Measurement of Functional Use in Upper Extremity Prosthetic Devices Using Wearable Sensors and Machine Learning.

Trials for therapies after an upper limb amputation (ULA) require a focus on the real-world use of the upper limb prosthesis. In this paper, we extend a novel method for identifying upper extremity functional and nonfunctional use to a new patient population: upper limb amputees. We videotaped five amputees and 10 controls performing a series of minimally structured activities while wearing sensors on both wrists that measured linear acceleration and angular velocity. The video data was annotated to provide ground truth for annotating the sensor data. Two different analysis methods were used: one that used fixed-size data chunks to create features to train a Random Forest classifier and one that used variable-size data chunks. For the amputees, the fixed-size data chunk method yielded good results, with 82.7% median accuracy (range of 79.3-85.8) on the 10-fold cross-validation intra-subject test and 69.8% in the leave-one-out inter-subject test (range of 61.4-72.8). The variable-size data method did not improve classifier accuracy compared to the fixed-size method. Our method shows promise for inexpensive and objective quantification of functional upper extremity (UE) use in amputees and furthers the case for use of this method in assessing the impact of UE rehabilitative treatments.

A trade-off between kinematic and dynamic control of bimanual reaching in virtual reality.

Bimanual coordination is an essential component of human movement. Cooperative bimanual reaching tasks are widely used to assess the optimal control of goal-directed reaching. However, little is known about the neuromuscular mechanisms governing these tasks. Twelve healthy, right-handed participants performed a bimanual reaching task in a three-dimensional virtual reality environment. They controlled a shared cursor, located at the midpoint between the hands, and reached targets located at 80% of full arm extension. Following a baseline of normal reaches, we placed a wrist weight on one arm and measured the change in coordination. Relative contribution (RC) was computed as the displacement of the right hand divided by the sum of displacements of both hands. We used surface electromyography placed over the anterior deltoid and biceps brachii to compute muscle contribution (MC) from root mean squared muscle activity data. We found RC was no different than 50% during baseline, indicating participants reached equal displacements when no weights were applied. Participants systematically altered limb coordination in response to altered limb dynamics. RC increased by 0.91% and MC decreased by 5.3% relative to baseline when the weight was applied to the left arm; RC decreased by 0.94% and MC increased by 6.3% when the weight was applied to the right arm. Participants adopted an optimal control strategy that attempted to minimize both kinematic and muscular asymmetries between limbs. What emerged was a trade-off between these two parameters, and we propose this trade-off as a potential neuromuscular mechanism of cooperative bimanual reaching.NEW & NOTEWORTHY This study is the first to propose a trade-off between kinematic and dynamic control parameters governing goal-directed reaching. We propose a straightforward tool to assess this trade-off without the need for computational modeling. The technologies and techniques developed in this study are discussed in the context of upper extremity rehabilitation.

Perceived effort affects choice of limb and reaction time of movements.

The decision regarding which arm to use to perform a task reflects a complex process that can be influenced by many factors, including effort requirements of acquiring the goal. In this study, we considered a virtual reality environment in which people reached to a visual target in three-dimensional space. To vary the cost of reaching, we altered the visual feedback associated with motion of one arm but not the other. This altered the extent of motion that was required to reach, thus changing the effort required to acquire the goal. We then measured how that change in effort affected the decision regarding which arm to use, as well as the preparation time for the movement that ensued. As expected, with increased visual amplification of one arm (reduced effort to reach the goal), subjects increased the probability of choosing that arm. Surprisingly, however, the reaction times to start these movements were also reduced: despite constancy of the visual representation of the target, reaction times were shorter for movements with less effort. Thus, as the perceived effort associated with accomplishing a goal was reduced for a given limb, the decision-making process was biased toward use of that limb. Furthermore, movements that were perceived to be less effortful were performed with shorter reaction times. These results suggest that visual amplification can alter the perceived effort associated with using a limb, thus increasing frequency of use. This may provide a useful method to increase use of a limb during rehabilitation.NEW & NOTEWORTHY We report that visual amplification may serve as an effective means to alter the perceived effort associated with use of a limb. This method may provide an effective tool with which use of the affected limb can be encouraged noninvasively after neurological injury.

Shoulder position and handedness differentially affect excitability and intracortical inhibition of hand muscles.

Individuals with stroke show distinct differences in hand function impairment when the shoulder is in adduction, within the workspace compared to when the shoulder is abducted, away from the body. To better understand how shoulder position affects hand control, we tested the corticomotor excitability and intracortical control of intrinsic and extrinsic hand muscles important for grasp in twelve healthy individuals. Motor evoked potentials (MEP) using single and paired-pulse transcranial magnetic stimulation were elicited in extensor digitorum communis (EDC), flexor digitorum superficialis (FDS), first dorsal interosseous (FDI), and abductor pollicis brevis (APB). The shoulder was fully supported in horizontal adduction (ADD) or abduction (ABD). Separate mixed-effect models were fit to the MEP parameters using shoulder position (or upper-extremity [UE] side) as fixed and participants as random effects. In the non-dominant UE, EDC showed significantly greater MEPs in shoulder ABD than ADD. In contrast, the dominant side EDC showed significantly greater MEPs in ADD compared to ABD; %facilitation of EDC on dominant side showed significant stimulus intensity x position interaction, EDC excitability was significantly greater in ADD at 150% of the resting threshold. Intrinsic hand muscles of the dominant UE received significantly more intracortical inhibition (SICI) when the shoulder was in ADD compared to ABD; there was no position-dependent modulation of SICI on the non-dominant side. Our findings suggest that these resting-state changes in hand muscle excitabilities reflect the natural statistics of UE movements, which in turn may arise from as well as shape the nature of shoulder-hand coupling underlying UE behaviors.

An Elbow Exoskeleton for Upper Limb Rehabilitation with Series Elastic Actuator and Cable-driven Differential.

Movement impairments resulting from neurologic injuries, such as stroke, can be treated with robotic exoskeletons that assist with movement retraining. Exoskeleton designs benefit from low impedance and accurate torque control. We designed a 2 degree-of-freedom tethered exoskeleton that can provide independent torque control on elbow flexion/extension and forearm supination/pronation. Two identical series elastic actuators (SEAs) are used to actuate the exoskeleton. The two SEAs are coupled through a novel cable-driven differential. The exoskeleton is compact and lightweight, with a mass of 0.9 kg. Applied RMS torque errors were less than 0.19 Nm. Benchtop tests demonstrated a torque rise time of approximately 0.1 s, a torque control bandwidth of 3.7 Hz and an impedance of less than 0.03 Nm/deg at 1 Hz. The controller can simulate a stable maximum wall stiffness of 0.45 Nm/deg. The overall performance is adequate for robotic therapy applications and the novelty of the design is discussed.

Pilot testing of the spring operated wearable enhancer for arm rehabilitation (SpringWear).

BACKGROUND: Robotic devices for neurorehabilitation of movement impairments in persons with stroke have been studied extensively. However, the vast majority of these devices only allow practice of stereotyped components of simulated functional tasks in the clinic. Previously we developed SpringWear, a wearable, spring operated, upper extremity exoskeleton capable of assisting movements during real-life functional activities, potentially in the home. SpringWear assists shoulder flexion, elbow extension and forearm supination/pronation. The assistance profiles were designed to approximate the torque required to move the joint passively through its range. These three assisted DOF are combined with two passive shoulder DOF, allowing complex multi-joint movement patterns. METHODS: We performed a cross-sectional study to assess changes in movement patterns when assisted by SpringWear. Thirteen persons with chronic stroke performed range of motion (ROM) and functional tasks, including pick and place tasks with various objects. Sensors on the device measured rotation at all 5 DOF and a kinematic model calculated position of the wrist relative to the shoulder. Within subject t-tests were used to determine changes with assistance from SpringWear. RESULTS: Maximum shoulder flexion, elbow extension and forearm pronation/supination angles increased significantly during both ROM and functional tasks (p < 0.002). Elbow flexion/extension ROM also increased significantly (p < 0.001). When the subjects volitionally held up the arm against gravity, extension at the index finger proximal interphalangeal joint increased significantly (p = 0.033) when assisted by SpringWear. The forward reach workspace increased 19% (p = 0.002). Nine subjects could not complete the functional tasks unassisted and only one showed improvement on task completion with SpringWear. CONCLUSIONS: SpringWear increased the usable workspace during reaching movements, but there was no consistent improvement in the ability to complete functional tasks. Assistance levels at the shoulder were increased only until the shoulder could be voluntarily held at 90 degrees of flexion. A higher level of assistance may have yielded better results. Also combining SpringWear with HandSOME, an exoskeleton for assisting hand opening, may yield the most dramatic improvements in functional task performance. These low-cost devices can potentially reduce effort and improve performance during task practice, increasing adherence to home training programs for rehabilitation.

Neural coupling between homologous muscles during bimanual tasks: effects of visual and somatosensory feedback.

While the effects of sensory feedback on bimanual tasks have been studied extensively at two ends of the motor control hierarchy, the cortical and behavioral levels, much less is known about how it affects the intermediate levels, including neural control of homologous muscle groups. We investigated the effects of somatosensory input on the neural coupling between homologous arm muscles during bimanual tasks. Twelve subjects performed symmetric elbow flexion/extension tasks under different types of sensory feedback. The first two types involve visual feedback, with one imposing stricter force symmetry than the other. The third incorporated somatosensory feedback via a balancing apparatus that forced the two limbs to produce equal force levels. Although the force error did not differ between feedback conditions, the somatosensory feedback significantly increased temporal coupling of bilateral force production, indicated by a high correlation between left/right force profiles (P < 0.001). More importantly, intermuscular coherence between biceps brachii muscles was significantly higher with somatosensory feedback than others (P = 0.001). Coherence values also significantly differed between tasks (flexion/extension). Notably, whereas feedback type mainly modulated coherence in the α- and γ-bands, task type only affected ß-band coherence. Similar feedback effects were observed for triceps brachii muscles, but there was also a strong phase effect on the coherence values (P < 0.001) that could have diluted feedback effects. These results suggest that somatosensory feedback can significantly increase neural coupling between homologous muscles. Additionally, the between-task difference in ß-band coherence may reflect different neural control strategies for the elbow flexor and extensor muscles. NEW & NOTEWORTHY: This study investigated the effects of somatosensory feedback during bimanual tasks on the neural coupling between arm muscles, which remains largely unexplored. Somatosensory feedback using a balancing apparatus, compared with visual feedback, significantly increased neural coupling between homologous muscles (indicated by intermuscular coherence values) and improved temporal correlation of bilateral force production. Notably, feedback type modulated coherence in the α- and γ-bands (more subcortical pathways), whereas task type mainly affected ß-band coherence (corticospinal pathway).

Dynamic motor tracking is sensitive to subacute mTBI.

Effective screening for mild traumatic brain injury (mTBI) is critical to accurate diagnosis, intervention, and improving outcomes. However, detecting mTBI using conventional clinical techniques is difficult, time intensive, and subject to observer bias. We examine the use of a simple visuomotor tracking task as a screening tool for mTBI. Thirty participants, 16 with clinically diagnosed mTBI (mean time since injury: 36.4 ± 20.9 days (95 % confidence interval); median = 20 days) were asked to squeeze a hand dynamometer and vary their grip force to match a visual, variable target force for 3 min. We found that controls outperformed individuals with mTBI; participants with mTBI moved with increased variability, as quantified by the standard deviation of the tracking error. We modeled participants' feedback response-how participants changed their grip force in response to errors in position and velocity-and used model parameters to classify mTBI with a sensitivity of 87 % and a specificity of 93 %, higher than several standard clinical scales. Our findings suggest that visuomotor tracking could be an effective supplement to conventional assessment tools to screen for mTBI and track mTBI symptoms during recovery.

Using Wearable Sensors and Machine Learning Models to Separate Functional Upper Extremity Use From Walking-Associated Arm Movements.

OBJECTIVE: To improve measurement of upper extremity (UE) use in the community by evaluating the feasibility of using body-worn sensor data and machine learning models to distinguish productive prehensile and bimanual UE activity use from extraneous movements associated with walking. DESIGN: Comparison of machine learning classification models with criterion standard of manually scored videos of performance in UE prosthesis users. SETTING: Rehabilitation hospital training apartment. PARTICIPANTS: Convenience sample of UE prosthesis users (n=5) and controls (n=13) similar in age and hand dominance (N=18). INTERVENTIONS: Participants were filmed executing a series of functional activities; a trained observer annotated each frame to indicate either UE movement directed at functional activity or walking. Synchronized data from an inertial sensor attached to the dominant wrist were similarly classified as indicating either a functional use or walking. These data were used to train 3 classification models to predict the functional versus walking state given the associated sensor information. Models were trained over 4 trials: on UE amputees and controls and both within subject and across subject. Model performance was also examined with and without preprocessing (centering) in the across-subject trials. MAIN OUTCOME MEASURE: Percent correct classification. RESULTS: With the exception of the amputee/across-subject trial, at least 1 model classified >95% of test data correctly for all trial types. The top performer in the amputee/across-subject trial classified 85% of test examples correctly. CONCLUSIONS: We have demonstrated that computationally lightweight classification models can use inertial data collected from wrist-worn sensors to reliably distinguish prosthetic UE movements during functional use from walking-associated movement. This approach has promise in objectively measuring real-world UE use of prosthetic limbs and may be helpful in clinical trials and in measuring response to treatment of other UE pathologies.

Proximal arm kinematics affect grip force-load force coordination.

During object manipulation, grip force is coordinated with load force, which is primarily determined by object kinematics. Proximal arm kinematics may affect grip force control, as proximal segment motion could affect control of distal hand muscles via biomechanical and/or neural pathways. The aim of this study was to investigate the impact of proximal kinematics on grip force modulation during object manipulation. Fifteen subjects performed three vertical lifting tasks that involved distinct proximal kinematics (elbow/shoulder), but resulted in similar end-point (hand) trajectories. While temporal coordination of grip and load forces remained similar across the tasks, proximal kinematics significantly affected the grip force-to-load force ratio (P = 0.042), intrinsic finger muscle activation (P = 0.045), and flexor-extensor ratio (P < 0.001). Biomechanical coupling between extrinsic hand muscles and the elbow joint cannot fully explain the observed changes, as task-related changes in intrinsic hand muscle activation were greater than in extrinsic hand muscles. Rather, between-task variation in grip force (highest during task 3) appears to contrast to that in shoulder joint velocity/acceleration (lowest during task 3). These results suggest that complex neural coupling between the distal and proximal upper extremity musculature may affect grip force control during movements, also indicated by task-related changes in intermuscular coherence of muscle pairs, including intrinsic finger muscles. Furthermore, examination of the fingertip force showed that the human motor system may attempt to reduce variability in task-relevant motor output (grip force-to-load force ratio), while allowing larger fluctuations in output less relevant to task goal (shear force-to-grip force ratio).

Internal models of upper limb prosthesis users when grasping and lifting a fragile object with their prosthetic limb.

Internal models allow unimpaired individuals to appropriately scale grip force when grasping and lifting familiar objects. In prosthesis users, the internal model must adapt to the characteristics of the prosthetic devices and reduced sensory feedback. We studied the internal models of 11 amputees and eight unimpaired controls when grasping and lifting a fragile object. When the object was modified from a rigid to fragile state, both subject groups adapted appropriately by significantly reducing grasp force on the first trial with the fragile object compared to the rigid object (p < 0.020). There was a wide range of performance skill illustrated by amputee subjects when lifting the fragile object in 10 repeated trials. One subject, using a voluntary close device, never broke the object, four subjects broke the fragile device on every attempt and seven others failed on their initial attempts, but improved over the repeated trials. Amputees decreased their grip forces 51 ± 7 % from the first to the last trial (p < 0.001), indicating a practice effect. However, amputees used much higher levels of force than controls throughout the testing (p < 0.015). Amputees with better performance on the Box and Blocks test used lower grip force levels (p = 0.006) and had more successful lifts of the fragile object (p = 0.002). In summary, amputees do employ internal models when picking up objects; however, the accuracy of these models is poor and grip force modulation is significantly impaired. Further studies could examine the alternative sensory modalities and training parameters that best promote internal model formation.

Responsiveness to exoskeleton loading during bimanual reaching is associated with corticospinal tract integrity in stroke.

Background: Device-based rehabilitation of upper extremity impairment following stroke often employs one-sized-fits-all approaches that do not account for individual differences in patient characteristics. Objective: Determine if corticospinal tract lesion load could explain individual differences in the responsiveness to exoskeleton loading of the arms in chronic stroke participants. Methods: Fourteen stroke participants performed a bimanual shared cursor reaching task in virtual reality while exoskeletons decreased the effective weight of the more-impaired arm and increased the effective weight of the less-impaired arm. We calculated the change in relative displacement between the arms (RC) and the change in relative muscle activity (MC) between the arms from the biceps and deltoids. We calculated corticospinal tract lesion load (wCSTLL) in a subset of 10 participants. Results: Exoskeleton loading did not change RC (p = 0.07) or MC (p = 0.47) at the group level, but significant individual differences emerged. Participants with little overlap between the lesion and corticospinal tract responded to loading by decreasing muscle activity in the more-impaired arm relative to the less-impaired arm. The change in deltoid MC was associated with smaller wCSTLL (R2 = 0.43, p = 0.039); there was no such relationship for biceps MC (R2 < 0.001, p = 0.98). Conclusion: Here we provide evidence that corticospinal tract integrity is a critical feature that determines one's ability to respond to upper extremity exoskeleton loading. Our work contributes to the development of personalized device-based interventions that would allow clinicians and researchers to titrate constraint levels during bimanual activities.

Cortical effects of repetitive finger flexion- vs. extension-resisted tracking movements: a TMS study.

While the cortical effects of repetitive motor activity are generally believed to be task specific, the task parameters that modulate these effects are incompletely understood. Since there are differences in the neural control of flexor vs. extensor muscles, the type of muscles involved in the motor task of interest may be one important parameter. In addition, the role each muscle plays in the task, such as whether or not it is the prime mover, is another potentially important task parameter. In the present study, use-dependent cortical plasticity was examined in healthy volunteers performing a robotic waveform tracking task with either the extensor digitorum communis (EDC) or flexor digitorum superficialis (FDS) acting as the prime mover. Transcranial magnetic stimulation was used to measure corticospinal excitability (CE) and short-interval intracortical inhibition of lower and higher threshold corticospinal neurons (SICI(L) and SICI(H), respectively) before and after a flexion- or extension-resisted finger tracking task. After repetitive performance of the tracking task, there was a significant decrease in SICI(L) targeting the EDC, while no change in CE targeting EDC was observed. In contrast, the reverse pattern was observed in the FDS: a significant increase in CE with no change in SICI(L). There was also a tendency toward increased SICI(H) targeting whichever muscle was acting as the prime mover, although this effect did not reach statistical significance. We conclude that there is a difference in patterns of use-dependent plasticity between extrinsic finger flexor and extensor muscles performing the same task.

Concurrent neuromechanical and functional gains following upper-extremity power training post-stroke.

BACKGROUND: Repetitive task practice is argued to drive neural plasticity following stroke. However, current evidence reveals that hemiparetic weakness impairs the capacity to perform, and practice, movements appropriately. Here we investigated how power training (i.e., high-intensity, dynamic resistance training) affects recovery of upper-extremity motor function post-stroke. We hypothesized that power training, as a component of upper-extremity rehabilitation, would promote greater functional gains than functional task practice without deleterious consequences. METHOD: Nineteen chronic hemiparetic individuals were studied using a crossover design. All participants received both functional task practice (FTP) and HYBRID (combined FTP and power training) in random order. Blinded evaluations performed at baseline, following each intervention block and 6-months post-intervention included: Wolf Motor Function Test (WMFT-FAS, Primary Outcome), upper-extremity Fugl-Meyer Motor Assessment, Ashworth Scale, and Functional Independence Measure. Neuromechanical function was evaluated using isometric and dynamic joint torques and concurrent agonist EMG. Biceps stretch reflex responses were evaluated using passive elbow stretches ranging from 60 to 180º/s and determining: EMG onset position threshold, burst duration, burst intensity and passive torque at each speed. PRIMARY OUTCOME: Improvements in WMFT-FAS were significantly greater following HYBRID vs. FTP (p = .049), regardless of treatment order. These functional improvements were retained 6-months post-intervention (p = .03). SECONDARY OUTCOMES: A greater proportion of participants achieved minimally important differences (MID) following HYBRID vs. FTP (p = .03). MIDs were retained 6-months post-intervention. Ashworth scores were unchanged (p > .05). Increased maximal isometric joint torque, agonist EMG and peak power were significantly greater following HYBRID vs. FTP (p < .05) and effects were retained 6-months post-intervention (p's < .05). EMG position threshold and burst duration were significantly reduced at fast speeds (≥120º/s) (p's < 0.05) and passive torque was reduced post-washout (p < .05) following HYBRID. CONCLUSIONS: Functional and neuromechanical gains were greater following HYBRID vs. FPT. Improved stretch reflex modulation and increased neuromuscular activation indicate potent neural adaptations. Importantly, no deleterious consequences, including exacerbation of spasticity or musculoskeletal complaints, were associated with HYBRID. These results contribute to an evolving body of contemporary evidence regarding the efficacy of high-intensity training in neurorehabilitation and the physiological mechanisms that mediate neural recovery.

Concurrent validity of machine learning-classified functional upper extremity use from accelerometry in chronic stroke.

Objective: This study aims to investigate the validity of machine learning-derived amount of real-world functional upper extremity (UE) use in individuals with stroke. We hypothesized that machine learning classification of wrist-worn accelerometry will be as accurate as frame-by-frame video labeling (ground truth). A second objective was to validate the machine learning classification against measures of impairment, function, dexterity, and self-reported UE use. Design: Cross-sectional and convenience sampling. Setting: Outpatient rehabilitation. Participants: Individuals (>18 years) with neuroimaging-confirmed ischemic or hemorrhagic stroke >6-months prior (n = 31) with persistent impairment of the hemiparetic arm and upper extremity Fugl-Meyer (UEFM) score = 12-57. Methods: Participants wore an accelerometer on each arm and were video recorded while completing an "activity script" comprising activities and instrumental activities of daily living in a simulated apartment in outpatient rehabilitation. The video was annotated to determine the ground-truth amount of functional UE use. Main outcome measures: The amount of real-world UE use was estimated using a random forest classifier trained on the accelerometry data. UE motor function was measured with the Action Research Arm Test (ARAT), UEFM, and nine-hole peg test (9HPT). The amount of real-world UE use was measured using the Motor Activity Log (MAL). Results: The machine learning estimated use ratio was significantly correlated with the use ratio derived from video annotation, ARAT, UEFM, 9HPT, and to a lesser extent, MAL. Bland-Altman plots showed excellent agreement between use ratios calculated from video-annotated and machine-learning classification. Factor analysis showed that machine learning use ratios capture the same construct as ARAT, UEFM, 9HPT, and MAL and explain 83% of the variance in UE motor performance. Conclusion: Our machine learning approach provides a valid measure of functional UE use. The accuracy, validity, and small footprint of this machine learning approach makes it feasible for measurement of UE recovery in stroke rehabilitation trials.

Evolution of a System to Monitor Infant Neuromotor Development in the Home: Lessons from COVID-19.

In the nine months leading up to COVID-19, our biomedical engineering research group was in the very early stages of development and in-home testing of HUGS, the Hand Use and Grasp Sensor (HUGS) system. HUGS was conceived as a tool to allay parents' anxiety by empowering them to monitor their infants' neuromotor development at home. System focus was on the evolving patterns of hand grasp and general upper extremity movement, over time, in the naturalistic environment of the home, through analysis of data captured from force-sensor-embedded toys and 3D video as the baby played. By the end of March, 2020, as the COVID-19 pandemic accelerated and global lockdown ensued, home visits were no longer possible and HUGS system testing ground to an abrupt halt. In the spring of 2021, still under lockdown, we were able to resume recruitment and in-home testing with HUGS-2, a system whose key requirement was that it be contactless. Participating families managed the set up and use of HUGS-2, supported by a detailed library of video materials and virtual interaction with the HUGS team for training and troubleshooting over Zoom. Like the positive/negative poles of experience reported by new parents under the isolation mandated to combat the pandemic, HUGS research was both impeded and accelerated by having to rely solely on distance interactions to support parents, troubleshoot equipment, and securely transmit data. The objective of this current report is to chronicle the evolution of HUGS. We describe a system whose design and development straddle the pre- and post-pandemic worlds of family-centered health technology design. We identify and classify the clinical approaches to infant screening that predominated in the pre-COVID-19 milieu and describe how these procedural frameworks relate to the family-centered conceptualization of HUGS. We describe how working exclusively through the proxy of parents revealed the family's priorities and goals for child interaction and surfaced HUGS design shortcomings that were not evident in researcher-managed, in-home testing prior to the pandemic.

Characterization of compensatory trunk movements during prosthetic upper limb reaching tasks.

OBJECTIVE: To characterize the compensatory movements of the trunk during functional reaching tasks performed by upper limb prosthesis users. DESIGN: Survey. SETTING: Clinical laboratory at a national rehabilitation hospital. PARTICIPANTS: Transhumeral and transradial prosthesis users (n=10) and uninjured control subjects (n=10). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Three-dimensional motion analysis data were collected during simulated reaching tasks, such as donning a cap, placing a nut, and sorting clothes. The metrics were range of motion of the trunk in the 3 anatomical directions and elbow and shoulder path distance. RESULTS: Prosthesis users had significantly larger truncal movements than controls during all 3 reaching tasks in all 3 directions (P≤.03). Shoulder path distance in persons with amputation was larger than in controls in all 3 tasks (P<.01). Elbow path distance in persons with amputation was larger than in controls in the nut and clothes tasks (P≤.02). The subgroup of transradial prosthesis users displayed these abnormal movements despite the presence of an intact elbow. CONCLUSIONS: The altered physiologic structure of the arm caused the individuals to develop a different motor control strategy than an intact arm. Functional limitations, such as the loss of distal degrees of freedom, required persons with amputation to use trunk displacement in place of arm/hand movement. These compensatory movements during reaching tasks may be a cause of prosthesis rejection and, in some cases, may be resolved with proper rehabilitative training. Analysis of compensatory trunk movements may also provide a useful endpoint for evaluating new prosthesis designs.

Hand Use and Grasp Sensor System in Monitoring Infant Fine Motor Development.

Objective: To assess the feasibility of a hand use and grasp sensor system in collecting and quantifying fine motor development longitudinally in an infant's home environment. Design: Cohort study. Researchers made home visits monthly to participating families to collect grasp data from infants using a hand use and grasp sensor. Setting: Data collection were conducted in each participant's home. Participants: A convenience sample of 14 typical developmental infants were enrolled from 3 months to 9 months of age. Two infants dropped out. A total of 62 testing sessions involving 12 infants were available for analysis (N=12). Interventions: At each session, the infant was seated in a standardized infant seat. Each instrumented toy was hung on the hand use and grasp sensor structure, presented for 6 minutes in 3 feedback modes: visual, auditory, and vibratory. Main Outcome Measures: Infant grasp frequency and duration, peak grasping force, average grasping force, force coefficient of variation, and proportion of bimanual grasps. Results: A total of 2832 recorded grasp events from 12 infants were analyzed. In linear mixed-effects model analysis, when interacting with each toy, infants' peak grasp force, average grasp force, and accumulated grasp time all increased significantly with age (all P<.001). Bimanual grasps also occupied an increasingly greater percentage of infants' total grasps as they grew older (bar toy P<.001, candy toy P=.021). Conclusions: We observed significant changes in hand use and grasp sensor outcome measures with age that are consistent with maturation of grasp skills. We envision the evolution of hand use and grasp sensor technology into an inexpensive and convenient tool to track infant grasp development for early detection of possible developmental delay and/or cerebral palsy as a supplement to clinical evaluations.

A tracking device for a wearable high-DOF passive hand exoskeleton.

In previous work, we developed an exoskeleton (HandSOME II) that allows movement at 15 hand degrees of freedom (DOF) and is intended for take-home use. An activity tracking device was developed in order to track index finger movement with a pair of magnetometers and magnet. The goal was to detect grip attempts by the individual. Machine learning was utilized to estimate angles for metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints at the index finger. Testing was performed with healthy control and individuals with stroke.Clinical Relevance- This device and method of data collection during daily activities might be useful for stroke rehabilitation and compliance with home-based therapy programs.

Clinical Test of a Wearable, High DOF, Spring Powered Hand Exoskeleton (HandSOME II).

In previous work, we developed an exoskeleton, Hand Spring Operated Movement Enhancer (HandSOME II), that allows movement at 15 hand degrees of freedom (DOF). Eleven separate elastic elements can be added to customize the extension assistance for individuals with impaired hand function. In this pilot study of twelve individuals with stroke, we measured the immediate improvements in range of motion (ROM) and upper extremity function when wearing the device. Index finger ROM was significantly improved at the PIP (p=.01) and DIP joints (p=.026), and the max extension was significantly increased at the MCP (p<.001), PIP (p=.013) and DIP joints (p=.016). The thumb CMC abduction max (p=.017) and CMC flexion/extension ROM also increased (p=.04). In a grip and release task involving various objects, six subjects were unable to complete the tasks without assistance. Across these 6 subjects, 13 of 42 tasks were completed without assistance, while 36 of 42 tasks were completed when wearing HandSOME II. Despite the extension assistance provided by the device, flexion grip force was not statistically decreased. HandSOME II can potentially increase the effectiveness of repetitive task practice in patients with moderate-severe hand impairment by allowing completion of grasp and release tasks that are impossible to complete unassisted.