Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder

Sang Ho Lee; Sanghun Yun; Jinung An; Dong Ha Lee

doi:10.1109/CSCI49370.2019.00296

Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder

Sang Ho Lee, Sanghun Yun, Jinung An, Dong Ha Lee

Division of Intelligent Robot

Daegu Gyeongbuk Institute of Science and Technology

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

Abstract

The new generation of consumer wristbands are now able to classify sleep stages based on multiple sensing data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic(PSG) parameters. Nevertheless, its feasibility in measuring sleep disorder remains unknown. This study aimed to evaluate the potential of Fitbit Charge 2 as a means of monitoring sleep disorders for workers. We recruited participants without mental and medical diseases from 3 sites consisting of department, hospital and research institute. Sleep data were obtained from 3-month night recording at each worker's home in 95 adults (22-64 years; 68 women; over 20 participants from each site). Our results indicate that there are some differences in sleep patterns in different occupations.

Original language	English
Title of host publication	Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1560-1561
Number of pages	2
ISBN (Electronic)	9781728155845
DOIs	https://doi.org/10.1109/CSCI49370.2019.00296
State	Published - Dec 2019
Event	6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019 - Las Vegas, United States Duration: 5 Dec 2019 → 7 Dec 2019

Publication series

Name	Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019

Conference

Conference	6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019
Country/Territory	United States
City	Las Vegas
Period	5/12/19 → 7/12/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

Sleep disorder
Sleep patterns
Wearable device

Access to Document

10.1109/CSCI49370.2019.00296

Cite this

Lee, S. H., Yun, S., An, J., & Lee, D. H. (2019). Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder. In Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019 (pp. 1560-1561). Article 9070812 (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CSCI49370.2019.00296

Lee, Sang Ho ; Yun, Sanghun ; An, Jinung et al. / Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder. Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1560-1561 (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019).

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title = "Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder",

abstract = "The new generation of consumer wristbands are now able to classify sleep stages based on multiple sensing data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic(PSG) parameters. Nevertheless, its feasibility in measuring sleep disorder remains unknown. This study aimed to evaluate the potential of Fitbit Charge 2 as a means of monitoring sleep disorders for workers. We recruited participants without mental and medical diseases from 3 sites consisting of department, hospital and research institute. Sleep data were obtained from 3-month night recording at each worker's home in 95 adults (22-64 years; 68 women; over 20 participants from each site). Our results indicate that there are some differences in sleep patterns in different occupations.",

keywords = "Sleep disorder, Sleep patterns, Wearable device",

author = "Lee, {Sang Ho} and Sanghun Yun and Jinung An and Lee, {Dong Ha}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019 ; Conference date: 05-12-2019 Through 07-12-2019",

year = "2019",

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doi = "10.1109/CSCI49370.2019.00296",

language = "English",

series = "Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019",

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Lee, SH, Yun, S, An, J & Lee, DH 2019, Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder. in Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019., 9070812, Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1560-1561, 6th Annual International Conference on Computational Science and Computational Intelligence, CSCI 2019, Las Vegas, United States, 5/12/19. https://doi.org/10.1109/CSCI49370.2019.00296

Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder. / Lee, Sang Ho; Yun, Sanghun; An, Jinung et al.
Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1560-1561 9070812 (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019).

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

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AU - Lee, Sang Ho

AU - Yun, Sanghun

AU - An, Jinung

AU - Lee, Dong Ha

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N2 - The new generation of consumer wristbands are now able to classify sleep stages based on multiple sensing data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic(PSG) parameters. Nevertheless, its feasibility in measuring sleep disorder remains unknown. This study aimed to evaluate the potential of Fitbit Charge 2 as a means of monitoring sleep disorders for workers. We recruited participants without mental and medical diseases from 3 sites consisting of department, hospital and research institute. Sleep data were obtained from 3-month night recording at each worker's home in 95 adults (22-64 years; 68 women; over 20 participants from each site). Our results indicate that there are some differences in sleep patterns in different occupations.

AB - The new generation of consumer wristbands are now able to classify sleep stages based on multiple sensing data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic(PSG) parameters. Nevertheless, its feasibility in measuring sleep disorder remains unknown. This study aimed to evaluate the potential of Fitbit Charge 2 as a means of monitoring sleep disorders for workers. We recruited participants without mental and medical diseases from 3 sites consisting of department, hospital and research institute. Sleep data were obtained from 3-month night recording at each worker's home in 95 adults (22-64 years; 68 women; over 20 participants from each site). Our results indicate that there are some differences in sleep patterns in different occupations.

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KW - Sleep patterns

KW - Wearable device

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Lee SH, Yun S, An J , Lee DH. Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder. In Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1560-1561. 9070812. (Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019). doi: 10.1109/CSCI49370.2019.00296

Feasibility study of a consumer multi-sensory wristband to monitor sleep disorder

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