An approach to the real-time surface electromyogram decomposition

Abstract

This paper studies a sequential decomposition method suitable for real-time separation of linear mixtures of finite-length signals. The signals are modelled as channel responses in a multiple-input multiple-output (MIMO) model, with positive pulse trains as channel inputs. Our decomposition method compensates the channel responses and aims to reconstruct the input pulse trains in real time. Tests on synthetic surface electromyograms (SEMG) show how well the proposed method performs, in comparison to its batch version, and how robust it is.