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Authors: Hoang Nhung 1 and Zilu Liang 1 ; 2

Affiliations: 1 Ubiquitous and Personal Computing Lab, Kyoto University of Advanced Science (KUAS), 621-8555 Kyoto, Japan ; 2 Institute of Industrial Science, The University of Tokyo, 113-8654 Tokyo, Japan

Keyword(s): Data Mining, Personal Informatics, Ubiquitous Computing, Contrast Set Mining.

Abstract: Prior studies have suggested potential associations between poor sleep and glucose dysregulation among diabetic patients. However, little is known about the relationship between sleep and glucose regulation in healthy populations. In this study, we proposed a data mining pipeline based on contrast set mining to identify significant associations between sleep and glucose in a dataset collected from a normoglycemic population in free-living environments. Unlike traditional correlation analysis, our approach does not assume a linear relationship between sleep and glucose and can potentially discover associations when a pair of metrics fall within certain value ranges. The data mining result highlights the total sleep time as an important sleep metric associated with glucose regulation the next day, which is characterised by rules with high lift and confidence. Furthermore, the result suggests that having a higher time ratio in normal glucose range was associated with better sleep contin uity at night. These results may provide insights that people can immediately act on for better sleep and better glucose control. Future research may leverage the proposed data mining protocol to develop healthy behaviour recommender systems. (More)

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Paper citation in several formats:
Nhung, H. and Liang, Z. (2023). Contrast Set Mining for Actionable Insights into Associations Between Sleep and Glucose in a Normoglycemic Population. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF; ISBN 978-989-758-631-6; ISSN 2184-4305, SciTePress, pages 522-529. DOI: 10.5220/0011783600003414

@conference{healthinf23,
author={Hoang Nhung. and Zilu Liang.},
title={Contrast Set Mining for Actionable Insights into Associations Between Sleep and Glucose in a Normoglycemic Population},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF},
year={2023},
pages={522-529},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011783600003414},
isbn={978-989-758-631-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - HEALTHINF
TI - Contrast Set Mining for Actionable Insights into Associations Between Sleep and Glucose in a Normoglycemic Population
SN - 978-989-758-631-6
IS - 2184-4305
AU - Nhung, H.
AU - Liang, Z.
PY - 2023
SP - 522
EP - 529
DO - 10.5220/0011783600003414
PB - SciTePress

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