A Virtual Reality Muscle–Computer Interface for Neurorehabilitation in Chronic Stroke: A Pilot Study

Abstract

<jats:p>Severe impairment of limb movement after stroke can be challenging to address in the chronic stage of stroke (e.g., greater than 6 months post stroke). Recent evidence suggests that physical therapy can still promote meaningful recovery after this stage, but the required high amount of therapy is difficult to deliver within the scope of standard clinical practice. Digital gaming technologies are now being combined with brain–computer interfaces to motivate engaging and frequent exercise and promote neural recovery. However, the complexity and expense of acquiring brain signals has held back widespread utilization of these rehabilitation systems. Furthermore, for people that have residual muscle activity, electromyography (EMG) might be a simpler and equally effective alternative. In this pilot study, we evaluate the feasibility and efficacy of an EMG-based variant of our REINVENT virtual reality (VR) neurofeedback rehabilitation system to increase volitional muscle activity while reducing unintended co-contractions. We recruited four participants in the chronic stage of stroke recovery, all with severely restricted active wrist movement. They completed seven 1-hour training sessions during which our head-mounted VR system reinforced activation of the wrist extensor muscles without flexor activation. Before and after training, participants underwent a battery of clinical and neuromuscular assessments. We found that training improved scores on standardized clinical assessments, equivalent to those previously reported for brain–computer interfaces. Additionally, training may have induced changes in corticospinal communication, as indexed by an increase in 12–30 Hz corticomuscular coherence and by an improved ability to maintain a constant level of wrist muscle activity. Our data support the feasibility of using muscle–computer interfaces in severe chronic stroke, as well as their potential to promote functional recovery and trigger neural plasticity.</jats:p>

Development of a Low-Cost, Modular Muscle–Computer Interface for At-Home Telerehabilitation for Chronic Stroke

“…We selected the current approach for its simplicity, low computational requirements, and its ability to capture the relationship of two antagonistic muscles. As noted above and mentioned in our previous work [ 20 ], we expect that using this ratio is advantageous to encourage wrist extension without simultaneous unintended wrist flexion. For each trial, a score is assigned as a function of the ER value and a probability likelihood as shown in Table 1 .…”

“…In a previous study, we showed that it is feasible to use a research-grade EMG acquisition system to train the activity of agonist muscles while avoiding the simultaneous activity of antagonists via EMG biofeedback [ 20 ]. Here, we showed that these ratios of muscle activity can be acquired in an individual with stroke using low-cost sensors.…”

“…Finally, although we showed moderate improvements in coordinated muscle activity, that is, reduced antagonist activation during attempted agonist activation, our reinforcement paradigm could be enhanced with improved in-game feedback. For example, in the future, we may incorporate adaptive control thresholds to encourage more individuated activity on a personalized basis, in a similar fashion to our previous work [ 20 ].…”

“…This is advantageous for continued development since different configurations of sensors, processing pipelines, and environments can be implemented without necessitating updates to other modules. Specifically, while we only tested EMG biofeedback on a laptop screen in the current study, the system builds on the modular architecture we developed in previous work, allowing for the input of electroencephalography or movement data, and visual output to either a laptop screen or HMD-VR system as well as proprioceptive feedback via handheld controllers [ 19 , 20 ]. Additionally, we incorporated a NeuroPype script (Intheon, San Diego, CA, USA) for real-time visualization of the digitized EMG signals.…”

“…To address these needs, we developed and tested a low-cost, portable telerehabilitation biofeedback system called Tele-REINVENT. Tele-REINVENT builds upon our previous work in which we developed and tested a system (REINVENT) that could provide biofeedback of brain or muscle activity on a computer screen or in immersive virtual reality (VR) with a head-mounted display (HMD) in a laboratory or clinic setting [ 19 , 20 ]. Tele-REINVENT uses the same modular platform and incorporates a telerehabilitation component for live video and audio conferencing with a clinician who meets regularly with the participant to monitor progress.…”