Identifying at-risk university students: A system for longitudinal monitoring of sleep health

Iva Bojic; Jintana Liu; Qi Chwen Ong; Ashwini Lawate; Malar Palaiyan; May Lwin; John Abisheganaden; Yin Leng Theng; Moon Ho Ringo Ho; Michael Yong Hwa Chia; Josip Car

doi:10.1109/ICDH60066.2023.00029

Identifying at-risk university students: A system for longitudinal monitoring of sleep health

Iva Bojic^*, Jintana Liu, Qi Chwen Ong, Ashwini Lawate, Malar Palaiyan, May Lwin, John Abisheganaden, Yin Leng Theng, Moon Ho Ringo Ho, Michael Yong Hwa Chia, Josip Car

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A significant percentage of university students reported poor sleep quality due to various factors. This affects their academic performance, mental well-being, and overall health. To address this, we propose a real-time monitoring system that can effectively identify students at risk of poor sleep quality. Our system utilizes two modes of continuous data collection (i.e., consumer-grade wearables and sleep diary) to inform both students and university well-being centers about sleep quality characteristics over the past week. Incorporating both subjective and objective measures facilitates a more holistic appraisal of sleep quality. We conducted a validation study in which we collected sleep health data from university students for four weeks to show how the proposed system could be implemented. The results of our study showed that it is feasible to implement the proposed system, although no agreement between the two modes of data collection was found. This calls for future research efforts aimed at devising a composite metric that harmoniously combines these two modes.

Original language	English
Title of host publication	Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023
Editors	Carl K. Chang, Rong N. Chang, Jing Fan, Geoffrey C. Fox, Zhi Jin, Graziano Pravadelli, Hossain Shahriar
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	143-149
Number of pages	7
ISBN (Electronic)	9798350341034
DOIs	https://doi.org/10.1109/ICDH60066.2023.00029
Publication status	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Digital Health, ICDH 2023 - Hybrid, Chicago, United States Duration: Jul 2 2023 → Jul 8 2023

Publication series

Name	Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023

Conference

Conference	2023 IEEE International Conference on Digital Health, ICDH 2023
Country/Territory	United States
City	Hybrid, Chicago
Period	7/2/23 → 7/8/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus Subject Areas

Signal Processing
Health Informatics

Keywords

consumer-grade wearables
Fitbit
sleep assessment
sleep diary
sleep quality
university wellbeing center

Access to Document

10.1109/ICDH60066.2023.00029

Cite this

Bojic, I., Liu, J., Ong, Q. C., Lawate, A., Palaiyan, M., Lwin, M., Abisheganaden, J., Theng, Y. L., Ho, M. H. R., Chia, M. Y. H., & Car, J. (2023). Identifying at-risk university students: A system for longitudinal monitoring of sleep health. In C. K. Chang, R. N. Chang, J. Fan, G. C. Fox, Z. Jin, G. Pravadelli, & H. Shahriar (Eds.), Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023 (pp. 143-149). (Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDH60066.2023.00029

Bojic, Iva ; Liu, Jintana ; Ong, Qi Chwen et al. / Identifying at-risk university students : A system for longitudinal monitoring of sleep health. Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023. editor / Carl K. Chang ; Rong N. Chang ; Jing Fan ; Geoffrey C. Fox ; Zhi Jin ; Graziano Pravadelli ; Hossain Shahriar. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 143-149 (Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023).

@inproceedings{737eac5f5aff41e2bac609dd9a800c75,

title = "Identifying at-risk university students: A system for longitudinal monitoring of sleep health",

abstract = "A significant percentage of university students reported poor sleep quality due to various factors. This affects their academic performance, mental well-being, and overall health. To address this, we propose a real-time monitoring system that can effectively identify students at risk of poor sleep quality. Our system utilizes two modes of continuous data collection (i.e., consumer-grade wearables and sleep diary) to inform both students and university well-being centers about sleep quality characteristics over the past week. Incorporating both subjective and objective measures facilitates a more holistic appraisal of sleep quality. We conducted a validation study in which we collected sleep health data from university students for four weeks to show how the proposed system could be implemented. The results of our study showed that it is feasible to implement the proposed system, although no agreement between the two modes of data collection was found. This calls for future research efforts aimed at devising a composite metric that harmoniously combines these two modes.",

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author = "Iva Bojic and Jintana Liu and Ong, {Qi Chwen} and Ashwini Lawate and Malar Palaiyan and May Lwin and John Abisheganaden and Theng, {Yin Leng} and Ho, {Moon Ho Ringo} and Chia, {Michael Yong Hwa} and Josip Car",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Digital Health, ICDH 2023 ; Conference date: 02-07-2023 Through 08-07-2023",

year = "2023",

doi = "10.1109/ICDH60066.2023.00029",

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series = "Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023",

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pages = "143--149",

editor = "Chang, {Carl K.} and Chang, {Rong N.} and Jing Fan and Fox, {Geoffrey C.} and Zhi Jin and Graziano Pravadelli and Hossain Shahriar",

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Bojic, I, Liu, J, Ong, QC, Lawate, A, Palaiyan, M, Lwin, M, Abisheganaden, J, Theng, YL, Ho, MHR, Chia, MYH & Car, J 2023, Identifying at-risk university students: A system for longitudinal monitoring of sleep health. in CK Chang, RN Chang, J Fan, GC Fox, Z Jin, G Pravadelli & H Shahriar (eds), Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023. Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023, Institute of Electrical and Electronics Engineers Inc., pp. 143-149, 2023 IEEE International Conference on Digital Health, ICDH 2023, Hybrid, Chicago, United States, 7/2/23. https://doi.org/10.1109/ICDH60066.2023.00029

Identifying at-risk university students: A system for longitudinal monitoring of sleep health. / Bojic, Iva; Liu, Jintana; Ong, Qi Chwen et al.
Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023. ed. / Carl K. Chang; Rong N. Chang; Jing Fan; Geoffrey C. Fox; Zhi Jin; Graziano Pravadelli; Hossain Shahriar. Institute of Electrical and Electronics Engineers Inc., 2023. p. 143-149 (Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Identifying at-risk university students

T2 - 2023 IEEE International Conference on Digital Health, ICDH 2023

AU - Bojic, Iva

AU - Liu, Jintana

AU - Ong, Qi Chwen

AU - Lawate, Ashwini

AU - Palaiyan, Malar

AU - Lwin, May

AU - Abisheganaden, John

AU - Theng, Yin Leng

AU - Ho, Moon Ho Ringo

AU - Chia, Michael Yong Hwa

AU - Car, Josip

PY - 2023

Y1 - 2023

N2 - A significant percentage of university students reported poor sleep quality due to various factors. This affects their academic performance, mental well-being, and overall health. To address this, we propose a real-time monitoring system that can effectively identify students at risk of poor sleep quality. Our system utilizes two modes of continuous data collection (i.e., consumer-grade wearables and sleep diary) to inform both students and university well-being centers about sleep quality characteristics over the past week. Incorporating both subjective and objective measures facilitates a more holistic appraisal of sleep quality. We conducted a validation study in which we collected sleep health data from university students for four weeks to show how the proposed system could be implemented. The results of our study showed that it is feasible to implement the proposed system, although no agreement between the two modes of data collection was found. This calls for future research efforts aimed at devising a composite metric that harmoniously combines these two modes.

AB - A significant percentage of university students reported poor sleep quality due to various factors. This affects their academic performance, mental well-being, and overall health. To address this, we propose a real-time monitoring system that can effectively identify students at risk of poor sleep quality. Our system utilizes two modes of continuous data collection (i.e., consumer-grade wearables and sleep diary) to inform both students and university well-being centers about sleep quality characteristics over the past week. Incorporating both subjective and objective measures facilitates a more holistic appraisal of sleep quality. We conducted a validation study in which we collected sleep health data from university students for four weeks to show how the proposed system could be implemented. The results of our study showed that it is feasible to implement the proposed system, although no agreement between the two modes of data collection was found. This calls for future research efforts aimed at devising a composite metric that harmoniously combines these two modes.

KW - consumer-grade wearables

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KW - sleep assessment

KW - sleep diary

KW - sleep quality

KW - university wellbeing center

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U2 - 10.1109/ICDH60066.2023.00029

DO - 10.1109/ICDH60066.2023.00029

M3 - Conference contribution

AN - SCOPUS:85172349159

T3 - Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023

SP - 143

EP - 149

BT - Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023

A2 - Chang, Carl K.

A2 - Chang, Rong N.

A2 - Fan, Jing

A2 - Fox, Geoffrey C.

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 2 July 2023 through 8 July 2023

ER -

Bojic I, Liu J, Ong QC, Lawate A, Palaiyan M, Lwin M et al. Identifying at-risk university students: A system for longitudinal monitoring of sleep health. In Chang CK, Chang RN, Fan J, Fox GC, Jin Z, Pravadelli G, Shahriar H, editors, Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 143-149. (Proceedings - 2023 IEEE International Conference on Digital Health, ICDH 2023). doi: 10.1109/ICDH60066.2023.00029

Identifying at-risk university students: A system for longitudinal monitoring of sleep health

Abstract

Publication series

Conference

Bibliographical note

ASJC Scopus Subject Areas

Keywords

Access to Document

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Cite this