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.
