A real-time surface EMG decomposition system for non-invasive human-machine interfaces

Abstract

Real-time surface EMG decomposition, to extract neural activity of spinal motor neurons, provides a non-invasive solution for establishing direct interfaces with the central nervous system. In this paper, we present a real-time EMG decomposition system, validate it through both synthetic and experimental high-density surface EMG (HD-sEMG) data, and demonstrate the system in an upper-limb prosthetic control scenario. The proposed system achieves (in real-time) median decomposition accuracy comparable to offline methods (within 0.5 %) with minimal utilisation of computational resources (x20 faster compared to the literature).