Activity recognition using one triaxial accelerometer: A neuro-fuzzy classifier with feature reduction

Jhun Ying Yang, Yen Ping Chen, Gwo Yun Lee, Shun Nan Liou, Jeen Shing Wang

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

53 Citations (Scopus)

Abstract

This paper presents a neuro-fuzzy classifer for activity recognition using one triaxial accelerometer and feature reduction approaches. We use a triaxial accelerometer to acquire subjects' acceleration data and train the neurofuzzy classifier to distinguish different activities/movements. To construct the neuro-fuzzy classifier, a modified mapping-constrained agglomerative clustering algorithm is devised to reveal a compact data configuration from the acceleration data. In addition, we investigate two different feature reduction methods, a feature subset selection and linear discriminate analysis. These two methods are used to determine the significant feature subsets and retain the characteristics of the data distribution in the feature space for training the neuro-fuzzy classifier. Experimental results have successfully validated the effectiveness of the proposed classifier.

Original languageEnglish
Title of host publicationEntertainment Computing - ICEC 2007 - 6th International Conference, Proceedings
EditorsLizhuang Ma, Matthias Rauterberg, Ryohei Nakatsu
PublisherSpringer Verlag
Pages395-400
Number of pages6
ISBN (Print)3540748725, 9783540748724
DOIs
Publication statusPublished - 2007
Event6th International Conference of Entertainment Computing, ICEC 2007 - Shanghai, China
Duration: 2007 Sep 152007 Sep 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4740 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference of Entertainment Computing, ICEC 2007
CountryChina
CityShanghai
Period07-09-1507-09-17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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