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Home Interactive Elderly Care Two-Way Video Healthcare System Design

This paper explores and analyses the interactive home geriatric two-way video health care system, investigates and analyses the daily lives and behaviours of the elderly in their homes through research interviews, obtains the main needs of the elderly population in their lives, as well as their cogn...

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Detalles Bibliográficos
Autores principales: Yi, Chun, Feng, Xiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843169/
https://www.ncbi.nlm.nih.gov/pubmed/33542800
http://dx.doi.org/10.1155/2021/6693617
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author Yi, Chun
Feng, Xiqiang
author_facet Yi, Chun
Feng, Xiqiang
author_sort Yi, Chun
collection PubMed
description This paper explores and analyses the interactive home geriatric two-way video health care system, investigates and analyses the daily lives and behaviours of the elderly in their homes through research interviews, obtains the main needs of the elderly population in their lives, as well as their cognitive and behavioural characteristics, and proposes four service function modules for the elderly in their homes; then, combining service design and interaction design theory, we propose the following four service modules for the elderly in their homes. Given the design methods and processes of the intelligent service system for the elderly at home as well as the interface interaction design principles on the three levels of vision, interaction, and reflection, the intelligent service system platform for the elderly at home was constructed, the interaction design of the mobile device terminal software of the service system platform practiced in the form of APP, and the eye-movement experiment method and fuzzy hierarchical analysis were applied to the design of the intelligent service system for the elderly at home from qualitative and quantitative perspectives. The thesis study provides a new way of thinking to design and provide intelligent service system products for the elderly living at home, which is an important contribution to society's care for the elderly and their quality of life. The key features of the human skeleton are extracted from the model of abnormal leaning and falling behaviour of the elderly, and the SVM machine learning method is used to classify and identify the data, which enables the identification of the abnormal behaviour of the elderly at home with an accuracy of 97%.
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spelling pubmed-78431692021-02-03 Home Interactive Elderly Care Two-Way Video Healthcare System Design Yi, Chun Feng, Xiqiang J Healthc Eng Research Article This paper explores and analyses the interactive home geriatric two-way video health care system, investigates and analyses the daily lives and behaviours of the elderly in their homes through research interviews, obtains the main needs of the elderly population in their lives, as well as their cognitive and behavioural characteristics, and proposes four service function modules for the elderly in their homes; then, combining service design and interaction design theory, we propose the following four service modules for the elderly in their homes. Given the design methods and processes of the intelligent service system for the elderly at home as well as the interface interaction design principles on the three levels of vision, interaction, and reflection, the intelligent service system platform for the elderly at home was constructed, the interaction design of the mobile device terminal software of the service system platform practiced in the form of APP, and the eye-movement experiment method and fuzzy hierarchical analysis were applied to the design of the intelligent service system for the elderly at home from qualitative and quantitative perspectives. The thesis study provides a new way of thinking to design and provide intelligent service system products for the elderly living at home, which is an important contribution to society's care for the elderly and their quality of life. The key features of the human skeleton are extracted from the model of abnormal leaning and falling behaviour of the elderly, and the SVM machine learning method is used to classify and identify the data, which enables the identification of the abnormal behaviour of the elderly at home with an accuracy of 97%. Hindawi 2021-01-21 /pmc/articles/PMC7843169/ /pubmed/33542800 http://dx.doi.org/10.1155/2021/6693617 Text en Copyright © 2021 Chun Yi and Xiqiang Feng. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Yi, Chun
Feng, Xiqiang
Home Interactive Elderly Care Two-Way Video Healthcare System Design
title Home Interactive Elderly Care Two-Way Video Healthcare System Design
title_full Home Interactive Elderly Care Two-Way Video Healthcare System Design
title_fullStr Home Interactive Elderly Care Two-Way Video Healthcare System Design
title_full_unstemmed Home Interactive Elderly Care Two-Way Video Healthcare System Design
title_short Home Interactive Elderly Care Two-Way Video Healthcare System Design
title_sort home interactive elderly care two-way video healthcare system design
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843169/
https://www.ncbi.nlm.nih.gov/pubmed/33542800
http://dx.doi.org/10.1155/2021/6693617
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