A Long Short Term Memory Network Based on Surface Electromyography for Continuous Estimation of Elbow Joint Angle

Abstract

A simple long short term memory (LSTM) network is built to estimate the model which is described the relationship between the elbow joint angle and the surface electromyography (sEMG) signals in this paper. The sEMG time series of biceps and triceps are the inputs of the model, and the elbow joint angle is the output of the model. The sEMG signals while the user is performing flexion and extension movements are collected by Biopac. Elbow joint angle is measured by angle sensor. The results show that for simple flexion and extension movements, the model is able to eatimate the movement intention of the elbow.