Force estimation based on sEMG using wavelet analysis and neural network

Du Jiang, Gongfa Li, Guozhang Jiang, Disi Chen, Zhaojie Ju

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

For further improving the action of sEMG in human-robot interaction, wavelet and neural network is utilized in prediction of grip force. Firstly, it is described based on the introduction platform how to gain sEMG as well as its traditional features. Then, the wavelet decomposition and reconstruction algorithm is used to analyze the sEMG signals and extract the corresponding energy characteristics. Different grasp force of and sEMG signals are collected simultaneously whose feature matrix is used in training model. Those are evaluated by root mean square error, whose results show that RMSE = 1.0 ± 0.4 of BP network and RMSE = 1.8 ± 0.5 of LSTM model.
Original languageEnglish
Title of host publication2019 9th International Conference on Information Science and Technology (ICIST)
PublisherIEEE
Pages320-326
Number of pages7
ISBN (Electronic)978-1-7281-2106-2
ISBN (Print)978-1-7281-2107-9
DOIs
Publication statusPublished - 16 Sep 2019
Event2019 9th International Conference on Information Science and Technology - Hulunbuir, China
Duration: 2 Aug 20195 Aug 2019

Publication series

Name9th International Conference on Information Science and Technology (ICIST)
PublisherIEEE
ISSN (Print)2573-3311

Conference

Conference2019 9th International Conference on Information Science and Technology
Country/TerritoryChina
CityHulunbuir
Period2/08/195/08/19

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