Towards non-invasive and adaptive peripheral neural interfaces for stroke and spinal cord injury rehabilitation

Neurotechnologies or Neural Interface Technologies are rapidly revolutionising healthcare, as they hold promise of restoring functional (sensory, motor, involuntary) capacity of millions of people with disabilities or neurological disorders including people with spinal cord injury, stroke, cerebral palsy, multiple sclerosis etc. However, despite tremendous progress, many hurdles remain, including complications of employing invasive neurostimulation, poor understanding of underlying neurophysiological mechanisms and challenges with designing and implementing low power, precise neurostimulatory hardware. This research project aims to validate and develop an innovative approach to restore sensorimotor function in neurological population by using non-invasive vibrotactile stimuli as a neurostimulatory intervention, thus opening up a unique opportunity to develop targeted, non-invasive neurotechnology as well as to answer fundamental clinical and scientific questions. We propose to deliver precise frequencies, amplitudes and numbers of non-invasive and easy to deliver vibrotactile stimuli to targeted sensory endings of fingertips in stroke survivors and targeted leg muscles in spinal cord injury individuals, to improve their sensory and functional capabilities respectively. In particular, we aim to identify precise characteristics of vibration frequencies, amplitudes and stimulation locations which generate the most beneficial response in improving sensory and motor function in stroke and SCI individuals respectively. Equally importantly, due to its ability to provide detailed window into neuronal workings, we propose to use novel high density electromyography technique along with electrical stimulation to elucidate poorly understood neuronal mechanisms contributing to the: a) improvement of sensory function in the upper limbs of stroke and b) generation of involuntary muscle contractions (spasms) in SCI. These improved understanding of neuronal mechanisms combined with knowledge of most effective vibration or electrical stimuli will enable the development of highly effective restorative neurotechnologies. In future, leveraging the power of AI, may enable these neurotechnologies to become self-tuning or adaptive, based on sense, calibrate, stimulate approach thus delivering more personalised neurorehabilitation.