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Intelligent clothing for automated recognition of human physical activities in free-living environment
Wu, Yuchuan Chen, Ronghua Wang, Jin Sun, Xiangping She, Mary F. H.
Wu, Yuchuan
Chen, Ronghua
Wang, Jin
Sun, Xiangping
She, Mary F. H.
Abstract
This paper presents an intelligent clothing framework for human daily activity recognition using a single waist-worn tri-axial accelerometer sensor coupled with a robust pattern recognition system. The activity recognition algorithm is realized to distinguish six different physical activities through three major steps: acceleration signal collection/pre-processing, wavelet-based principle component analysis, and a support vector machine classifier. The proposed activity recognition method has been experimentally validated through two batches of trials with an overall mean classification accuracy of 95.25 and 94.87%, respectively. These results suggest that the intelligent clothing is not only able to learn the activity patterns but also capable of generalizing new data from both known and unknown subjects. This enables the proposed intelligent clothing to be applied in a comfortable and in situ assessment of human physical activities, which would open up new market segments to the textile industry.
Keywords
wearable, acceleration, signal, discrete wavelet transform
Date
2012
Type
Journal article
Journal
Journal of the Textile Institute
Book
Volume
103
Issue
8
Page Range
806-816
Article Number
ACU Department
Non-faculty
Collections
Relation URI
Source URL
Event URL
Open Access Status
License
File Access
Controlled