Utilizing activity sensors to identify the behavioural activity patterns of elderly home care clients |
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Author: | Hyväri, Sauli1; Elo, Satu2; Kukkohovi, Saara1; |
Organizations: |
1Research Unit of Health Sciences and Technology, GeroNursing Centre, University of Oulu, Oulu, Finland 2Future Health Services, Lapland University of Applied Sciences, Kemi, Finland |
Format: | article |
Version: | published version |
Access: | open |
Online Access: | PDF Full Text (PDF, 3.3 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2022091358916 |
Language: | English |
Published: |
Informa,
2022
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Publish Date: | 2022-09-13 |
Description: |
AbstractPurpose: The behavioural activity pattern is a behavioural and biological 24-hour rhythm. Ageing, diseases and memory disorders can change this pattern. Home care staff can utilize knowledge about the behavioural activity pattern of elderly home care clients in many ways. The purpose of this study was to evaluate whether home care staff could identify the behavioural activity pattern of elderly home care clients using activity sensors, namely, actigraphs and motion sensors, could identify the behavioural activity rhythms. Materials and methods: A total of four elderly home care clients and one elderly home rehabilitation client took part in the study. The participants wore actigraphs on their wrist and motion sensors were installed in their apartment. In addition to sensor data, home care staff answered one open-ended question during each home care visit. The data collection period was two weeks. Both quantitative and qualitative methods were used in the analysis. Results: The behavioural activity pattern was easy to identify from the motion sensor data, whereas actigraph data were difficult to interpret. The home care staff members’ answers to open-ended questions reinforced the reliability of motion sensor data. Conclusions: Motion sensors are relatively cheap, unobtrusive and reliable way to identify and detect changes in the behavioural activity patterns of elderly home care clients. see all
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Series: |
Disability and rehabilitation. Assistive technology |
ISSN: | 1748-3107 |
ISSN-E: | 1748-3115 |
ISSN-L: | 1748-3107 |
Volume: | In press |
DOI: | 10.1080/17483107.2022.2110951 |
OADOI: | https://oadoi.org/10.1080/17483107.2022.2110951 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
3141 Health care science |
Subjects: | |
Copyright information: |
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |