Cognitive-based Prosthetics to Improve Grasp and Reaching After SCI

Cognitive-based Rehabilitation Platform of Hand Grasp After Spinal Cord Injury Using Virtual Reality and Instrumented Wearables

Rehabilitation of functional movements after spinal cord injury (SCI) requires commitment and engagement to the processes of physical therapy. Outcomes may be improved by techniques that strengthen cognitive connections between users and physical therapy exercises. The investigators will investigate combinations of virtual reality and innovative wearable technology to accelerate rehabilitation of hand grasp and reach. These devices use multi-sensory feedback to enhance the sense of agency, or feelings of control, and better train movements during physical rehabilitation exercises. The investigators will measure the effect of these devices on improving the speed, efficiency, and accuracy of performed movements in Veterans with SCI.

Spinal cord injury (SCI) at the cervical level impairs hand function severely compromises performance of activities of daily living. The physical rehabilitation process requires commitment by the participant to achieve meaningful gains in function. Rehabilitation approaches that are cognitively engaging can facilitate greater commitment to practice and improved movement learning. The investigators propose to develop innovative platforms that utilize virtual reality (VR) and instrumented wearables that enhance cognitive factors during motor learning of hand grasp and reach after SCI. These factors include greater sense of agency, or perception of control, and multi-sensory feedback. Sense of agency is implicated with greater movement control, and various sensory feedback modalities (visual, audio, and haptic) are proven effective in movement training. However, these factors are not well considered in traditional physical therapy approaches. The investigators have developed two novel cognitive-based platforms for rehabilitating grasp and reach function and propose to test each platform in Veterans with chronic SCI at the cervical level. Aim 1 will investigate how the "cognition" glove may improve functional grasp. This glove includes force and flex sensors that provide inputs to a machine learning algorithm trained to predict when secure grasp is achieved. The glove alerts the user of secure grasp through onboard sensory modules providing visual (LED), audio (beeper), and tactile (vibrator) feedback. During training, feedback is provided at gradually shorter time-intervals to progressively induce agency based on the neuroscience principle of 'intentional binding'. This principle suggests that with greater agency, one perceives their action (i.e., secure grasp) is more coupled in time to a sensory consequence (i.e., glove feedback). The glove is user-ready, and now has compatibility with customized VR applications to provide enhanced sensory feedback through engaging and customized visual and sound alerts. The investigators hypothesize that enhanced feedback in VR will produce even greater improvements in grasp performance than onboard feedback alone. Aim 2 will investigate how Veterans with SCI may learn greater arm muscle control during virtual reaching while using a "sensory" brace that provides isometric resistance to one arm to elicit electromyography (EMG) patterns that can drive a virtual arm. The person receives visual feedback from VR and muscle tendon haptic feedback from the brace during training. Tendon stimulation can elicit movement sensations that modulate muscle activation patterns. The VR feedback will provide conscious movement training cues while vibration feedback will subconsciously elicit more distinct EMG patterns based on cluster analysis. The investigators hypothesize that the promotion of distinct EMG patterns, achieved by maximizing inter-cluster distances, will improve performance of a reach-to-touch task. Importantly, the concept of strengthening cognitive agency and learning of movement using wearable technology, multi-sensory feedback, and virtual reality during physical training will be applicable to all forms of neuromuscular impairment, including stroke and traumatic brain injury in addition to SCI.

At each visit, prototype cognitive prosthetic devices will be tested under 3 conditions: No feedback, simple feedback, and enhanced feedback. Outcomes will include time taken for successful movements; and accuracy of movements.

The investigators have developed and tested a functional prototype of an instrumented glove to alert the user about secure grasp of objects. Onboard force and flex sensors provide inputs to a machine learning algorithm (artificial neural network, ANN) to estimate secure grasp based on previously collected training data. The glove enhances agency by alerting the user to secure grasp through sensory feedback modules (visual - LED, audio - beeper, tactile - vibrator).

A a size- and position-adjustable arm brace with weight-support capability and housing for vibration motors and EMG sensors. Position adjustment allows for physical therapists to find and recommend arm postures that are clinically relevant to each person. The participant can then isometrically push/resist against the brace to strengthen target muscles while performing VR reach-to-touch. The person will receive visual feedback from the virtual environment to train movement performance and vibrotactile feedback at tendons to subconsciously adjust their muscle activation patterns

Inclusion Criteria: SCI occurred greater than 12 months ago SCI occurred between levels C1-T1 Hand weakness: score of 2, 3, or 4 out of 5 on manual muscle testing of finger extension, finger flexion, or finger abduction in either hand Exclusion Criteria: History of other serious brain or spinal cord injuries History of seizures Ventilator dependence; open tracheostomy Use of medications that significantly lower seizure threshold History of significant cognitive deficits Open skin lesions over the face, neck, shoulders, arms, or hands Pregnancy

A Limited Dataset (LDS) will be shared in electronic format pursuant to a VA-approved Data Use Agreement. This will include all outcomes data and deidentified demographics. Individually Identifiable Data will be shared pursuant to valid HIPAA Authorization, Informed Consent, and an appropriate written agreement limiting use of the data to the conditions as described in the authorization and consent, and a written assurance from the recipient that the information will be maintained in accordance with the security requirements of 38 CFR Part 1.466.

Individually Identifiable Data will be shared pursuant to valid HIPAA Authorization, Informed Consent, and an appropriate written agreement limiting use of the data to the conditions as described in the authorization and consent, and a written assurance from the recipient that the information will be maintained in accordance with the security requirements of 38 CFR Part 1.466.