research-article

Identifying Elderly with Poor Sleep Quality using Unobtrusive In-home Sensors for Early Intervention

Authors:

Nadee Goonawardene,

Hwee Pink TanAuthors Info & Claims

Goodtechs '18: Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good

Pages 94 - 99

https://doi.org/10.1145/3284869.3284894

Published: 28 November 2018 Publication History

Abstract

Along with the upward trend in population ageing is the increasing proportion of the elderly population living alone in the community. This group is especially vulnerable as the onset of various physical, social and mental health issues may be more likely and may go undetected. However, smart homes enabled with elderly monitoring and care systems (EMCS) can now be used to alert caregivers of anomalies in the daily living patterns of the elderly. In this study, we focus on the sleep quality as the key living pattern, as it has been shown that poor sleep quality can lead to health issues. To ensure data collection while preserving their living patterns, we have deployed the EMCS comprising passive and unobtrusive sensors in more than 90 homes of elderly living alone in Singapore. We have built a binary classification model based on Random Forests using the sensor data collected and the subjective PSQI scores obtained from surveys as the ground truth. From the latter, the elderly's sleep qualities for each survey were divided into 2 groups, representing good and poor sleep qualities. Our model, based on data from 39 participants, achieved 84% classification accuracy, and holds promise for improved accuracy with additional data points.

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Cited By

Ghafurian MWang KDhode IKapoor MMorita PDautenhahn K(2023)Smart Home Devices for Supporting Older Adults: A Systematic ReviewIEEE Access10.1109/ACCESS.2023.326664711(47137-47158)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3266647
Matayong SJetwanna KChoksuchat CChoosawang STrakulmaykee NLimsuwan SInthanuchit K(2023)IoT-based systems and applications for elderly healthcare: a systematic reviewUniversal Access in the Information Society10.1007/s10209-023-01055-1Online publication date: 2-Nov-2023
https://doi.org/10.1007/s10209-023-01055-1
Nuqoba BTan H(2021)Prediction of Sleep Quality in Live-Alone Diabetic Seniors Using Unobtrusive In-Home SensorsHuman Aspects of IT for the Aged Population. Supporting Everyday Life Activities10.1007/978-3-030-78111-8_21(307-321)Online publication date: 3-Jul-2021
https://doi.org/10.1007/978-3-030-78111-8_21
Show More Cited By

Index Terms

Identifying Elderly with Poor Sleep Quality using Unobtrusive In-home Sensors for Early Intervention
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Hardware
  1. Communication hardware, interfaces and storage
    1. Sensor applications and deployments

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cover image ACM Other conferences

Goodtechs '18: Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good

November 2018

316 pages

ISBN:9781450365819

DOI:10.1145/3284869

General Chairs:
Marco Furini
University of Modena and Reggio Emilia, Italy
,
Silvia Mirri
University of Bologna, Italy
,
Kevin Bouchard
Université du Québec à Chicoutimi, Canada
,
Publications Chair:
Barbara Guidi
University of Pisa, Italy

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 November 2018

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Goodtechs '18

Goodtechs '18: International Conference on Smart Objects and Technologies for Social Good

November 28 - 30, 2018

Bologna, Italy

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Cited By

Ghafurian MWang KDhode IKapoor MMorita PDautenhahn K(2023)Smart Home Devices for Supporting Older Adults: A Systematic ReviewIEEE Access10.1109/ACCESS.2023.326664711(47137-47158)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3266647
Matayong SJetwanna KChoksuchat CChoosawang STrakulmaykee NLimsuwan SInthanuchit K(2023)IoT-based systems and applications for elderly healthcare: a systematic reviewUniversal Access in the Information Society10.1007/s10209-023-01055-1Online publication date: 2-Nov-2023
https://doi.org/10.1007/s10209-023-01055-1
Nuqoba BTan H(2021)Prediction of Sleep Quality in Live-Alone Diabetic Seniors Using Unobtrusive In-Home SensorsHuman Aspects of IT for the Aged Population. Supporting Everyday Life Activities10.1007/978-3-030-78111-8_21(307-321)Online publication date: 3-Jul-2021
https://doi.org/10.1007/978-3-030-78111-8_21
Nuqoba BTAN H(2020)Prediction of Nocturia in Live Alone Elderly Using Unobtrusive In-Home Sensors2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377949(4929-4937)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9377949
Chhetri CMotti V(2020)Identifying Vulnerabilities in Security and Privacy of Smart Home DevicesNational Cyber Summit (NCS) Research Track 202010.1007/978-3-030-58703-1_13(211-231)Online publication date: 9-Sep-2020
https://doi.org/10.1007/978-3-030-58703-1_13
TAN CTAN H(2019)Evaluation of Sigfox LPWAN for sensor-enabled homes to identify at risk community dwelling seniors2019 IEEE 44th Conference on Local Computer Networks (LCN)10.1109/LCN44214.2019.8990768(26-33)Online publication date: Oct-2019
https://doi.org/10.1109/LCN44214.2019.8990768

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