Intelligent clothing for automated recognition of human physical activities in free-living environment

Journal article

Wu, Yuchuan, Chen, Ronghua, Wang, Jin, Sun, Xiangping and She, Mary F. H.. (2012). Intelligent clothing for automated recognition of human physical activities in free-living environment. Journal of the Textile Institute. 103(8), pp. 806 - 816. https://doi.org/10.1080/00405000.2011.611641
AuthorsWu, Yuchuan, Chen, Ronghua, Wang, Jin, Sun, Xiangping and 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.

Keywordswearable; acceleration; signal; discrete wavelet transform
Year2012
JournalJournal of the Textile Institute
Journal citation103 (8), pp. 806 - 816
PublisherTextile Institute
ISSN0040-5000
Digital Object Identifier (DOI)https://doi.org/10.1080/00405000.2011.611641
Scopus EID2-s2.0-84863843687
Page range806 - 816
Research GroupInstitute for Learning Sciences and Teacher Education (ILSTE)
Publisher's version
File Access Level
Controlled
Place of publicationUnited Kingdom
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