A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs.

ABSTRACT: Surface electromyography (sEMG) is a signal consisting of different motor unit action potential trains and records from the surface of the muscles. One of the applications of sEMG is the estimation of muscle force. We proposed a new real-time convex and interpretable model for solving the sEMG-force estimation. We validated it on the upper limb during isometric voluntary flexions-extensions at 30%, 50%, and 70% Maximum Voluntary Contraction in five subjects, and lower limbs during standing tasks in thirty-three volunteers, without a history of neuromuscular disorders. Moreover, the performance of the proposed method was statistically compared with that of the state-of-the-art (13 methods, including linear-in-the-parameter models, Artificial Neural Networks and Supported Vector Machines, an

SUBMITTER: Shirzadi M 

PROVIDER: S-EPMC10009160 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature