Locomotion classification using emg signal - A comparative study

Sarthak Pati, Deepak Joshi, Ashutosh Mishra

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

4 Citations (Scopus)

Abstract

This work gives a comparative study on the use of Linear Discriminant Analysis (LDA), Artificial Neural Network (ANN) and Naive-Bayes Classifier (NBC) for recognizing various locomotion modes using parameters derived from the transient EMG signals taken from healthy subjects and thus provide a better control mechanism for lower limb prosthesis. These classifiers have been taken into consideration owing to their extensive use in various realtion, time applications.

Original languageEnglish
Title of host publication2010 International Conference on Information and Emerging Technologies, ICIET 2010
DOIs
Publication statusPublished - 30-12-2010
Externally publishedYes
Event2nd International Conference on Information and Emerging Technologies, ICIET 2010 - Karachi, Pakistan
Duration: 14-06-201016-06-2010

Conference

Conference2nd International Conference on Information and Emerging Technologies, ICIET 2010
CountryPakistan
CityKarachi
Period14-06-1016-06-10

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems

Cite this

Pati, S., Joshi, D., & Mishra, A. (2010). Locomotion classification using emg signal - A comparative study. In 2010 International Conference on Information and Emerging Technologies, ICIET 2010 [5625677] https://doi.org/10.1109/ICIET.2010.5625677