There are over 7 million stroke survivors in the US alone, with approximately 795,000 new cases annually. Despite the best available physiotherapy, 30-60% of stroke survivors remain affected by gait function impairments, with foot drop often being the primary cause. Given that post-stroke gait impairments remain suboptimally addressed, novel methods that can provide lasting neurological and functional improvements are necessary. Brain-computer interface (BCI) technology may be one such novel approach. BCI technology enables ?direct brain control? of external devices such as assistive devices and prostheses by translating brain electrophysiologi- cal signals (e.g. EEG) into control signals. When BCI systems are integrated with functional electrical stimulation (FES) systems, they can be used to deliver a novel physiotherapy to improve motor function after stroke. BCI- FES systems are hypothesized to stimulate a Hebbian plasticity process (where ?neurons that ?re together, wire together?), and this approach may lead to functional recovery after stroke beyond that of conventional physiother- apy. The applicant's preliminary research indicates that applying this technique to foot drop after stroke is safe and may improve gait function via neural processes. Hence, this warrants further investigation to: 1. determine if BCI-FES therapy can provide lasting gains in gait function in chronic stroke patients with foot drop; 2. determine what factors in?uence BCI-FES therapy; and 3. explicitly elucidate the underlying neural repair mechanisms. First, a Phase II clinical trial in patients with foot drop due to chronic stroke will compare the effect of BCI- FES dorsi?exion therapy to that of dose- and intensity-matched standard physiotherapy (Aim 1). Comparing the improvement in gait velocity and other secondary outcome measures between the two groups will test the hypothesis that BCI-FES therapy provides functional and neurological gains beyond those of conventional phys- iotherapy. It will also determine which aspects of gait impairment are best addressed with BCI-FES therapy versus conventional physiotherapy. The relationship between the subjects' baseline characteristics (gait velocity, dorsi?exion function, motor evoked potentials, electroencephalogram features, sensation) and the outcomes will determine what features in?uence responsiveness to BCI-FES dorsi?exion therapy (Aim 2). Finally, the underlying mechanism driving the neurological improvements of BCI-FES will be elucidated using an explicit computational neuroscience model of stroke recovery, informed by experimental neurophysiological measurements (Aim 3). Determining that BCI-FES therapy can provide improvements beyond that of conventional therapy may lead to a new neural repair mechanism that can be effective in stroke patients. This mechanism can inform the design of future physiotherapy techniques or improve current ones. Finally, BCI-FES therapy may ultimately become a novel form of physiotherapy to reduce post-stroke disability, and in turn reduce the public health burden of stroke.
Brain-computer interface-controlled functional electrical stimulation technology may be used as a new rehabilitation method to improve walking after stroke. If effective, the technology will help decrease disability after stroke. The decreased disability will in turn improve quality of life, reduce the long-term cost of post-stroke care, and subsequently reduce the public health burden caused by stroke.
