Soft pneumatic actuators for pushing fingers into extension.

BACKGROUND: Compliant pneumatic actuators possess many characteristics that are desirable for wearable robotic systems. These actuators can be lightweight, integrated with clothing, and accommodate uncontrolled degrees of freedom. These attributes are especially desirable for hand exoskeletons, where the soft actuator can conform to the highly variable digit shape. In particular, locating the pneumatic actuator on the palmar side of the digit may have benefits for assisting finger extension and resisting unwanted finger flexion, but this configuration requires suppleness to allow digit flexion while retaining sufficient stiffness to assist extension. METHODS: To meet these needs, we designed an actuator consisting of a hollow chamber long enough to span the joints of each digit while sufficiently narrow not to inhibit finger adduction. We explored the geometrical design parameter space for this chamber in terms of shape, dimensions, and wall thickness. After fabricating an elastomer-based prototype for each actuator design, we measured active extension force and passive resistance to bending for each chamber using a mechanical jig. We also created a finite element model for each chamber to enable estimation of the impact of chamber deformation, caused by joint rotation, on airflow through the chamber. Finally, we created a prototype hand exoskeleton with the chamber parameters yielding the best outcomes. RESULTS: A rectangular cross-sectional area was preferable to a semi-obround shape for the chamber; wall thickness also impacted performance. Extension joint torque reached 0.33 N-m at a low chamber pressure of 48.3 kPa. The finite element model confirmed that airflow for the rectangular chamber remained high despite deformation resulting from joint rotation. The hand exoskeleton created with the rectangular chambers enabled rapid movement, with a cycle time of 1.1 s for voluntary flexion followed by actuated extension. CONCLUSIONS: The developed soft actuators are feasible for use in promoting finger extension from the palmar side of the hand. This placement utilizes pushing rather than pulling for digit extension, which is more comfortable and safer. The small chamber volumes allow rapid filling and evacuation to facilitate relatively high frequency finger movements.

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.

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).

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.

Development of a 3D, networked multi-user virtual reality environment for home therapy after stroke.

BACKGROUND: Impairment of upper extremity function is a common outcome following stroke, to the detriment of lifestyle and employment opportunities. Yet, access to treatment may be limited due to geographical and transportation constraints, especially for those living in rural areas. While stroke rates are higher in these areas, stroke survivors in these regions of the country have substantially less access to clinical therapy. Home therapy could offer an important alternative to clinical treatment, but the inherent isolation and the monotony of self-directed training can greatly reduce compliance. METHODS: We developed a 3D, networked multi-user Virtual Environment for Rehabilitative Gaming Exercises (VERGE) system for home therapy. Within this environment, stroke survivors can interact with therapists and/or fellow stroke survivors in the same virtual space even though they may be physically remote. Each user's own movement controls an avatar through kinematic measurements made with a low-cost, Kinect™ device. The system was explicitly designed to train movements important to rehabilitation and to provide real-time feedback of performance to users and clinicians. To obtain user feedback about the system, 15 stroke survivors with chronic upper extremity hemiparesis participated in a multisession pilot evaluation study, consisting of a three-week intervention in a laboratory setting. For each week, the participant performed three one-hour training sessions with one of three modalities: 1) VERGE system, 2) an existing virtual reality environment based on Alice in Wonderland (AWVR), or 3) a home exercise program (HEP). RESULTS: Over 85% of the subjects found the VERGE system to be an effective means of promoting repetitive practice of arm movement. Arm displacement averaged 350 m for each VERGE training session. Arm displacement was not significantly less when using VERGE than when using AWVR or HEP. Participants were split on preference for VERGE, AWVR or HEP. Importantly, almost all subjects indicated a willingness to perform the training for at least 2-3 days per week at home. CONCLUSIONS: Multi-user VR environments hold promise for home therapy, although the importance of reducing complexity of operation for the user in the VR system must be emphasized. A modified version of the VERGE system is currently being used in a home therapy study.

Design and Evaluation of an Actuated Exoskeleton for Examining Motor Control in Stroke Thumb.

Chronic hand impairment is common following stroke. This paper presents an actuated thumb exoskeleton (ATX) to facilitate research in examining motor control and hand rehabilitation. The ATX presented in this work aims to provide independent bi-directional actuation in each of the 5 degrees-of-freedom (DOF) of the thumb using a novel flexible shaft based mechanism that has 5 active DOF and 3 passive DOF. A prototype has been built and experiments have been conducted to measure the allowable workspace at the thumb and evaluate the kinematic and kinetic performance of the ATX. The experimental results show that the ATX is able to provide individual actuation at all 5 thumb joints with high joint velocity and torque capacities. Further improvement and future work are discussed.

Finger-thumb coupling contributes to exaggerated thumb flexion in stroke survivors.

The purpose of this study was to investigate altered finger-thumb coupling in individuals with chronic hemiparesis poststroke. First, an external device stretched finger flexor muscles by passively rotating the metacarpophalangeal (MCP) joints. Subjects then performed isometric finger or thumb force generation. Forces/torques and electromyographic signals were recorded for both the thumb and finger muscles. Stroke survivors with moderate (n = 9) and severe (n = 9) chronic hand impairment participated, along with neurologically intact individuals (n = 9). Stroke survivors exhibited strong interactions between finger and thumb flexors. The stretch reflex evoked by stretch of the finger flexors of stroke survivors led to heteronymous reflex activity in the thumb, while attempts to produce isolated voluntary finger MCP flexion torque/thumb flexion force led to increased and undesired thumb force/finger MCP torque production poststroke with a striking asymmetry between voluntary flexion and extension. Coherence between the long finger and thumb flexors estimated using intermuscular electromyographic correlations, however, was small. Coactivation of thumb and finger flexor muscles was common in stroke survivors, whether activation was evoked by passive stretch or voluntary activation. The coupling appears to arise from subcortical or spinal sources. Flexor coupling between the thumb and fingers seems to contribute to undesired thumb flexor activity after stroke and may impact rehabilitation outcomes.

Carryover effects of cyclical stretching of the digits on hand function in stroke survivors.

OBJECTIVE: To investigate the longevity and cumulative impact of multiple sessions of passive, cyclical stretching of the digits on hand function in subacute stroke survivors. DESIGN: Before-after trial with intervention repeated on 3 consecutive days. SETTING: Research laboratory. PARTICIPANTS: Individuals (N=27) with moderate to severe hand impairment, 2 to 6 months (subacute, n=12) and >7 months (chronic, n=15) poststroke. INTERVENTIONS: Subjects wore an actuated glove orthosis that cyclically moved their fingers and thumb from a relaxed/flexed posture into neutral extension for 30 minutes on 3 consecutive days. MAIN OUTCOME MEASURES: Three hand-specific tasks from the Graded Wolf Motor Function Test, Box and Block Test (BBT), grip strength, and lateral pinch strength. Recordings were taken before stretching and at 3 time points, each separated by 30 minutes after completion of stretching on each day. RESULTS: Significant improvement was observed immediately after the stretching for both groups. Improvements in the subacute group were largely maintained up to 1 hour poststretching, with significant carryover from day to day for some outcomes measures such as the BBT (P=.006) and grip strength (P=.012). In contrast, improvements after stretching for the chronic group were transient, with the changes largely dissipating over time and no significant cumulative effect across days. CONCLUSIONS: Cyclical stretching of the digits had a lasting and reinforcing effect on improving hand motor control for subacute stroke survivors. Incorporation of cyclical stretching before active hand therapy may prove to be a beneficial treatment for stroke survivors, especially during the subacute phase of recovery.

Training finger individuation with a mechatronic-virtual reality system leads to improved fine motor control post-stroke.

BACKGROUND: Dexterous manipulation of the hand, one of the features of human motor control, is often compromised after stroke, to the detriment of basic functions. Despite the importance of independent movement of the digits to activities of daily living, relatively few studies have assessed the impact of specifically targeting individuated movements of the digits on hand rehabilitation. The purpose of this study was to investigate the impact of such finger individuation training, by means of a novel mechatronic-virtual reality system, on fine motor control after stroke. METHODS: An actuated virtual keypad (AVK) system was developed in which the impaired hand controls a virtual hand playing a set of keys. Creation of individuated digit movements is assisted by a pneumatically actuated glove, the PneuGlove. A study examining efficacy of the AVK system was subsequently performed. Participants had chronic, moderate hand impairment resulting from a single stroke incurred at least 6 months prior. Each subject underwent 18 hour-long sessions of extensive therapy (3x per week for 6 weeks) targeted at finger individuation. Subjects were randomly divided into two groups: the first group (Keypad: N = 7) utilized the AVK system while the other group (OT: N = 7) received a similarly intensive dose of occupational therapy; both groups worked directly with a licensed occupational therapist. Outcome measures such as the Jebsen-Taylor Hand Function Test (JTHFT), Action research Arm Test (ARAT), Fugl-Meyer Upper Extremity Motor Assessment/Hand subcomponent (FMUE/FMH), grip and pinch strengths were collected at baseline, post-treatment and one-month post-treatment. RESULTS: While both groups exhibited some signs of change after the training sessions, only the Keypad group displayed statistically significant improvement both for measures of impairment (FMH: p = 0.048) and measures of task performance (JTHFT: p = 0.021). Additionally, the finger individuation index - a measure of finger independence - improved only for the Keypad group after training (p = 0.05) in the subset (Keypad: N = 4; OT: N = 5) of these participants for which it was measured. CONCLUSIONS: Actively assisted individuation therapy comprised of non task-specific modalities, such as can be achieved with virtual platforms like the AVK described here, may prove to be valuable clinical tools for increasing the effectiveness and efficiency of therapy following stroke.

Design and Development of the Cable Actuated Finger Exoskeleton for Hand Rehabilitation Following Stroke.

Finger impairment following stroke results in significant deficits in hand manipulation and the performance of everyday tasks. While recent advances in rehabilitation robotics have shown promise for facilitating functional improvement, it remains unclear how best to employ these devices to maximize benefits. Current devices for the hand, however, lack the capacity to fully explore the space of possible training paradigms. Particularly, they cannot provide the independent joint control and levels of velocity and torque required. To fill this need, we have developed a prototype for one digit, the cable actuated finger exoskeleton (CAFE), a three-degree-of-freedom robotic exoskeleton for the index finger. This paper presents the design and development of the CAFE, with performance testing results.

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.

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.

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.

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.

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.

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.

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.

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.