Relative confidence based information fusion for Semg-based pattern recognition

Jinrong Li, Yinfeng Fang, Yong Ning, Jing Jie, Ping Tan, Honghai Liu

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

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Abstract

This study aims to establish a decision fusion scheme that synthesize the advantages of different classifiers and avoids uncertain decisions. Thus, relative confidence factors of each classifier was proposed to correct the classification decision made by each classifier, and the final classification result was derived by fusing all corrected decision based on the combination of Dempster-Shafer's rule. The novel fusion scheme is evaluated in the scenario of sEMG-based hand movement identification, in which five classffiers are adopted. The experimental results demonstrated that the novel scheme can obtain higher classification accuracy and stability than the other methods.
Original languageEnglish
Title of host publication 2018 International Conference on Machine Learning and Cybernetics
Subtitle of host publicationICMLC
PublisherIEEE
Pages625-630
ISBN (Electronic)978-1-5386-5214-5
ISBN (Print)978-1-5386-5215-2
DOIs
Publication statusPublished - 12 Nov 2018
Event2018 International Conference on Machine Learning and Cybernetics - http://www.icmlc.com/icmlc/welcome.html, Chengdu, China
Duration: 15 Jul 201818 Jul 2018

Publication series

NameIEEE ICMLC Proceedings Series
PublisherIEEE
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Conference

Conference2018 International Conference on Machine Learning and Cybernetics
Abbreviated titleICMLC 2018
Country/TerritoryChina
CityChengdu
Period15/07/1818/07/18

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