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

Authors:
Jhun-Ying Yang;Yen-Ping Chen;Gwo-Yun Lee;Shun-Nan Liou;Jeen-Shing Wang
Affiliations:
Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan;Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan;Micro Systems Technology Research Laboratories, Industrial Technology Research Institute, Tainan, Taiwan;Micro Systems Technology Research Laboratories, Industrial Technology Research Institute, Tainan, Taiwan;Department of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan
Venue:
ICEC'07 Proceedings of the 6th international conference on Entertainment Computing
Year:
2007

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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.