Sensing and decoding the neural drive to paralyzed muscles during attempted movements of a person with tetraplegia using a sleeve array
Jordyn E. Ting, Alessandro Del Vecchio, Devapratim Sarma, Nikhil Verma, Samuel C. Colachis, Nicholas V. Annetta, Jennifer L. Collinger, Dario Farina, Douglas J. Weber
Abstract
A wearable electrode array and machine learning methods were used to record and decode myoelectric signals and motor unit firing in paralyzed muscles of a person with motor complete tetraplegia. The myoelectric activity and motor unit firing rates were task specific, even in the absence of visible motion, enabling accurate classification of attempted single-digit movements. This wearable system has the potential to enable people with tetraplegia to control assistive devices through movement intent.
Topics & Concepts
TetraplegiaPhysical medicine and rehabilitationComputer scienceMotor unitWearable computerElectromyographyTask (project management)NeuroprostheticsNeurosciencePsychologyMedicineSpinal cordSpinal cord injuryEngineeringSystems engineeringEmbedded systemMuscle activation and electromyography studiesEEG and Brain-Computer InterfacesGaze Tracking and Assistive Technology