Soft-Wearable Device for the Estimation of Shoulder Orientation and Gesture (original) (raw)

2020

Abstract

This study presents the development of a wearable device that merges capacitive soft-flexion and surface electromyography (sEMG) sensors for the estimation of shoulder orientation and movement, evaluating five natural movement gestures of the human arm. The use of Time Series Networks (TSN) to estimate the arm orientation, and a pattern recognition method for the estimation of the classification of the gesture are proposed. It is demonstrated that it is possible to know the orientation of the shoulder, and that the algorithm is capable of recognising the five gestures proposed with two different configurations. The study is performed on people who reported healthy upper limbs.

Miguel Angel Sánchez Urán hasn't uploaded this paper.

Let Miguel Angel Sánchez know you want this paper to be uploaded.

Ask for this paper to be uploaded.