Robust EMG pattern recognition to muscular fatigue effect for human-machine interaction

Jae Hoon Song, Jin Woo Jung, Zeungnam Bien

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

The main goal of this paper is to design an electromyogram (EMG) pattern classifier which is robust to muscular fatigue effects for human-machine interaction. When a user operates some machines such as a PC or a powered wheelchair using EMG-based interface, muscular fatigue is generated by sustained duration time of muscle contraction. Therefore, recognition rates are degraded by the muscular fatigue. In this paper, an important observation is addressed: the variations of feature values due to muscular fatigue effects are consistent for sustained duration time. From this observation, a robust pattern classifier was designed through the adaptation process of hyperboxes of Fuzzy Min-Max Neural Network. As a result, significantly improved performance is confirmed.

Original languageEnglish
Title of host publicationMICAI 2006
Subtitle of host publicationAdvances in Artificial Intelligence - 5th Mexican International Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages1190-1199
Number of pages10
ISBN (Print)3540490264, 9783540490265
DOIs
StatePublished - 2006
Event5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence - Apizaco, Mexico
Duration: 13 Nov 200617 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4293 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence
Country/TerritoryMexico
CityApizaco
Period13/11/0617/11/06

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