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.

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.

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.

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.

Estimating infant upper extremities motion with an RGB-D camera and markerless deep neural network tracking: A validation study

Quantitative biomarkers of infant motion may be predictive of the development of movement disorders. This study presents and validates a low cost, markerless motion tracking method for the estimation of upper body kinematics of infants from which proper biomarkers may be extracted. The method requires a single RGB-D camera, a 2D motion tracking software publicly available (DeepLabCut) and an algorithm generating 3D point coordinates from the 2D tracked points, dealing with missing data, originating from various sources, for estimating joint kinematics. The proposed method is validated using known point kinematics obtained from a doll, with size and shape of an infant, lying on a turntable rotating at 33⅓ rpm. Two camera image plane orientations are tested: parallel to the turntable motion plane and forming a 45° angle with respect to the motion plane. The latter enhances the occurrence of body parts occlusions during motion as expected in live infant motion recordings. The length of upper body segments, elbow and shoulder joint angles and the linear point velocity determined with the proposed method are evaluated against reference values obtained from the known motion of the turntable. The relevant Mean Absolute Errors (MAE) found indicate the margin of error to expect when processing live infant motion. The proposed method may be improved if enhanced hardware and tracking software are employed, therefore reducing the above-mentioned margin of error. Clinical Relevance - The validation of the proposed method carried out in this study allows clinicians to select proper quantitative biomarkers obtained from infants upper body motion that may be useful for predicting movement disorders.

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.

Home-Based Therapy After Stroke Using the Hand Spring Operated Movement Enhancer (HandSOME II)

We have developed a passive and lightweight wearable hand exoskeleton (HandSOME II) that improves range of motion and functional task practice in laboratory testing. For this longitudinal study, we recruited 15 individuals with chronic stroke and asked them to use the device at home for 1.5 h per weekday for 8 weeks. Subjects visited the clinic once per week to report progress and troubleshoot problems. Subjects were then given the HandSOME II for the next 3 months, and asked to continue to use it, but without any scheduled contact with the project team. Clinical evaluations and biomechanical testing was performed before and after the 8 week intervention and at the 3 month followup. EEG measures were taken before and after the 8 weeks of training to examine any recovery associated brain reorganization. Ten subjects completed the study. After 8 weeks of training, functional ability (Action Research Arm Test), flexor tone (Modified Ashworth Test), and real world use of the impaired limb (Motor Activity Log) improved significantly (p < 0.05). Gains in real world use were retained at the 3-month followup (p = 0.005). At both post-training and followup time points, biomechanical testing found significant gains in finger ROM and hand displacement in a reaching task (p < 0.05). Baseline functional connectivity correlated with gains in motor function, while changes in EEG functional connectivity paralleled changes in motor recovery. HandSOME II is a low-cost, home-based intervention that elicits brain plasticity and can improve functional motor outcomes in the chronic stroke population.

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.

Pilot Test of Dosage Effects in HEXORR II for Robotic Hand Movement Therapy in Individuals With Chronic Stroke

Impaired use of the hand in functional tasks remains difficult to overcome in many individuals after a stroke. This often leads to compensation strategies using the less-affected limb, which allows for independence in some aspects of daily activities. However, recovery of hand function remains an important therapeutic goal of many individuals, and is often resistant to conventional therapies. In prior work, we developed HEXORR I, a robotic device that allows practice of finger and thumb movements with robotic assistance. In this study, we describe modifications to the device, now called HEXORR II, and a clinical trial in individuals with chronic stroke. Fifteen individuals with a diagnosis of chronic stroke were randomized to 12 or 24 sessions of robotic therapy. The sessions involved playing several video games using thumb and finger movement. The robot applied assistance to extension movement that was adapted based on task performance. Clinical and motion capture evaluations were performed before and after training and again at a 6-month followup. Fourteen individuals completed the protocol. Fugl-Meyer scores improved significantly at the 6 month time point compared to baseline, indicating reductions in upper extremity impairment. Flexor hypertonia (Modified Ashworth Scale) also decreased significantly due to the intervention. Motion capture found increased finger range of motion and extension ability after the intervention that continued to improve during the followup period. However, there was no change in a functional measure (Action Research Arm Test). At the followup, the high dose group had significant gains in hand displacement during a forward reach task. There were no other significant differences between groups. Future work with HEXORR II should focus on integrating it with functional task practice and incorporating grip and squeezing tasks.

Trial Registration:ClinicalTrials.gov, NCT04536987. Registered 3 September 2020 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/record/NCT04536987.

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.

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.

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.

Improving Accelerometry-Based Measurement of Functional Use of the Upper Extremity After Stroke: Machine Learning Versus Counts Threshold Method

BACKGROUND

Wrist-worn accelerometry provides objective monitoring of upper-extremity functional use, such as reaching tasks, but also detects nonfunctional movements, leading to ambiguity in monitoring results.

OBJECTIVE

Compare machine learning algorithms with standard methods (counts ratio) to improve accuracy in detecting functional activity.

METHODS

Healthy controls and individuals with stroke performed unstructured tasks in a simulated community environment (Test duration = 26 ± 8 minutes) while accelerometry and video were synchronously recorded. Human annotators scored each frame of the video as being functional or nonfunctional activity, providing ground truth. Several machine learning algorithms were developed to separate functional from nonfunctional activity in the accelerometer data. We also calculated the counts ratio, which uses a thresholding scheme to calculate the duration of activity in the paretic limb normalized by the less-affected limb.

RESULTS

The counts ratio was not significantly correlated with ground truth and had large errors (r = 0.48; P = .16; average error = 52.7%) because of high levels of nonfunctional movement in the paretic limb. Counts did not increase with increased functional movement. The best-performing intrasubject machine learning algorithm had an accuracy of 92.6% in the paretic limb of stroke patients, and the correlation with ground truth was r = 0.99 (P < .001; average error = 3.9%). The best intersubject model had an accuracy of 74.2% and a correlation of r =0.81 (P = .005; average error = 5.2%) with ground truth.

CONCLUSIONS

In our sample, the counts ratio did not accurately reflect functional activity. Machine learning algorithms were more accurate, and future work should focus on the development of a clinical tool.

HandMATE: Wearable Robotic Hand Exoskeleton and Integrated Android App for At Home Stroke Rehabilitation

We have developed HandMATE (Hand Movement Assisting Therapy Exoskeleton); a wearable motorized hand exoskeleton for home-based movement therapy following stroke. Each finger and the thumb is powered by a linear actuator which provides flexion and extension assistance. Force sensitive resistors integrated into the design measure grasp and extension initiation force. An assistive therapy mode is based on an admittance control strategy. We evaluated our control system via subject and bench testing. Errors during a grip force tracking task while using the HandMATE were minimal (<1%) and comparable to unassisted healthy hand performance. We also outline a dedicated app we have developed for optimal use of HandMATE at home. The exoskeleton communicates wirelessly with an Android tablet which features guided exercises, therapeutic games and performance feedback. We surveyed 5 chronic stroke patients who used the HandMATE device to further evaluate our system, receiving positive feedback on the exoskeleton and integrated app.

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.

Comparison of Two Series Elastic Actuator Designs Incorporated into a Shoulder Exoskeleton

Low impedance and torque control are critical for movement rehabilitation using robotic exoskeletons. A grounded 3 degree of freedom shoulder exoskeleton was designed for movement assistance in shoulder abduction/adduction, flexion/extension, and shoulder internal/external rotation. Two series elastic actuators designs were developed using a linear spring arrangement with a global nonlinear stiffness behavior. RMS errors during application of constant torque were less than.06 Nm in shoulder add/abd and less than.04 Nm in arm rotation as the limb was moved in sinusoidal trajectories up to 3.5 Hz. For abd/adduction, the step response rise time was.05 s, and free mode impedance peaked at.007 Nm/deg during 3.5 Hz oscillations. For arm rotation, the step response rise time was.03 s, and impedance peaked at.023 Nm/deg during 3.5 Hz oscillations. Both SEA designs had performance measurements that were similar to other SEA designs in terms of torque tracking, but with much lower impedance than previously reported.

Cross-sectional evaluation of visuomotor tracking performance following subconcussive head impacts

BACKGROUND

Repeated mild traumatic brain injury (mTBI) has been associated with increased risk of degenerative neurological disorders. While the effects of mTBI and repeated injury are known, studies have only recently started examining repeated subconcussive impacts, impacts that do not result in a clinically diagnosed mTBI. In these studies, repeated subconcussive impacts have been connected to cognitive performance and brain imaging changes.

OBJECTIVE

Recent research suggests that performance on a visuomotor tracking (VMT) task may help improve the identification of mTBI. The goal of this study was to investigate if VMT performance is sensitive to the cumulative effect of repeated subconcussive head impacts in collegiate men's lacrosse players.

METHODS

A cross-sectional, prospective study was completed with eleven collegiate men's lacrosse players. Participants wore helmet-mounted sensors and completed VMT and reaction time assessments. The relationship between cumulative impact metrics and VMT metrics were investigated.

RESULTS

In this study, VMT performance correlated with repeated subconcussive head impacts; individuals approached clinically diagnosed mTBI-like performance as the cumulative rotational velocity they experienced increased.

CONCLUSION

This suggests that repeated subconcussive impacts can result in measurable impairments and indicates that visuomotor tracking performance may be a useful tool for monitoring the effects of repeated subconcussive impacts.

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.

Hand rehabilitation after stroke using a wearable, high DOF, spring powered exoskeleton

Stroke patients often have inappropriate finger flexor activation and finger extensor weakness, which makes it difficult to open their affected hand for functional grasp. The goal was to develop a passive, lightweight, wearable device to enable improved hand function during performance of activities of daily living. The device, HandSOME II, assists with opening the patient's hand using 11 elastic actuators that apply extension torques to finger and thumb joints. Device design and initial testing are described. A novel mechanical design applies forces orthogonal to the finger segments despite the fact that all of the device DOFs are not aligned with human joint DOF. In initial testing with seven stroke subjects with impaired hand function, use of HandSOME II significantly increased maximum extension angles and range of motion in all of the index finger joints (P<;0.05). HandSOME II allows performance of all the grip patterns used in daily activities and can be used as part of home-based therapy programs.

Spring operated wearable enhancer for arm rehabilitation (SpringWear) after stroke

A 5-DOF spring actuated exoskeleton, called SpringWear, was developed to increase range of motion in the affected arms of stroke patients. Theoretically perfect gravity compensation is provided at the shoulder elevation DOF. Additional torque is provided to assist weakness in forearm supination and elbow extension. Three stroke patients were tested. All of the assisted joints increased in range of motion, and larger gains should be possible with refinements in the available torque profiles. Additionally, finger range of motion was increased in one subject when asked to open the hand while holding the shoulder at 90 degrees of elevation.

Home-Based Therapy After Stroke Using the Hand Spring Operated Movement Enhancer (HandSOME)

In previous work, we developed a lightweight wearable hand exoskeleton (Hand Spring Operated Movement Enhancer) that improves range of motion and function in laboratory testing. In this pilot study, we added the ability to log movement data for extended periods and recruited ten chronic stroke subjects to use the device during reach and grasp task practice at home for 1.5 h/day, five days per week, and for four weeks. Seven subjects completed the study, performing 448 ± 651 hand movements per training day. After training, impairment was reduced (Fugl-Meyer test; gain = 4.9 ± 4.1; p = .039) and function was improved (Action Research Arm Test; gain = 3.3 ± 2.6; p = .032). There was a significant correlation between gains in the Action Research Arm Test and the number of movements during training (r = 0.90; p = .005). Proximal arm control also improved, as evidenced by a significant reduction in the reach path ratio (p = 0.038). Five subjects responded well to the treatment, having gains of six points or more on the Fugl-Meyer or action research arm test, and achieving significant gains in digit extension (gain = 19.8 ± 10.2°; p = 0.024). However, all of the gains that were significant immediately after training were no longer significant at the three month follow-up. This treatment approach appears promising, but longer periods of home training may be needed to achieve sustainable gains.

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 β-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 β-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 β-band coherence (corticospinal pathway).

Use of Accelerometers to Assess Upper-Extremity Motor Performance Following Stroke: A Pilot Study

Date Presented 4/9/2016

The poster will discuss the results of a pilot study conducted in a free-standing rehabilitation hospital investigating the relationship between hemiplegic arm use after stroke measured in the clinic versus measurement of arm use in the home setting by wrist accelerometers.

Primary Author and Speaker: Rahsaan Holley

Additional Authors and Speakers: Neepa Shah, Evan Chan, Peter Lum

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).

Using the Kinect to limit abnormal kinematics and compensation strategies during therapy with end effector robots

Abnormal kinematics and the use of compensation strategies during training limit functional improvement from therapy. The Kinect is a low cost ($100) sensor that does not require any markers to be placed on the user. Integration of this sensor into currently used therapy systems can provide feedback about the user's movement quality, and the use of compensatory strategies to complete tasks. This paper presents a novel technique of adding the Kinect to an end effector robot to limit compensation strategies and to train normal joint coordination during movements with an end effector robot. This methodology has wider implications for other robotic and passively actuated end effector rehabilitation devices.

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.

Robotic therapy provides a stimulus for upper limb motor recovery after stroke that is complementary to and distinct from conventional therapy

BACKGROUND

Individuals with chronic stroke often have long-lasting upper extremity impairments that impede function during activities of daily living. Rehabilitation robotics have shown promise in improving arm function, but current systems do not allow realistic training of activities of daily living. We have incorporated the ARMin III and HandSOME device into a novel robotic therapy modality that provides functional training of reach and grasp tasks.

OBJECTIVE

To compare the effects of equal doses of robotic and conventional therapy in individuals with chronic stroke.

METHODS

Subjects were randomized to 12 hours of robotic or conventional therapy and then crossed over to the other therapy type after a 1-month washout period. Twelve moderate to severely impaired individuals with chronic stroke were enrolled, and 10 completed the study.

RESULTS

Across the 3-month study period, subjects showed significant improvements in the Fugl-Meyer (P = .013) and Box and Blocks tests (P = .028). The robotic intervention produced significantly greater improvements in the Action Research Arm Test than conventional therapy (P = .033). Gains in the Box and Blocks test from conventional therapy were larger than from robotic therapy in subjects who received conventional therapy after robotic therapy (P = .044).

CONCLUSIONS

Data suggest that robotic therapy can elicit improvements in arm function that are distinct from conventional therapy and supplements conventional methods to improve outcomes. Results from this pilot study should be confirmed in a larger study.

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.

RESULTS

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.

Compensation for the intrinsic dynamics of the InMotion2 robot

The InMotion2 and other similarly designed robots, are commonly used for rehabilitation of neurological injuries and motor adaptation studies. These robots are used to simulate haptic environments; however, anisotropy in end-point impedance due to the intrinsic robot dynamics can compromise these experiments. The goal was to decrease the magnitude and anisotropy of the robot impedance using a dynamic compensation algorithm that reduces the forces normally felt by the user during rapid movements. We tested this algorithm with two different methods for real-time calculation of derivatives, a novel quadratic fit method (CQF) and the commonly used backward derivative method (CBD). Six subjects performed a series of point-to-point movements under three conditions (no compensation, CQF, CBD), in different directions at peak speeds of 50, 100 and 150 cm/s. Without compensation, tangential peak-to-peak forces were as large as 69 N in certain directions at the 150 cm/s speed. Both CQF and CBD significantly reduced tangential forces in all directions and speeds. CQF outperformed CBD in the directions with highest intrinsic impedance, reducing tangential forces by 64% in these directions. Compensation also significantly reduced forces normal to the movement direction, with CQF again outperforming CBD in several cases. Anisotropy was assessed by the range of tangential peak-to-peak forces across movement directions. In the no compensation condition, anisotropy was as high as 52.7 N at the 150 cm/s speed, but an average anisotropy reduction of 74% was achieved with CQF. The CQF method can significantly reduce impedance and anisotropy in this class of robot.

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.

A telerehabilitation platform for home-based automated therapy of arm function

Constraint-Induced Movement Therapy (CI therapy) has been shown to be an effective approach for improving arm function in stroke survivors with mild to severe hemiparesis. Given the time-intensive nature of the intervention, and the inherent costs and travel required to receive in-clinic treatment, the accessibility and availability of CI therapy is limited. To facilitate home-based CI therapy, a telerehabilitation platform has been developed. It consists of a table-top workstation configured with a range of physical task devices (e.g. pegboard, object flipping, threading, vertical reaching). A desktop PC is used to acquire data from sensors embedded in the task devices; display visual instructions, stimuli, and feedback to the patient during tasks; and provide videoconferencing and remote connection capabilities so the therapist can interact with and monitor the patient during at-home therapy sessions. This system has potential to greatly expand access to CI therapy and make it a more realistic option for a larger number of stroke survivors with upper extremity impairment.

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

Hand Spring Operated Movement Enhancer (HandSOME): a portable, passive hand exoskeleton for stroke rehabilitation

Stroke patients often have flexor hypertonia and finger extensor weakness, which makes it difficult to open their affected hand for functional grasp. Because of this impairment, hand rehabilitation after stroke is essential for restoring functional independent lifestyles. The goal of this study is to develop a passive, lightweight, wearable device to assist with hand function during performance of activities of daily living. The device, Hand Spring Operated Movement Enhancer (HandSOME), assists with opening the patient's hand using a series of elastic cords that apply extension torques to the finger joints and compensates for the flexor hypertonia. Device design and calibration are described as well as functional and usability testing with stroke subjects with a wide range of hand impairments. In initial testing with eight stroke subjects with finger flexor hypertonia, use of the HandSOME significantly increased range of motion and functional ability (p=0.002) . There was some decrease in grip strength with the HandSOME device at the subject's ideal setting, however this was not statistically significant (p=0.167) and did not seem to have a significant effect on function. Overall HandSOME shows promise as a training tool to facilitate repetitive task practice for improving hand function in stroke patients. HandSOME can be used as part of a home-based therapy program, or as an orthotic for replacing lost function.

Hand spring operated movement enhancer (HandSOME) device for hand rehabilitation after stroke

Hand rehabilitation after stroke is essential for restoring functional independent lifestyles. After stroke, patients often have flexor hypertonia, making it difficult to open their hand for functional grasp. The development and initial testing of a passive hand rehabilitation device is discussed. The device, Hand Spring Operated Movement Enhancer (HandSOME), assists with opening the patient's hand using a series of bungee cords that apply extension torques to the finger joints that compensate for the flexor hypertonia. This results in significant increase in range of motion and functional use when wearing HandSOME, even in severely impaired subjects. Device design, calibration, and range of motion are described as well as functional and usability testing with stroke subjects.

Time Independent Functional task Training: a case study on the effect of inter-joint coordination driven haptic guidance in stroke therapy

After a stroke abnormal joint coordination of the arm may limit functional movement and recovery. To aid in training inter-joint movement coordination a haptic guidance method for functional driven rehabilitation after stroke called Time Independent Functional Training (TIFT) has been developed for the ARMin III robot. The mode helps retraining inter-joint coordination during functional movements, such as putting an object on a shelf, pouring from a pitcher, and sorting objects into bins. A single chronic stroke subject was tested for validation of the modality. The subject was given 1.5 hrs of robotic therapy twice a week for 4 weeks. The therapy and the results of training the single stroke subject are discussed. The subject showed a decrease in training joint error for the sorting task across training sessions and increased self-selected movement time in training. In kinematic reaching analysis the subject showed improvements in range of motion and joint coordination in a reaching task, as well as improvements in supination-pronation range of motion at the wrist.

Comparison of Tone compensation and Spring assistance for hand rehabilitation in HEXORR

Robotic rehabilitation techniques have the capacity to provide high dosage therapy without the labor burden of conventional methods. The most effective means of using robots to retrain function is not yet known, though many studies now support providing assistance to movement while the user actively participates in that movement. In this study, we compare, in three chronic stroke subjects, a novel Tone assistance mode to a Spring assistance method commonly used in other robots. The Tone mode provides assistance comparable to the subject's own resistance to extension while Spring mode provides a spring-like force to pull the subject to the target. All three subjects produced larger finger movements with robotic assistance, but they also produced much more positive work with the Tone assistance compared to the Spring assistance. This demonstrates that subjects were actively driving the movements in Tone mode to a greater extent than in Spring mode. Two out of three subjects showed similar results in the thumb. In the third subject, work was comparable across all modes. With Tone assistance, subjects produced movement and torque profiles more similar to that of Unassisted movement than Spring-assisted movement for both fingers and thumb. These results suggest that providing assistance tailored to the user's own tone profile may be an effective means of enhancing range of motion to ultimately enable gains in hand function.

Hand function recovery in chronic stroke with HEXORR robotic training: A case series

After a stroke, many survivors have impaired motor function. Robotic rehabilitation techniques have emerged to provide a repetitive, activity-based therapy at potentially lower cost than conventional methods. Many patients exhibit intrinsic resistance to hand extension in the form of spasticity and/or hypertonia. We have developed a therapy program using the Hand Exoskeleton Rehabilitation Robot (HEXORR) that is capable of compensating for tone to assist patients in opening the paretic hand. The system can move the user's hand, assist movement, allow free movement, or restrict movement to allow static force production. These options combine with an interactive virtual reality game to enhance user motivation. Four chronic stroke subjects received 18 sessions of robot therapy as well as pre and post evaluation sessions. All subjects showed at least modest gains in active finger range of motion (ROM) measured in the robot, and all but one subject had gains in active thumb ROM. Most of these gains carried over to ROM gains outside of the robot. The clinical measures (Fugl-Meyer, Box-and-Blocks) showed clear improvements in two subjects and mixed results in two subjects. Overall, the robot therapy was well received by subjects and shows promising results. We conclude HEXORR therapy is best suited for patients with mild-moderate tone and at least minimal extension.

Development and pilot testing of HEXORR: hand EXOskeleton rehabilitation robot

BACKGROUND

Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased.

METHODS

This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject.

RESULTS

For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the exoskeleton and the force assistance mode was successful in increasing active ROM by 43 +/- 5% (P < 0.001) and 24 +/- 6% (P = 0.041) for the fingers and thumb, respectively.

CONCLUSIONS

Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation.

Effect of training on upper-extremity prosthetic performance and motor learning: a single-case study

OBJECTIVES

To examine the impact of a new prosthesis on an experienced and highly motivated prosthetic limb user, to evaluate the effects of training and the ability of clinical measures to detect change, and to gain insight into the mechanisms by which improvement occurs.

DESIGN

A single-case study.

SETTING

An outpatient clinic.

PARTICIPANT

A bilateral high-arm amputee (right shoulder disarticulation, left above elbow).

INTERVENTIONS

Provision of new prosthesis and occupational therapy.

MAIN OUTCOME MEASURES

Action Research Arm Test, box and block test of manual dexterity, Jebsen-Taylor Hand Function Test, and speed and accuracy of reaching movements with and without visual guidance.

RESULTS

In this experienced prosthesis user, provision of a new prosthesis led to an immediate worsening in functional limitation. With training, the subject recovered his baseline status and then exceeded it in both proximal and distal function. All study clinical measures detected change, but the change detected varied as much as 300-fold depending on the measure chosen. The clinical improvements were associated with modest improvements in the speed of reaching but not the accuracy of reaching under visual guidance. Improvements in reaching accuracy without visual guidance were seen after 10 trials, suggesting that some motor learning had occurred.

CONCLUSIONS

Provision of a new prosthesis can cause functional decline even in an experienced user; this decline can be reversed with training. There is wide variability in sensitivity to change among functional limitation measures. Although some training-related improvements may have been due to increased speed and accuracy of reaching without visual guidance, skill in prosthesis use also plays a role.

Automated Constraint-Induced Therapy Extension (AutoCITE) for movement deficits after stroke

We report progress in the development of AutoCITE, a workstation that delivers the task practice component of upper-limb Constraint-Induced Movement therapy and that can potentially be used in the clinic or the home without the need for one-on-one supervision from a therapist. AutoCITE incorporates a computer and eight task devices arranged on a modified cabinet. Task performance is automatically recorded, and several types of feedback are provided. In preliminary testing, nine chronic stroke subjects with mild to moderate motor deficits practiced with AutoCITE for 3 h each weekday for 2 weeks. Subjects wore a padded mitt on the less-affected hand for a target of 90% of their waking hours. In terms of effect sizes, gains were large and significant on the Motor Activity Log, and moderate to large on the Wolf Motor Function Test. These gains were comparable to the gains of a matched group of 12 subjects who received standard Constraint-Induced Movement therapy.