Use of computational modeling to examine fingertip force production in children with hemiplegic cerebral palsy.

Most children with hemiplegic cerebral palsy (HCP), one of the most prevalent subtypes of cerebral palsy, struggle with grasping and manipulating objects. This impairment may arise from a diminished capacity to properly direct forces created with the finger pad due to aberrant force application. Children with HCP were asked to create maximal force with the index finger pad in the palmar (normal) direction with both the paretic and non-paretic hands. The resulting forces and finger postures were then applied to a computational musculoskeletal model of the hand to estimate the corresponding muscle activation patterns. Subjects tended to create greater shear force relative to normal force with the paretic hand (p < 0.05). The resultant force was directed 33.6°±10.8° away from the instructed palmar direction in the paretic hand, but only 8.0°±7.3° in the non-paretic hand. Additionally, participants created greater palmar force with the non-paretic hand than with the paretic hand (p < 0.05). These differences in force production are likely due to differences in muscle activation pattern, as our computational models showed differences in which muscles are active and their relative activations when recreating the measured force vectors for the two hands (p < 0.01). The models predicted reduced activation in the extrinsic and greater reductions in activation in the intrinsic finger muscles, potentially due to reduced voluntary activation or muscle atrophy. As the large shear forces could lead to objects slipping from grasp, muscle activation patterns may provide an important target for therapeutic treatment in children with HCP.

Effects of wrist posture and stabilization on precision grip force production and muscle activation patterns.

Most of the power for generating forces in the fingers arises from muscles located in the forearm. This configuration maximizes finger joint range of motion while minimizing finger mass and inertia. The resulting multiarticular arrangement of the tendons, however, complicates independent control of the wrist and the digits. Actuating the wrist impacts sensorimotor control of the fingers and vice versa. The goal of this study was to systematically investigate interactions between isometric wrist and digit control. Specifically, we examined how the need to maintain a specified wrist posture influences precision grip. Fifteen healthy adults produced maximum precision grip force at 11 different wrist flexion/extension angles, with the arm supported, under two conditions: 1) the participant maintained the desired wrist angle while performing the precision grip and 2) a robot maintained the specified wrist angle. Wrist flexion/extension posture significantly impacted maximum precision grip force (P < 0.001), with the greatest grip force achieved when the wrist was extended 30° from neutral. External wrist stabilization by the robot led to a 20% increase in precision grip force across wrist postures. Increased force was accompanied by increased muscle activation but with an activation pattern similar to the one used when the participant had to stabilize their wrist. Thus, simultaneous wrist and finger requirements impacted performance of an isometric finger task. External wrist stabilization can promote increased precision grip force resulting from increased muscle activation. These findings have potential clinical significance for individuals with neurologically driven finger weakness, such as stroke survivors.NEW & NOTEWORTHY We explored the interdependence between wrist and fingers by assessing the influence of wrist posture and external stabilization on precision grip force generation. We found that maximum precision grip force occurred at an extended wrist posture and was 20% greater when the wrist was Externally Stabilized. The latter resulted from amplification of muscle activation patterns from the Self-Stabilized condition rather than adoption of new patterns exploiting external wrist stabilization.

Cosimulation of the index finger extensor apparatus with finite element and musculoskeletal models.

Musculoskeletal modeling has been effective for simulating dexterity and exploring the consequences of disability. While previous approaches have examined motor function using multibody dynamics, existing musculoskeletal models of the hand and fingers have difficulty simulating soft tissue such as the extensor mechanism of the fingers, which remains underexplored. To investigate the extensor mechanism and its impact on finger motor function, we developed a finite element model of the index finger extensor mechanism and a cosimulation method that combines the finite element model with a multibody dynamic model. The finite element model and cosimulation were validated through comparison with experimentally derived tissue strains and fingertip endpoint forces respectively. Tissue strains predicted by the finite element model were consistent with the experimentally observed strains of the 9 postures tested in cadaver specimens. Fingertip endpoint forces predicted using the cosimulation were well aligned in both force (difference within 0.60 N) and direction (difference within 30°with experimental results. Sensitivity of the extensor mechanism to changes in modulus and adhesion configuration were evaluated for ± 50% of experimental moduli, presence of the radial and ulnar adhesions, and joint capsule. Simulated strains and endpoint forces were found to be minimally sensitive to alterations in moduli and adhesions. These results are promising and demonstrate the ability of the cosimulation to predict global behavior of the extensor mechanism, while enabling measurement of stresses and strains within the structure itself. This model could be used in the future to predict the outcomes for different surgical repairs of the extensor mechanism.

Robust neural decoding for dexterous control of robotic hand kinematics.

BACKGROUND: Manual dexterity is a fundamental motor skill that allows us to perform complex daily tasks. Neuromuscular injuries, however, can lead to the loss of hand dexterity. Although numerous advanced assistive robotic hands have been developed, we still lack dexterous and continuous control of multiple degrees of freedom in real-time. In this study, we developed an efficient and robust neural decoding approach that can continuously decode intended finger dynamic movements for real-time control of a prosthetic hand. METHODS: High-density electromyogram (HD-EMG) signals were obtained from the extrinsic finger flexor and extensor muscles, while participants performed either single-finger or multi-finger flexion-extension movements. We implemented a deep learning-based neural network approach to learn the mapping from HD-EMG features to finger-specific population motoneuron firing frequency (i.e., neural-drive signals). The neural-drive signals reflected motor commands specific to individual fingers. The predicted neural-drive signals were then used to continuously control the fingers (index, middle, and ring) of a prosthetic hand in real-time. RESULTS: Our developed neural-drive decoder could consistently and accurately predict joint angles with significantly lower prediction errors across single-finger and multi-finger tasks, compared with a deep learning model directly trained on finger force signals and the conventional EMG-amplitude estimate. The decoder performance was stable over time and was robust to variations of the EMG signals. The decoder also demonstrated a substantially better finger separation with minimal predicted error of joint angle in the unintended fingers. CONCLUSIONS: This neural decoding technique offers a novel and efficient neural-machine interface that can consistently predict robotic finger kinematics with high accuracy, which can enable dexterous control of assistive robotic hands.

Concurrent and Continuous Prediction of Finger Kinetics and Kinematics via Motoneuron Activities.

OBJECTIVE: Robust neural decoding of intended motor output is crucial to enable intuitive control of assistive devices, such as robotic hands, to perform daily tasks. Few existing neural decoders can predict kinetic and kinematic variables simultaneously. The current study developed a continuous neural decoding approach that can concurrently predict fingertip forces and joint angles of multiple fingers. METHODS: We obtained motoneuron firing activities by decomposing high-density electromyogram (HD EMG) signals of the extrinsic finger muscles. The identified motoneurons were first grouped and then refined specific to each finger (index or middle) and task (finger force and dynamic movement) combination. The refined motoneuron groups (separate matrix) were then applied directly to new EMG data in real-time involving both finger force and dynamic movement tasks produced by both fingers. EMG-amplitude-based prediction was also performed as a comparison. RESULTS: We found that the newly developed decoding approach outperformed the EMG-amplitude method for both finger force and joint angle estimations with a lower prediction error (Force: 3.47±0.43 vs 6.64±0.69% MVC, Joint Angle: 5.40±0.50° vs 12.8±0.65°) and a higher correlation (Force: 0.75±0.02 vs 0.66±0.05, Joint Angle: 0.94±0.01 vs 0.5±0.05) between the estimated and recorded motor output. The performance was also consistent for both fingers. CONCLUSION: The developed neural decoding algorithm allowed us to accurately and concurrently predict finger forces and joint angles of multiple fingers in real-time. SIGNIFICANCE: Our approach can enable intuitive interactions with assistive robotic hands, and allow the performance of dexterous hand skills involving both force control tasks and dynamic movement control tasks.

Exploring Kinetic and Kinematic Finger Individuation Capability in Children With Hemiplegic Cerebral Palsy.

While fine manual dexterity develops over time, the extent to which children show independent control of their digits in each hand and the impact of perinatal brain injury on this individuation have not been well quantified. Our goal in this study was to assess and compare finger force and movement individuation in 8-14 year old children with hemiplegic cerebral palsy (hCP; n = 4) and their typically developing peers (TD; n = 10). We evaluated finger force individuation with five independent load cells and captured joint movement individuation with video tracking. We observed no significant differences in individuation indices between the dominant and non-dominant hands of TD children, but individuated force and movement were substantially reduced in the paretic versus non paretic hands of children with hCP (p < 0.001). In TD participants, the thumb tended to have the greatest level of independent control. This small sample of children with hCP showed substantial loss of individuation in the paretic hand and some deficits in the non-paretic hand, suggesting possible benefit from targeted training of digit independence in both hands for children with CP.

Abnormal proximal-distal interactions in upper-limb of stroke survivors during object manipulation: A pilot study.

Despite its importance, abnormal interactions between the proximal and distal upper extremity muscles of stroke survivors and their impact on functional task performance has not been well described, due in part to the complexity of upper extremity tasks. In this pilot study, we elucidated proximal-distal interactions and their functional impact on stroke survivors by quantitatively delineating how hand and arm movements affect each other across different phases of functional task performance, and how these interactions are influenced by stroke. Fourteen subjects, including nine chronic stroke survivors and five neurologically-intact subjects participated in an experiment involving transport and release of cylindrical objects between locations requiring distinct proximal kinematics. Distal kinematics of stroke survivors, particularly hand opening, were significantly affected by the proximal kinematics, as the hand aperture decreased and the duration of hand opening increased at the locations that requires shoulder abduction and elbow extension. Cocontraction of the extrinsic hand muscles of stroke survivors significantly increased at these locations, where an increase in the intermuscular coherence between distal and proximal muscles was observed. Proximal kinematics of stroke survivors was also affected by the finger extension, but the cocontraction of their proximal muscles did not significantly increase, suggesting the changes in the proximal kinematics were made voluntarily. Our results showed significant proximal-to-distal interactions between finger extension and elbow extension/shoulder abduction of stroke survivors exist during their functional movements. Increased cocontraction of the hand muscles due to increased neural couplings between the distal and proximal muscles appears to be the underlying mechanism.

Effect of novel training to normalize altered finger force direction post-stroke: study protocol for a double-blind randomized controlled trial.

BACKGROUND: Functional task performance requires proper control of both movement and force generation in three-dimensional space, especially for the hand. Control of force in three dimensions, however, is not explicitly treated in current physical rehabilitation. To address this gap in treatment, we have developed a tool to provide visual feedback on three-dimensional finger force. Our objective is to examine the effectiveness of training with this tool to restore hand function in stroke survivors. METHODS: Double-blind randomized controlled trial. All participants undergo 18 1-h training sessions to practice generating volitional finger force of various target directions and magnitudes. The experimental group receives feedback on both force direction and magnitude, while the control group receives feedback on force magnitude only. The primary outcome is hand function as measured by the Action Research Arm Test. Other outcomes include the Box and Block Test, Stroke Impact Scale, ability to direct finger force, muscle activation pattern, and qualitative interviews. DISCUSSION: The protocol for this clinical trial is described in detail. The results of this study will reveal whether explicit training of finger force direction in stroke survivors leads to improved motor control of the hand. This study will also improve the understanding of neuromuscular mechanisms underlying the recovery of hand function. TRIAL REGISTRATION: ClinicalTrials.gov NCT03995069 . Registered on June 21, 2019.

A generic neural network model to estimate populational neural activity for robust neural decoding.

BACKGROUND: Robust and continuous neural decoding is crucial for reliable and intuitive neural-machine interactions. This study developed a novel generic neural network model that can continuously predict finger forces based on decoded populational motoneuron firing activities. METHOD: We implemented convolutional neural networks (CNNs) to learn the mapping from high-density electromyogram (HD-EMG) signals of forearm muscles to populational motoneuron firing frequency. We first extracted the spatiotemporal features of EMG energy and frequency maps to improve learning efficiency, given that EMG signals are intrinsically stochastic. We then established a generic neural network model by training on the populational neuron firing activities of multiple participants. Using a regression model, we continuously predicted individual finger forces in real-time. We compared the force prediction performance with two state-of-the-art approaches: a neuron-decomposition method and a classic EMG-amplitude method. RESULTS: Our results showed that the generic CNN model outperformed the subject-specific neuron-decomposition method and the EMG-amplitude method, as demonstrated by a higher correlation coefficient between the measured and predicted forces, and a lower force prediction error. In addition, the CNN model revealed more stable force prediction performance over time. CONCLUSIONS: Overall, our approach provides a generic and efficient continuous neural decoding approach for real-time and robust human-robot interactions.

Use of an EMG-Controlled Game as a Therapeutic Tool to Retrain Hand Muscle Activation Patterns Following Stroke: A Pilot Study.

BACKGROUND/PURPOSE: To determine the feasibility of training with electromyographically (EMG) controlled games to improve control of muscle activation patterns in stroke survivors. METHODS: Twenty chronic stroke survivors (>6 months) with moderate hand impairment were randomized to train either unilaterally (paretic only) or bilaterally over 9 one-hour training sessions. EMG signals from the unilateral or bilateral limbs controlled a cursor location on a computer screen for gameplay. The EMG muscle activation vector was projected onto the plane defined by the first 2 principal components of the activation workspace for the nonparetic hand. These principal components formed the x- and y-axes of the computer screen. RESULTS: The recruitment goal (n = 20) was met over 9 months, with no screen failure, no attrition, and 97.8% adherence rate. After training, both groups significantly decreased the time to move the cursor to a novel sequence of targets (P = 0.006) by reducing normalized path length of the cursor movement (P = 0.005), and improved the Wolf Motor Function Test (WMFT) quality score (P = 0.01). No significant group difference was observed. No significant change was seen in the WMFT time or Box and Block Test. DISCUSSION/CONCLUSIONS: Stroke survivors could successfully use the EMG-controlled games to train control of muscle activation patterns. While the nonparetic limb EMG was used in this study to create target EMG patterns, the system supports various means for creating target patterns per user desires. Future studies will employ training with the EMG-controlled games in conjunction with functional task practice for a longer intervention duration to improve overall hand function.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A379).

Characteristics of the severely impaired hand in survivors of stroke with chronic impairments.

BACKGROUND: Diminished sensorimotor control of the hand is one of the most common outcomes following stroke. This hand impairment substantially impacts overall function and quality of life; standard therapy often results in limited improvement. Mechanisms of dysfunction of the severely impaired post-stroke hand are still incompletely understood, thereby impeding the development of new targeted treatments. OBJECTIVE: To identify and determine potential relationships among the mechanisms responsible for hand impairment following stroke. METHODS: This cohort study observed stroke survivors (n = 95) with severe, chronic hand impairment (Chedoke-McMaster Hand score = 2-3). Custom instrumentation created precise perturbations and measured kinematic responses. Muscle activation was recorded through electromyography. Strength, spasticity, muscle relaxation time, and muscle coactivation were quantified. RESULTS: Maximum grip strength in the paretic hand was only 12% of that achieved by the nonparetic hand, and only 6 of 95 participants were able to produce any net extension force. Despite force deficits, spastic reflex response of the finger flexor evoked by imposed stretch averaged 90.1 ± 26.8% of maximum voluntary activation, relaxation time averaged 3.8 ± 0.8 seconds, and coactivation during voluntary extension exceeded 30% of maximum contraction, thereby resulting in substantial net flexion. Surprisingly, these hypertonicity measures were not significantly correlated with each other. CONCLUSIONS: Survivors of severe, chronic hemiparetic stroke experience profound weakness of both flexion and extension that arises from increased involuntary antagonist activation and decreased voluntary activation. The lack of correlation amongst hypertonicity measures suggests that these phenomena may arise from multiple, potentially independent mechanisms that could require different treatments.

Hand function development of children with hemiplegic cerebral palsy: A scoping review.

PURPOSE: Hemiplegic cerebral palsy (hCP) typically impacts sensorimotor control of the hand, but comprehensive assessments of the hands of children with hCP are relatively rare. This scoping review summarizes the development of hand function for children with hCP. METHODS: This scoping review focused on the development of hand function in children with hCP. Electronic databases (PubMed, PEDro, Web of Science, CINAHL, and SpringerLink) were searched to identify studies assessing hand function in children with hCP. The search was performed using keywords (e.g., "hemiplegia"). An iterative approach verified by two authors was used to select the studies. Articles which reported quantitative data for children with hCP on any items of a specified set of hand evaluations were included. Measures were sorted into three categories: quantitative neuromechanics, clinical assessments, and clinical functional evaluations. RESULTS: Initial searches returned 1536 articles, 131 of which were included in the final review. Trends between assessment scores and age were examined for both hands. CONCLUSION: While several studies have evaluated hand function in children with hCP, the majority relied on clinical scales, assessments, or qualitative descriptions. Further assessments of kinematics, kinetics, and muscle activation patterns are needed to identify the underlying impairment mechanisms that should be targeted for treatment.

High Compliance Pneumatic Actuators to Promote Finger Extension in Stroke Survivors.

Compliant pneumatic systems are well suited for wearable robotic applications. The actuators are lightweight, conformable to irregular shapes, and tolerant of uncontrolled degrees of freedom. These attributes are especially desirable for hand exoskeletons given their space and mass constraints. Creating active digit extension with these exoskeletons is especially critical for clinical populations such as stroke survivors who often have great difficulty opening their paretic hand. To achieve active digit extension with a soft actuator, we have created pneumatic chambers that lie along the palmar surface of the digits. These chambers can directly extend the digits when pressurized. We present a characterization of the extension force and passive flexion resistance generated by these pneumatic chambers across a range of joint angles as a function of cross-sectional shape, dimension, and wall thickness. The chambers were fabricated out of DragonSkin 20 using custom molds and were tested on a custom jig. Extension forces created at the end of the chamber (where fingertip contact would occur) exceeded 3.00 N at relatively low pressure (48.3 kPa). A rectangular cross-section generated higher extension force than a semi-obround cross-sectional shape. Extension force was significantly higher (p < 0.05) for actuators with the highest wall thickness compared to those with the thinnest walls. In comparison to previously used polyurethane actuators, the DragonSkin actuators had a much higher extension force for a similar passive bending resistance. Passive bending resistance of the chamber (simulating finger flexion) did not vary significantly with actuator shape, wall thickness, width, or depth. The flexion resistance, however, could be significantly reduced by applying a vacuum. These results provide guidance in designing pneumatic actuators for assisting finger extension and resisting unwanted flexion in the fingers.

A Hand Exoskeleton for Stroke Survivors' Activities of Daily Life.

Stroke is a leading cause of disability in the U.S. Hand impairment is a common consequence of stroke, potentially impacting all facets of life as the hands are the primary means of interacting with the world. Typically, therapy is the prescribed treatment after stroke. However, a majority of stroke survivors have limited recovery and thus chronic impairment. Assistive, rather than therapeutic, devices may help these individuals restore lost function and improve independence and engagement in society. Current assistive devices, however, typically fail to address the greatest barriers to successful use with stroke survivors. In the hand, weakness and incoordination arise from a seemingly paradoxical combination of limited voluntary activation of muscles and involuntary neuromuscular hyperexcitability. Thus, profound strength deficits can be accompanied by substantial forces opposing the intended movement. The assistive device presented in this paper can provide both sufficient flexion and extension assistance to overcome these barriers. A single actuator for each digit provides flexion or extension assistance through push-pull cables guided along the dorsal side of the hand. User intent can be decoded from Electromyographic (EMG) signals to drive the device throughout the movement. EMG control is customized to the capabilities of each user by examining the voluntary EMG workspace.

Automatic Detection of Contracting Muscle Regions via the Deformation Field of Transverse Ultrasound Images: A Feasibility Study.

Accurate identification of contracting muscles can help us to understand the muscle function in both physiological and pathological conditions. Conventional electromyography (EMG) have limited access to deep muscles, crosstalk, or instability in the recordings. Accordingly, a novel framework was developed to detect contracting muscle regions based on the deformation field of transverse ultrasound images. We first estimated the muscle movements in a stepwise calculation, to derive the deformation field. We then calculated the divergence of the deformation field to locate the expanding or shrinking regions during muscle contractions. Two preliminary experiments were performed to evaluate the feasibility of the developed algorithm. Using concurrent intramuscular EMG recordings, Experiment I verified that the divergence map can capture the activity of superficial and deep muscles, when muscles were activated voluntarily or through electrical stimulation. Experiment II verified that the divergence map can only capture contracting muscles but not muscle shortening during passive movements. The results demonstrated that the divergence can individually capture the activity of muscles at different depths, and was not sensitive to muscle shortening during passive movements. The proposed framework can automatically detect the regions of contracting muscle, and could potentially serve as a tool to assess the functions of a group of muscles concurrently.

Modulation of finger muscle activation patterns across postures is coordinated across all muscle groups.

Successful grasp requires that grip forces be properly directed between the fingertips and the held object. Changes in digit posture significantly affect the mapping between muscle force and fingertip force. Joint torques must subsequently be altered to maintain the desired force direction at the fingertips. Our current understanding of the roles of hand muscles in force production remains incomplete, as past studies focused on a limited set of postures or force directions. To thoroughly examine how hand muscles adapt to changing external (force direction) and internal (posture) conditions, activation patterns of six index finger muscles were examined with intramuscular electrodes in 10 healthy subjects. Participants produced submaximal isometric forces in each of six orthogonal directions at nine different finger postures. Across force directions, participants significantly altered activation patterns to accommodate postural changes in the interphalangeal joint angles but not changes in the metacarpophalangeal joint angles. Modulation of activation levels of the extrinsic hand muscles, particularly the extensors, were as great as those of intrinsic muscles, suggesting that both extrinsic and intrinsic muscles were involved in creating the desired forces. Despite considerable between-subject variation in the absolute activation patterns, principal component analysis revealed that participants used similar strategies to accommodate the postural changes. The changes in muscle coordination also helped increase joint impedance in order to stabilize the end-point force direction. This effect counteracts the increased signal-dependent motor noise that arises with greater magnitude of muscle activation as interphalangeal joint flexion is increased. These results highlight the role of the extrinsic muscles in controlling fingertip force direction across finger postures.NEW & NOTEWORTHY We examined how hand muscles adapt to changing external (force direction) and internal (posture) conditions. Muscle activations, particularly of the extrinsic extensors, were significantly affected by postural changes of the interphalangeal, but not metacarpophalangeal, joints. Joint impedance was modulated so that the effects of the signal-dependent motor noise on the force output were reduced. Comparisons with theoretical solutions showed that the chosen activation patterns occupied a small portion of the possible solution space, minimizing the maximum activation of any one muscle.

Survivors of Chronic Stroke Experience Continued Impairment of Dexterity But Not Strength in the Nonparetic Upper Limb.

OBJECTIVE: To investigate the performance of the less affected upper limb in people with stroke compared with normative values. To examine less affected upper limb function in those whose prestroke dominant limb became paretic and those whose prestroke nondominant limb became paretic. DESIGN: Cohort study of survivors of chronic stroke (7.2±6.7y post incident). SETTING: The study was performed at a freestanding academic rehabilitation hospital. PARTICIPANTS: Survivors of chronic stroke (N=40) with severe hand impairment (Chedoke-McMaster Stroke Assessment rating of 2-3 on Stage of Hand) participated in the study. In 20 participants the prestroke dominant hand (DH) was tested (nondominant hand [NH] affected by stroke), and in 20 participants the prestroke NH was tested (DH affected by stroke). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Jebsen-Taylor Hand Function Test. Data from survivors of stroke were compared with normative age- and sex-matched data from neurologically intact individuals. RESULTS: When combined, DH and NH groups performed significantly worse on fine motor tasks with their nonparetic hand relative to normative data (P<.007 for all measures). Even the participants who continued to use their prestroke DH as their primary hand after the stroke demonstrated reduced fine motor skills compared with normative data. In contrast, grip strength was not significantly affected in either group of survivors of stroke (P>.140). CONCLUSIONS: Survivors of stroke with severe impairment of the paretic limb continue to present significant upper extremity impairment in their nominally nonparetic limb even years after stroke. This phenomenon was observed regardless of whether the DH or NH hand was primarily affected. Because this group of survivors of stroke is especially dependent on the nonparetic limb for performing functional tasks, our results suggest that the nonparetic upper limb should be targeted for rehabilitation.

Home-based Upper Extremity Stroke Therapy Using a Multiuser Virtual Reality Environment: A Randomized Trial.

OBJECTIVE: To compare participation and subjective experience of participants in both home-based multiuser virtual reality (VR) therapy and home-based single-user (SU) VR therapy. DESIGN: Crossover, randomized trial. SETTING: Initial training and evaluations occurred in a rehabilitation hospital; the interventions took place in participants' homes. PARTICIPANTS: Survivors of stroke with chronic upper extremity impairment (N=20). INTERVENTIONS: Four weeks of in-home treatment using a custom, multiuser virtual reality system (VERGE): 2 weeks of both multiuser (MU) and SU versions of VERGE. The order of presentation of SU and MU versions was randomized such that participants were divided into 2 groups, First MU and First SU. MAIN OUTCOME MEASURES: We measured arm displacement during each session (m) as the primary outcome measure. Secondary outcome measures include time participants spent using each MU and SU VERGE and Intrinsic Motivation Inventory scores. Fugl-Meyer Assessment of Motor Recovery After Stroke Upper Extremity (FMA-UE) score and compliance with prescribed training were also evaluated. Measures were recorded before, midway, and after the treatment. Activity and movement were measured during each training session. RESULTS: Arm displacement during a session was significantly affected the mode of therapy (MU: 414.6m, SU: 327.0m, P=.019). Compliance was very high (99% compliance for MU mode and 89% for SU mode). Within a given session, participants spent significantly more time training in the MU mode than in the SU mode (P=.04). FMA-UE score improved significantly across all participants (Δ3.2, P=.001). CONCLUSIONS: Multiuser VR exercises may provide an effective means of extending clinical therapy into the home.

A Platform for Rehabilitation of Finger Individuation in Children with Hemiplegic Cerebral Palsy.

The brain injury that results in cerebral palsy CP may adversely affect fine motor control of the hand. The degradation of manual dexterity in the fingers profoundly impacts overall functionality of the upper limb, yet research efforts to facilitate rehabilitation of finger individuation in children with CP have been limited. This study describes the development of an integrated hardware and software platform for training and evaluating finger individuation. A pneumatically actuated glove provides extension assistance or flexion resistance independently to each digit in concert with playing a virtual reality keyboard. This setup enables intensive and efficient practice of fine motor control of either or both hands. Bimanual training options range from mirror movements to fully independent motions and rhythms in each hand, thereby enabling maintenance of the proper level of challenge. Additionally, an instrument was created to provide assessment of individuated fingertip force generation in order to evaluate effectiveness of the training. Preliminary data were obtained from children both with and without CP using this tool.