An Experimental Investigation Comparing Age-Specific and Mixed-Age Models for Wearable Assisted Activity Recognition in Women

Pratool Bharti, Arup Kanti Dey, Sriram Chellappan, Theresa Beckie

2019

Abstract

In this paper, we investigate the impact of age diversity on accuracy for activity recognition among women with wrist-worn wearables. Using a sample of 10 elder women and 10 younger women, and by monitoring five activities related to cardiac care (Running, Brisk Walking, Walking, Standing and Sitting), we show that while personalized models are best, activities classification based on age specific models are definitely superior in terms of accuracy compared to classification using mixed age models. We do so by a) extracting 11 features from inertial sensing data; b) reducing dimensionality using Linear Discriminant Analysis methods; c) quantifying variance among features using Principal Component Analysis; d) clustering activities; and finally e) comparing classification accuracies of all activities for personalized, age-specific and mixed-age models. We believe that our study is unique, and potentially important for superior healthcare for women, a demographic that is largely underserved today across the world.

Paper Citation

in Harvard Style

Bharti P., Dey A., Chellappan S. and Beckie T. (2019). An Experimental Investigation Comparing Age-Specific and Mixed-Age Models for Wearable Assisted Activity Recognition in Women. In Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5: HEALTHINF; ISBN 978-989-758-353-7, SciTePress, pages 367-374. DOI: 10.5220/0007398003670374

in Bibtex Style

@conference{healthinf19,
author={Pratool Bharti and Arup Kanti Dey and Sriram Chellappan and Theresa Beckie},
title={An Experimental Investigation Comparing Age-Specific and Mixed-Age Models for Wearable Assisted Activity Recognition in Women},
booktitle={Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5: HEALTHINF},
year={2019},
pages={367-374},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007398003670374},
isbn={978-989-758-353-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019) - Volume 5: HEALTHINF
TI - An Experimental Investigation Comparing Age-Specific and Mixed-Age Models for Wearable Assisted Activity Recognition in Women
SN - 978-989-758-353-7
AU - Bharti P.
AU - Dey A.
AU - Chellappan S.
AU - Beckie T.
PY - 2019
SP - 367
EP - 374
DO - 10.5220/0007398003670374
PB - SciTePress