Identification of Gesture Based on Combination of Raw sEMG and sEMG Envelope Using Supervised Learning and Univariate Feature Selection

• Published in: Journal of bionics engineering Vol. 16; no. 4; pp. 647 - 662
• Main Authors: Liang, Shili, Wu, Yansheng, Chen, Jianfei, Zhang, Ling, Chen, Peipei, Chai, Zongqian, Cao, Chunlei
• Format: Journal Article
• Language: English
• Published: Singapore Springer Singapore 01.07.2019
• Subjects: Artificial Intelligence; Biochemical Engineering; Bioinformatics; Biomaterials; Biomedical Engineering and Bioengineering; Biomedical Engineering/Biotechnology; Engineering; surface electromyography (sEMG); gesture identification; univariate feature selection; supervised learning; individual differences

In this paper, we propose a novel study for gesture identification using surface electromyography (sEMG) signal, and the raw sEMG signal and the sEMG envelope signal are collected by the sensor at the same time. An efficient method of gesture identification based on the combination of two signals us...