targeted joint, are expensive, and are often challenging for high fall risk older adults in need of these trainings [25, 26], Further, previous work has shown that active trainings are more effective for enhancing balance in older adults when compared to passive movements

[0025] , Building upon previous research, embodiments are designed to be simple and feasible to perform while sitting for improving ankle proprioceptive performance in high fall risk older adults, which incorporates combined anterior-posterior and medial-lateral maneuvers to replicate real-life sensation and experiences more realistically. Embodiments are accessible, engaging, and user-friendly and may be expandable to a telehealth in-home setup.

[0046] Embodiments provide evidence for implementing SRT, thereby assessing and improving proprioceptive performance. Embodiments discussed herein focus primarily on the ankle joint, but it should be understood that embodiments may be applicable to other joints as well. SRT may incorporate 30-second trials performed by a participant, that involves tracking a flying target presented on a computer screen by moving their ankle joint (with, according to an embodiment, an attached sensor) in the plantarflexion / dorsiflexion (up and down) and abduction / adduction (lateral and medial). (See FIGs.l and 2A-2C, discussed herein below). By measuring the amplitude and directional accuracy outcomes during the tracking, the embodiments engage ankle proprioceptive function based on a correction mechanism of tracking error through the short-latency open-loop reflexive responses, as well as feedback long-latency closed-loop adjustment within the central nervous system [27, 28], Validity of embodiments for measuring proprioceptive performance in comparison with other measures of proprioceptive performance as well as postural and recovery balance performance is discussed hereinbelow. See FIG. 11, discussed hereinbelow). The effectiveness of embodiments at improving balance in the participant has been assessed by testing disclosed herein below.

[0047] An embodiment incorporates a computer processor, and a memory, with computer code instructions stored thereon configured to enable display of SRT testing to theparticipant. For example, the computer processor, with the memory, and the computer code instructions stored thereon, may enable display of the first and second targets on the display, and enable receipt of the angular velocity measurements from an inertial measurement device (IMU), e.g., a gyroscope, affixed to the participant. By integrating the angular velocity measurements, embodiments determine the angular position of the joint (e.g., ankle joint) in both the X-axis and Y-axis and visually represent this position on the screen, via the second target, for the participant to view. The angular velocity of the participant’s foot is recorded in both dorsiflexion / plantarflexion and medial / lateral rotation and show the position of the joint (e.g., ankle joint) via the on-screen target in real time. The equation for determining the angular position, 9, from the angular velocity, co, measurements is shown as:

[0048] FIG. 1 is a diagram showing example movements 100 to control the displayed second target, according to an embodiment. The ankle 101a has three axes of motion, dorsiflexion 103 / plantarflexion 104, medial 107 / lateral 106 rotation, and inversion / eversion of the foot (not shown). For the purpose of SRT, movements 100 utilizes two of these axes, namely, dorsiflexion 103 / plantarflexion 104 and medial 107 / lateral 106 rotation as these have the greatest range of motion for a healthy participant. Further, these provide two axes for which to set as the X- 105 and Y-axes 102 within the computer code instructions associated with embodiments. Dorsiflexion 103 and plantarflexion 104 will contribute to Y-axis 102 motion, while medial 107 and lateral 106 rotation will contribute to X-axis 105 motion.

[0049] In an embodiment, the participant (or a test administrator) may attach a sensor to the extremity, e.g., the foot lOla-b. For example, the participant may be asked to track, on a display, a first target 109 (e.g., a blue circle) by articulating their foot lOla-b. As the participant tracks the first target 109 on the screen, the motion of the participant’s ankle 101a or foot 101b, and hence the tracking, is represented as the second target 108 (e.g., a red circle). To track the first target 109 as it moves in the Y-axis 102, the participant may articulate the foot lOla-b in a dorsiflexion 103 motion to move upwards, or a plantarflexion 104 motion to move downwards. To track the first target 109 as it moves in the X-axis 105, the participant may articulate the foot lOla-b in a lateral 106 motion to move leftward, or a medial 107 motion to move rightward. The ability of the participant to accurately track the first target 109 is recorded and is representative of the participant’s proprioceptive performance.

[0050] FIG. 2 A shows the foot 200 of a participant and a gyroscopic sensor 201 attached to the foot 200 via a strap 203 for measuring ankle rotations, according to an embodiment. While FIG. 2 A shows the gyroscopic sensor 201 attached to the foot 200 of a participant, any sensor capable of returning angular velocity measurements may be utilized attached to any joint of a participant to measure rotations of that joint. FIG. 2A also shows a 3-Dimensional (3D) compass 203 illustrating, in relation to the foot 200, abduction and adduction 204 movements and plantarflexion and dorsiflexion movements 205, respectively.

[0051] FIG. 2B shows a diagram 206 illustrating how the corresponding adduction / ab duction 204 and plantarflexion / dorsiflexion 205 movements of the ankle 200 and thereby the sensor 201 correspond to vertical motion 207 (plantarflexion / dorsiflexion 205) and horizontal movement 208 (abduction / adduction 204), according to an embodiment. For example, the participant would be tasked to angle their foot 200 in a vertical motion 207 and horizontal motion 208, to follow a first target 212a-c around a computer screen (not shown). According to an embodiment, a second target 215a-c represents the current acceleration of the participants tracking, for feedback and reference as they track the first target 212a-c. In an embodiment, there is a tiered difficulty system for the pre-defined track the first target 212a-c takes associated with tasking the participant to track the first target 212a-c around an easy path 209, a medium difficulty path 210, and a hard difficulty path 211.

[0052] FIG. 2C shows a representation 213 of the real-time tracking of a path 214 recorded by a participant attempting to follow the first target, via movement of their ankle, around a path shown to the participant on a screen.

[0053] FIG. 3 is a flow diagram illustrating a method 300 for assessing and improving proprioceptive performance in a subject, according to an embodiment. The method 300 begins at step 301 by measuring motion of an extremity of the subject (e.g., participant) with an inertial sensing device (e.g., gyroscope, motion tracking device, a suitable smart device, a suitable fitness device, or any combination thereof, capable of measuring angle or angular velocity) affixed to the extremity (e.g., ankle) of the subject. In an embodiment, the subject’s extremity movements may be isolated by restraining a portion of the subject. Next, at step 302, the method 300 continues by presenting on a digital display (e.g., a computer screen) a first target representing an aimpoint for the subject, and a second target represent the motion of the subject’s extremity as measured by the inertial sensing device. In an embodiment, visual feedback may be presented to the subject on the digital display. Then, at step 303, the method 300 causes motion of the first target on the digital display according to a selectedtrajectory. In turn, at step 304, the method 300 prompts the subject to perform a tracking task by moving the extremity to track the motion of the first target on the digital display with the second target representing the motion of the subject’s extremity. At step 305, the method 300 continues by capturing tracking performance data representative of the subject’s ability to track the motion of the first target with the second target. Then, at step 306, the method 300 determines a tracking metric from the tracking performance data, the tracking metric being indicative of proprioceptive performance of the subject. In an embodiment, the tracking metric may further include an assessment of fall risk for the subject. According to an embodiment, the measuring at step 301, presenting at step 302, causing at step 303, prompting at step 304, capturing at step 305, and determining at step 306 may be repeated over time to improve proprioceptive performance in the subject.

[0054] According to an embodiment of the method 300, capturing tracking performance data at step 303 may include measuring the angular rotation, angular velocity, and angular acceleration of the extremity, and converting the angular rotation, angular velocity, and angular acceleration into a two-dimensional plane. In an embodiment, the performance data may further include calculating a percentage of time the second target is within a proximity to the first target. According to an embodiment, calculating the proximity may include utilizing a bell curve comprised of data from healthy subjects performing the tracking task and considering any proximity within one or two standard deviations (SD) of the data to be considered within the proximity to the first target.

[0055] According to an embodiment of the method 300, the extremity may be a lower extremity, including an ankle joint, and measuring motion of the extremity at step 301 may include measuring the plantarflexion and dorsiflexion of the extremity of the subject via the inertial sensing device as the subject articulates the extremity.

[0056] In an embodiment of the method 300, the trajectory may be selected from a group of trajectories having a tiered difficulty. An embodiment may include a low difficulty trajectory having a slow speed of movement of the first target, and a small number of direction changes of the first target, a moderate difficulty trajectory having a moderate speed of movement of the first target, and a moderate number of direction changes of the first target, and a high difficulty trajectory comprising a fast speed of movement of the first target, and a large number of direction changes of the first target.

[0057] An embodiment of the method 300 may further include performing a calibration procedure prior to prompting the subject at step 304. The calibration procedure may includeprompting the subject to perform a maximum articulation in a first direction, and a maximum articulation in a second direction opposite of the first direction, identifying a maximum range of possible motion for the subject to be used as a calibration of motion of the first target. In an embodiment, the range of possible motion may be reduced by a predetermined percentage, where the reduced range of possible motion defines the maximum boundary of required articulation by the subject during the assessment.

[0058] In an embodiment of the method 300, determining the tracking metric at step 306 may include determining the absolute distance between the first target and the second target during the duration of the tracking task.

[0059] FIG. 4 shows an illustration of a system 400 for assessing and improving proprioceptive performance in a subject 401, according to an embodiment. For example, the system 400 may include a processor and memory with computer code instructions stored thereon, schematically illustrated in FIG. 4 as computer 405. (See also FIGs. 12 and 13, discussed herein below). While a desktop computer 405 and computer screen display 404 are shown, it should be understood that any type of computing device and display combination may be used, including computing devices with integrated displays, such as, for example, a tablet, a mobile computing device, etc. The system 400 may be configured to measure motion of an extremity, for example, the ankle or foot 403 of a subject 401 with an inertial sensing device 402 affixed to the extremity 403 of the subject 401, while the subject 401 sits in a chair 410. The system 400 may present on a digital display 404 a first target 407a representing an aimpoint for the subject 401 and a second target 407b representing the motion of the subject’s 401 extremity 403 as measured by the inertial sensing device 402. The system 400 may cause motion of the first target 407a on the digital display 404 with the second target 407b representing the motion of the subject’s extremity. The system 400 may capture tracking performance data representative of the subject’s 401 ability to track the motion of the first target 407a with the second target 407b. The system 400 may then determine a tracking metric from the tracking performance data, where the tracking metric is indicative of proprioceptive performance of the subject. The system 400 may be configured to implement any of the embodiments disclosed herein, for example, the method 300 disclosed herein above.

[0060] FIGs. 5A and 5B show an amplitude accuracy graph 500 and a directional accuracy graph 510, respectively, illustrating data obtained utilizing embodiments disclosed herein. In pilot data, 20 young participants (i.e., age = 22+1 years) and five low fall risk olderadult participants (i.e., age = 73+5 years) were recruited. In all participants, their dominant side was their right side. All participants performed the four SRT trials including a full combination of two difficulty levels for two sides. Plot 500 shows amplitude accuracy, comparing the mean distance from the target (in pixels) 501, in a normal 506 and difficult 507 tracking session, for young adults (left foot) 502, for young adults (right foot) 503, older adults (left foot) 504, and older adults (right foot) 505. Plot 510 shows directional accuracy, comparing the percent time in the “free zone” 511, in a normal 516 and difficult 517 tracking session, for young adults (left foot) 512, for young adults (right foot) 513, older adults (left foot) 514, and older adults (right foot) 515. In an embodiment, the “free zone” may be defined for each tracking difficulty using the shape and size of the zone at each instant of time based on one or two standard deviations of distances between the first target and the second target data points collected from healthy young participants results from previous tests. The main observations from plots 500 and 510 are a worse SRT performance in the non-dominant (i.e., left foot in the current sample) foot ( / ?<0.05), within the difficult tracking session 507 and 517 ( / ?<0.01), and, more interesting, among older adults compared to the healthy young group (See FIG. 5A and 5B - / ?<0.001). These initial findings were intriguing as we were able to capture slight differences in dominant versus non-dominant feet performance, as well as age-related difference in proprioceptive performance, within the small sample size.

[0061] FIGs. 6 A and 6B show plots 600 and 610 illustrating amplitude accuracy and directional accuracy, respectively for SRT test and re-test one week apart for eight young participants. To evaluate the reliability of the testing of FIGs. 6 A and 6B, eight of the original healthy adult participants were recruited to return for a secondary test approximately a week after the initial visit. The re-test (i.e., second test 604 and 614) consisted of running all three difficulties (i.e., easy difficulty 209, medium difficulty 210, and hard difficulty 211) of track on each leg. Average distance between testing regimes decreased 9% (p = 0.02) See 600) and directional accuracy increased 8% (p = 0.02) (See 610). Intraclass correlation coefficient (ICC) for the test-retest reliability of embodiments was 0.86 +- 0.01. Plot 600 shows amplitude accuracy, comparing mean distance from the target 601 (in pixels) for each participant 602 for a first test 603 and a second test 604 one week apart from the first test 603. Plot 610 shows directional accuracy, comparing mean distance from the target 611 (in pixels) for each participant 612 for a first test 613 and a second test 614 one week apart from the first test 613. By combining visual feedback and proprioceptive testing, the observed hightest-retest reliability was provided, which is higher on average compared to most reported values for JPS, kinesthesia, and force sense tests in the literature [22, 29] . A consistent improvement in SRT performance in the second testing across participants ( / ?=0.02 for paired t-test, FIGs. 6A and 6B) was observed. SRT for proprioceptive improvement may be further validated using balance tests in this project, discussed herein below (See FIG. 9).

[0062] An example implementation of embodiments disclosed herein is described herein below. For example, 80 older adults may be recruited and stratified into ~40 high fall risk individuals and ~40 low fall risk individuals, based on the Center for Disease Control (CDC) recommended “Stopping Elderly Accidents, Deaths & Injuries” (STEADI) screening [39, 40] STEADI tests may include: (i) fall history, unsteadiness, and fear of falling; (ii) timed-up- and-go; (iii) 30-second chair stand; and (iv) four stage Romberg balance test

[0041] , It is expected that majority of high fall risk, and some low fall risk older adults have proprioceptive deficits. Proprioceptive performance may be assessed using, for example, JPS. The inclusion criteria for this example test may be: (i) age 65 years or older; and (ii) the ability to understand study instructions. The exclusion criteria of this example test may be: (i) disorders associated with severe motor and balance deficits, including stroke, Parkinson’s disease, severe arthritis, lower-extremity amputation, spinal cord pathologies (e.g., spinal stenosis), and diabetes; (ii) history of severe vestibular disorder such as bilateral vestibular hypofunction or poorly-compensated unilateral vestibular hypofunction, or a Dizziness Handicap Inventory (DHI) score > 40; (iii) central nervous disease; (iv) cognitive impairment (e.g., a Montreal Cognitive Assessment (MoCA) score < 26); (v) vision problems including cataract, presbyopia, and similar problems that may influence balance; and (vi) sedating medication or alcohol consumption within 24 hours. With regards to sex considerations, previous studies have reported no significant difference between males and females in terms of aging-related impairments associated with falls and proprioceptive performance [42-44], Nevertheless, equal numbers of males and females should be included in each fall risk group to assure adequate representation of both sexes. The expected recruitment duration of the 80 recruited participants may be, for example, 20 months (-four participants per month). As an example, a recruitment site may be community dwellings.

[0063] FIG. 7 shows a table 700 illustrating a description of example clinical measures for the example implementation described above, according to an embodiment. For example, these clinical measures may be asked to the participants in the form of a questionnaire. These measures may include the following: demographics 701, e.g., age, sex, height, weight,ethnicity, and race; fear of falling 702, e.g., on a Falls Efficacy Scale-International (FES-I)

[0030] ; cognition 703, e.g., based on a MoCA score; comorbidity 704, e.g., Centers for Medicare & Medicaid Services (CMS) Hierarchical Condition Category (HCC) (CMS - HCC)

[0032] ; depression 705, e.g., a patient health questionnaire (PHQ) (e.g., PHQ-9)

[0033] ; pain in legs 706, e.g., via a Visual Analog Scale (VAS)

[0034] ; muscle strength 707, e.g., isometric ankle and hip max movement [35, 36]; ankle function 708, e.g., via a Cumberland Ankle Instability Tool (CAIT)

[0037] ; and vestibular 709, e.g., via DHI

[0038] ,

[0064] According to an embodiment, participant questionnaires may be administered as specified in table 700 of FIG. 7. For example, cognition 703 may be measured as a screening criterion and a covariate; while depression 704, fear of falling 702, lower-extremity pain (e.g., pain in legs) 705, muscle strength 707, and functional ankle 708 instability

[0037] may be measured as covariates, as they are associated with falling and balance [35, 45-50], In an embodiment, the isometric ankle plantar flexion maximum moments (across three measures) may be measured, using, for example, a dynamometer [51, 52]; and DHI

[0038] may be conducted to assess vestibular-related 709 symptoms.

[0065] During SRT, participants may sit on a tall chair to avoid contact between feet and the floor. According to an embodiment, the thigh and shin of the participant’s testing side may be restrained to the chair e.g., using Velcro, to restrain the limbs and limit the tracking to the ankle and not the knee and hip movements. In an embodiment, participants may wear a motion sensor (e.g., tri-axial gyroscope, LEGSys™, BioSensics LLC, Boston, MA, with a sampling frequency = 100Hz) on the testing foot (See FIG. 2A).

[0066] To assure similar exposures, the tracker motion may be calibrated based on the participant’s available range of motion in plantarflexion / dorsiflexion and ab duction / adduction directions, according to an embodiment. For this, participants may rotate the ankle to a maximum range in both relevant directions, and the tracking path may be calibrated to be within 90% of the identified maximum range, which may be defined based on pilot data to provide the most reliable results for embodiments. In an example testing scenario of embodiments disclosed herein, participants may see two targets, a first target (e.g., a blue circle) and a second target (e.g., a red circle), on a display (e.g., a computer screen) positioned, for example, 100 cm away from the participant’s face. In an embodiment, the first target may be derived from SRT software to represent the predefined track for the participant to follow, and the second target may be derived from angular velocity received from the motion sensor affixed to the participant’s foot indicating movement of the joint, e.g., theankle. During testing, only the first and second targets (e.g., the red and blue circles) may be visible on the display, not the trajectories, to avoid prediction of movement by the participants. Embodiments provide for at least three movement pattern difficulties, easy, medium, and hard (See FIG. 2B) that correlate to the number and type of path curvatures and angles, as well as speed of movement of the first target. Embodiments may utilize a custom software allowing for the distance between the first target and the second target to be recorded during the entire test sequence. Participants may repeat each task difficulty two times for each side (total of 12 trials).

[0067] To measure test-retest reliability, participants may repeat the SRT tests in the baseline session once before and once after completing the questionnaires of table 700. This data may be used to assess test-retest reliability of embodiments. The coordinates data (e.g., X-axis: abduction / adduction, Y-axis: plantarflexion / dorsiflexion) may be implemented from the first target (i.e., the predefined track) and second target (i.e., the ankle movement), to extract outcomes, including amplitude accuracy See FIGs. 5A and 6A) and directional accuracy (See FIGs. 5B and 6B) [53, 54], Amplitude accuracy (See FIGs. 5A and 6A) may be measured by calculating the absolute distance (radius) between the first target and the second target during the test sequence. Directional accuracy (See FIGs. 5B and 6B) may be measured by the percentage of the time that the participant keeps the second target within a “free zone” of the first target, ahead of it, or behind it (representing time on target, overshoots, and undershoots). As previously recited, the “free zone” may be defined for each tracking difficulty using the shape and size of the zone at each instant of time based on one or two standard deviations of distances between the first target and the second target data points collected from healthy young participants results from previous tests. A summary of outcomes and definitions are summarized in table 1000 of FIG. 10 discussed herein below.

[0068] FIG. 8 shows a joint position test (JPS) 800 being administered for the ankle joint, according to an embodiment. For example, a JPS test 800 may be administered for the ankle joint 801 since this test 800 may be more reliable, compared to kinesthesia (perception of passive joint movement)

[0055] , In this embodiment, a participant 805 may be tested in a seated posture in a chair 804 while participant’s the thigh is horizontal, and feet are resting on a platform 803 at a neutral position

[0056] , Based on established protocols and previous work [56, 57], an ankle joint 801 may be passively positioned at a targeted angle of, for example, 10° to 15° pl antarfl exion and 10° dorsiflexion in random order for five seconds.Subsequently, the ankle joint 801 may be moved passively to the neutral angle, and then theparticipant 805 may actively move the ankle 801 to the targeted angle. According to an embodiment, angles may be measured using a motion sensor 802 attached to the platform 803. Based previous evidence

[0058] , each angle may be repeated three times for each side to provide reliable JPS outcomes (total of 18 trials). The JPS test 800 outcome is the absolute (and percent) difference between the target and observed angle.

[0069] For postural standing balance testing, a participant may perform two 30-second balance tests with their eyes closed. All trials for postural standing balance may be performed with eyes closed, since previous work indicates that aging-related proprioceptive deficits in balance manifest without visual input [59, 60], In an embodiment, a participant may be prompted to stand upright barefoot with their feet as close together as possible without touching, and their arms crossed. To assess body sway during balance trials, the center of gravity (COG) may be measured using wearable motion sensors following procedures in previous work [61-63], Two sensors may be used, one on the right shin and one on the trunk, each including, according to an embodiment, a tri-axial gyroscope, to estimate ankle and hip angles. A two-link inverted-pendulum model may be used to calculate the COG from anterior-posterior (AP) and medial-lateral (ML) angles of legs (lower link-ankle rotation) and upper-body (upper link-hip rotation) and the participant’s anthropometric data [17, 61], Balance sway outcomes may include ankle and hip sway 1004, COG sway 1005, sway displacement 1006, and sway velocity 1007 (See table 1000).

[0070] FIG. 9 shows a modified treadmill setup 900 that may be used to impose trip-like perturbations [2, 19], according to an embodiment. To avoid an actual fall, the modified treadmill setup 900 may provide a protection harness 901 to prevent knee or hand contact with the treadmill 903. The perturbation may involve a sudden backward movement 904 of the belt (of the treadmill 903) to move the participant’s 905 feet posteriorly and induce a forward loss of balance 906 [19, 64], In response to this perturbation, the participant’s 905 sensorimotor system may execute a reactive stepping 907 to expand the base of support [19, 65], According to an embodiment, body kinematics may be captured using wearable sensors 902; acceleration and angular velocity of shins, thighs, and the trunk may be measured using five sensors (902, not all sensors are shown), to derive reaction and gait parameters using established methods [63, 66-70], Embodiments may measure muscle activity to identify onset for the support and swing limbs during reactive stepping 907, across muscles with dominant involvement

[0071] , including for example, tibialis anterior, peroneus longus, soleus, gastrocnemius, quadriceps, and paraspinals, using surface electromyography.

[0071] According to an embodiment, in each session of the testing using the modified treadmill setup 900, after practicing and warming up twice at a slow treadmill speed, each participant 905 may go through five trials of perturbation, including randomized exposure to two trials of sudden backward belt movement 904 with a max speed of 0.35m / s, two trials of sudden backward belt movement 904 with a max speed of 0.7m / s, and one trial of forward belt movement (not shown) with max speed of 0.2m / s (to minimize the anticipation effect). In each trial the treadmill 903 may reach the max speed in ~40 msec. Treadmill 903 speeds and acceleration may be selected based on pilot data [19, 70], After a successful recovery, participants 905 may walk until they gain their steady-state walking (~20 steps). The order of trials may be randomized to minimize potential fatigue and learning effects.

[0072] Outcomes of this testing may be extracted from backward trials. Failing to recover from the perturbation may be identified if the entire body weight of the participant 905 is supported by the harness 901 [2, 19], Recoveries with integrated weight support greater than 5% of the weight x second may be classified as harness-assisted [2], All other recoveries may be considered successful and may be used for further analysis. The max treadmill 903 speed may be selected to assure older participants 905 can recover successfully

[0019] ; nevertheless, if failure to recovery occurs, the trial may be repeated. Based on pilot testing, less than two trials failed, but if more than two unsuccessful recovery trials occur, the testing may be stopped (new participants 905 may be recruited for replacement). Kinematics outcomes, based on previous work in the same setup, may assess response time 1008, recovery step execution 1009, and lower-extremity motion during recovery

[0070] (See table 1000).Assessment of muscle activity may provide insights regarding the support limb contribution to recovery, in addition to the recovery limb

[0071] , For assessing EMG, raw signal may be band-pass filtered (10-500Hz) and converted to RMS to calculate onsets [72, 73] See table 1000).

[0073] FIG. 10 shows a table 1000 illustrating the summary of all outcomes for SRT, JPS, postural balance, and balance recovery, according to an embodiment. For SRT, the outcomes may be amplitude accuracy 1001, e.g., absolute distance between the predefined track and the tracker, and directional accuracy 1002, e.g., percentage of time that the tracker is inside the free zone of the predefined track. For JPS, the outcome may be angle reproduction accuracy 1003, e.g., the absolute (and percent) difference between the target and the observed ankle angle. For Postural standing balance, the outcomes may be ankle and hip sway 1004, e.g., product of range of rotation in anterior-posterior and medial-lateraldirections; center of gravity (COG) 1005 sway, e.g., product of range of COG sway in anterior-posterior and medial-lateral directions; sway displacement 1006, e.g., total displacement of COG in anterior-posterior and medial-lateral directions; sway velocity 1007, e.g., velocity of COG displacement over the test duration. For balance recover, the outcomes may be reaction time 1008, e.g., time from the onset of treadmill motion to recovery step toe- off; recovery step length 1009, e.g., length of initial step (% of body height); recovery base of support 1010, e.g., distance between center of gravity and the recovery foot at the contact (% of body height); full recovery time 1011, e.g., time to reach steady-state walking (group of six strides with a standard deviation below the median standard deviation); and muscle response onset 1012, e.g., support and swing limbs muscle onset after treadmill motion.

[0074] To determine the association between fall risk and SRT performance, the SRT (and JPS) testing outcomes may be compared as dependent variables between low fall risk and high fall risk older adults, using multivariable repeated measures analysis using mixed effects modeling, considering fall risk groups as between- subject and SRT testing side (left vs. right) and difficulty as within-subject independent variables. Age, sex, and body mass index (BMI) may be considered with significant association with SRT outcomes as covariates. The association between SRT with JPS, postural standing balance, and balance recovery outcomes may be determined using Pearson or Spearman’s rank (based on the distribution of data). To evaluate the test-retest reliability of SRT (and JPS) between two assessments (before and after questionnaire 700 for SRT), intraclass correlation coefficient (ICC) two-way mixed effects F-test models may be used. In all statistical analyses, the False Discovery Rate (FDR) method [74-76], may be used with an expected proportion coefficient of q=0.05 to adjust for multiple comparison [77, 78],

[0075] FIG. 11 shows a chart 1100 illustrating an example application of a personalized SRT intervention utilizing embodiments disclosed herein for improving proprioceptive performance measured by postural and dynamic balance enhancement.

[0076] In the example, 40 high fall risk older adults (wherein, “n” denotes the number of participants) may be recruited to participate in a 6-week training experiment, and 20 may be randomly assigned to the SRT intervention group and 20 may be randomly assigned to the control group.

[0077] Within two days from the baseline session 1101, participants in the intervention group 1102 may undergo the 6-week exercise 1102 series that includes ~5-minutes of SRT training (four unidentical repetitions of an assigned task difficulty for each side (left andright) for a total of eight trials) every other day for a total of 21 sessions. The difficulty of the training may be adjusted every week based on the performance of the prior week. Six ascending difficulty levels for SRT are designed based on the path trajectory and speed of movement of the first target. Once the performance within the last testing session of the week reaches a level equal to mean minus standard error of low fall risk older adults, the difficulty level for the training may be increased to challenge participant throughout the six-week training series. The control group may not receive any intervention. Both the SRT and control groups may receive follow-up 1103 balance performance assessment as disclosed below.

[0078] Both SRT intervention and control groups may perform the postural standing balance and balance recovery assessment, as objective primary endpoints, within two days of their last SRT training session. Balance measurements may be administered the same way as explained above, to determine balance outcomes following the six-week period for each participant.

[0079] Considering the null hypothesis of no difference between the intervention and control groups, the mean values of changes in postural balance and balance recovery outcomes may be compared between the two groups using t-test for normally distributed outcomes. A non-parametric Mann-Whitney U test was used for outcomes that were not normally distributed. In comparing all balance outcomes between the two groups, a False Discovery Rate (FDR) method [74-76] may be used to control the expected proportion of the rejected hypotheses that were falsely rejected, with an expected proportion coefficient of q=0.05 [77, 78],

[0080] Online statistical computing web programming may be used for the generation of a randomized schedule. Further, investigators, for post-processing of the data, may be blinded to the labels of participants (intervention vs. control). To maximize adherence to the intervention program a robust calendar reminder setup may be used that as be applied to participants’ phone at the time of the baseline visit. Each participant may be provided with a tablet and the required sensor setup. Each training session may be quick (~5 minutes) to enhance adherence to the protocol. The training session itself may be simple to perform and participants may be trained at the time of the visit and provided an additional training video on the tablet in case a reminder is required. Any potential missed training sessions may be recorded using date information for each recorded data.

[0081] All major covariates may be considered including age, sex, BMI, (i.e., demographics 701) cognition 703, depression 705, comorbidity 704, fear of falling 702,vestibular disorder 709, and lower-extremity pain 706 and strength 707 and those with severe conditions that can affect their balance were excluded. Post- vs. pre-training balance performances may be compared to minimize the effect of the above confounding variables. Including older adults with aging-related muscular and vestibular deficits may not compromise the main goal of improving proprioceptive deficits among high fall risk older adults. Embodiments provide robust evidence of proprioceptive and balance improvement using SRT.

[0082] Computer Support

[0083] FIG. 12 is a simplified block diagram of a computer-based system 1220 that may be used to assess and improve proprioceptive performance in a subject, according to any variety of embodiments described herein. The system 1220 comprises a bus 1223. The bus 1223 serves as an interconnect between the various components of the system 1220. Connected to the bus 1223 is an input / output device interface 1226 for connecting various input and output devices such as a keyboard, mouse, display, speakers, etc. to the system 1220. A central processing unit (CPU) 1222 is connected to the bus 1223 and provides for the execution of computer instructions implementing embodiments. Memory 1225 provides volatile storage for data used for carrying out computer instructions implementing embodiments described herein. Storage 1224 provides non-volatile storage for software instructions, such as an operating system (not shown) and embodiment configurations, etc. The system 1220 also comprises a network interface 1221 for connecting to any variety of networks known in the art, including wide area networks (WANs) and local area networks (LANs).

[0084] It should be understood that the example embodiments described herein may be implemented in many different ways. In some instances, the various methods and machines described herein may each be implemented by a physical, virtual, or hybrid general purpose computer, such as the computer system 1220, or a computer network environment such as the computer environment 1220, described herein below in relation to FIG. 13. The computer system 1220 may be transformed into the machines that execute the methods described herein, for example, by loading software instructions into either memory 1225 or non-volatile storage 1224 for execution by the CPU 1222. One of ordinary skill in the art should further understand that the system 1220 and its various components may be configured to carry out any embodiments or combination of embodiments described herein. Further, the system 1220 may implement the various embodiments described herein utilizing any combination ofhardware, software, and firmware modules operatively coupled, internally, or externally, to the system 1220. Further, the system 1220 may be communicatively coupled to or be embedded within a manufacturing device so as to control the device to create a physical object with an optimized design as described herein.

[0085] FIG. 13 illustrates a computer network environment 1320 in which an embodiment of the present invention may be implemented. In the computer network environment 1320, the server 1321 is linked through the communications network 1322 to the clients 1323a-n. The environment 1320 may be used to allow the clients 1323a-n, alone or in combination with the server 1321, to execute any of the methods described herein, for example, the method 300 or the system 400, disclosed herein above. For non-limiting example, computer network environment 1320 provides cloud computing embodiments, software as a service (SAAS) embodiments, and the like.

[0086] Embodiments or aspects thereof may be implemented in the form of hardware, firmware, or software. If implemented in software, the software may be stored on any nontransient computer readable medium that is configured to enable a processor to load the software or subsets of instructions thereof. The processor then executes the instructions and is configured to operate or cause an apparatus to operate in a manner as described herein.

[0087] Further, firmware, software, routines, or instructions may be described herein as performing certain actions and / or functions of the data processors. However, it should be appreciated that such descriptions contained herein are merely for convenience and that such actions in fact result from computing devices, processors, controllers, or other devices executing the firmware, software, routines, instructions, etc.

[0088] It should be understood that the flow diagrams, block diagrams, and network diagrams may include more or fewer elements, be arranged differently, or be represented differently. But it further should be understood that certain implementations may dictate the block and network diagrams and the number of block and network diagrams illustrating the execution of the embodiments be implemented in a particular way.

[0089] Accordingly, further embodiments may also be implemented in a variety of computer architectures, physical, virtual, cloud computers, and / or some combination thereof, and thus, the data processors described herein are intended for purposes of illustration only and not as a limitation of the embodiments.

[0090] The teachings of all patents, published applications, appendices and references cited herein are incorporated by reference in their entirety.

[0091] While example embodiments have been particularly shown and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the embodiments encompassed by the appended claims.

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Claims

CLAIMSWhat is claimed is:

1. A method of assessing and improving proprioceptive performance in a subject, the method comprising: measuring motion of an extremity of the subject with an inertial sensing device affixed to the extremity of the subject; presenting on a digital display a first target representing an aimpoint for the subject, and a second target representing the motion of the subject’s extremity as measured by the inertial sensing device; causing motion of the first target on the digital display according to a selected trajectory; prompting the subject to perform a tracking task by moving the extremity to track the motion of the first target on the digital display with the second target representing the motion of the subject’s extremity; capturing tracking performance data representative of the subject’s ability to track the motion of the first target with the second target; and determining a tracking metric from the tracking performance data, the tracking metric being indicative of proprioceptive performance of the subject.

2. The method of Claim 1, wherein the extremity is a lower extremity, including an ankle joint, and measuring motion of the extremity includes measuring the abduction and adduction of the extremity of the subject via the inertial sensing device as the subject moves the extremity.

3. The method of Claim 1 or 2, wherein the extremity is a lower extremity, including an ankle joint, and measuring motion of the extremity includes measuring the plantarflexion and dorsiflexion of the extremity of the subject via the inertial sensing device as the subject moves the extremity.

4. The method of any one of Claims 1 - 3, further comprising selecting the trajectory from a group of trajectories having a tiered difficulty, the group of trajectories comprising:a low difficulty trajectory comprising a slow speed of movement of the first target, and a small number of direction changes of the first target; a moderate difficulty trajectory comprising a moderate speed of movement of the first target, and a moderate number of direction changes of the first target; and a high difficulty trajectory comprising a fast speed of movement of the first target, and a large number of direction changes of the first target.

5. The method of any one of Claims 1 - 4, wherein the tracking metric further comprises an assessment of fall risk for the subject.

6. The method of any one of Claims 1 - 5, wherein capturing tracking performance data further comprises measuring the angular rotation, angular velocity, and angular acceleration of the extremity, and converting the angular rotation, angular velocity, and angular acceleration into a two-dimensional plane.

7. The method of any one of Claims 1 - 6, further comprising performing a calibration procedure prior to prompting the subject, the calibration procedure comprising: prompting the subject to perform a maximum articulation in a first direction, and a maximum articulation in a second direction opposite of the first direction; and identifying a maximum range of possible motion for the subject to be used as a calibration of motion of the first target based on the indication of maximum articulation in the first direction and the indication of maximum articulation in the second direction.

8. The method of Claim 7, further comprising reducing the maximum range of possible motion identified by a predetermined percentage, wherein the maximum range of possible motion reduced defines the maximum boundary of required articulation by the subject during the tracking task.

9. The method of any one of Claims 1 - 8, wherein determining the tracking metric comprises measuring an absolute distance between the first target and the second target during a duration of the tracking task.

10. The method of any one of Claims 1 - 9, wherein capturing the tracking performance data further comprises calculating a percentage of time the second target is within a proximity to the first target.

11. The method of Claim 10, further comprising calculating the proximity by utilizing a bell curve comprised of data from healthy subjects performing the tracking task and considering any proximity within one or two standard deviations of the data to be considered within the proximity to the first target.

12. The method of any one of Claims 1 - 11, further comprising isolating the subject’s extremity movements by restraining a portion of the subject.

13. The method of any one of Claims 1 - 12, wherein the inertial sensing device is a gyroscope, motion tracking device, a suitable smart device, a suitable fitness device, or any combination thereof, capable of measuring angle or angular velocity.

14. The method of any one of Claims 1 - 13, further comprising providing visual feedback to the subject on the digital display.

15. A system for assessing and improving proprioceptive performance in a subject, the system comprising: a processor, and a memory with computer code instructions stored thereon configured to cause the system to: measure motion of an extremity of the subject with an inertial sensing device affixed to the extremity of the subject; present on a digital display a first target representing an aimpoint for the subject, and a second target representing the motion of the subject’s extremity as measured by the inertial sensing device; cause motion of the first target on the digital display according to a selected trajectory; prompt the subject to perform a tracking task by moving the extremity to track the motion of the first target on the digital display with the second target representing the motion of the subject’s extremity; capture tracking performance data representative of the subject’s ability to track the motion of the first target with the second target; anddetermine a tracking metric from the tracking performance data, the tracking metric being indicative of proprioceptive performance of the subject.

16. The system of Claim 15, further comprising the inertial sensing device and the digital display.

17. The system of Claim 15 or 16, wherein the trajectory is selected from a group of trajectories having a tiered difficulty, comprising: a low difficulty trajectory comprising a short overall trace length of the first target, and a small number of direction changes of the first target; a moderate difficulty trajectory comprising a moderate overall trace length of the first target, and a moderate number of direction changes of the first target; and a high difficulty trajectory comprising a long overall trace length of the first target, and a large number of direction changes of the first target.

18. The system of any one of Claims 15 - 17, wherein the processor and the memory with computer code instructions stored thereon are further configured to cause the system to perform a calibration procedure prior to the subject being prompted, the calibration procedure comprising: prompt the subject to perform a maximum articulation in a first direction, and a maximum articulation in a second direction opposite of the first direction; and identify a maximum range of possible motion for the subject to be used as a calibration of motion of the first target based on the indication of maximum articulation in the first direction and the indication of maximum articulation in the second direction.

19. The system of Claim 18, wherein the processor and the memory with computer code instructions stored thereon are further configured to cause the system to reduce the maximum range of possible motion identified by a predetermined percentage, wherein the maximum range of possible motion reduced defines the maximum boundary of required articulation by the subject during the tracking task.

20. The system of any one of Claims 15 - 19, wherein the inertial sensing device is a gyroscope, motion tracking device, a suitable smart device, a suitable fitness device, or any combination thereof, capable of measuring angle or angular velocity.

21. The method of any one of Claims 1 - 14, further comprising repeating over time the measuring, presenting, causing, prompting, capturing, and determining.

22. The system of any one of Claims 15 - 20, wherein the processor, and the memory with computer code instructions stored thereon are further configured to cause the system to repeat over time the measuring, presenting, causing, prompting, capturing, and determining, to improve proprioceptive performance in the subject.

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