CLUSTERING OF EMG GAIT PATTERN WITH TEMPORAL FEATURE.

Jia-Jin Chen, R. G. Shiavi

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

Abstract

A technique for automatic clustering of the linear envelope of the EMG during gait has been developed which uses a temporal feature representation and maximum peak matching scheme. This technique provides a viable way to define compact and meaningful EMG waveform features. The envelope matching is performed by dynamic programming, providing qualitatively the largest numbers of matched peaks and quantitatively minimum distance measurement. The resulting averaged EMG profiles have low statistical variation and can serve as templates for EMG comparison and classification.

Original languageEnglish
Title of host publicationIEEE/Engineering in Medicine and Biology Society Annual Conference
PublisherIEEE
Pages614-617
Number of pages4
Publication statusPublished - 1986

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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