Assisting Personalized Healthcare of Elderly People: Developing a Rule-Based Virtual Caregiver System Using Mobile Chatbot

To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical health states through human–computer interaction in the form of dialogue. The purpose of this paper is to implement and evaluate a virtual c...

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Published inSensors (Basel, Switzerland) Vol. 22; no. 10; p. 3829
Main Authors Miura, Chisaki, Chen, Sinan, Saiki, Sachio, Nakamura, Masahide, Yasuda, Kiyoshi
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.05.2022
MDPI
Subjects
Aged
Analysis
Caregivers
Delivery of Health Care
Feedback
Health aspects
Humans
Internet of Things
mind monitoring
Mobile Applications
mobile chatbot
Nursing care
Older people
Perception
personalized healthcare
Questionnaires
Robots
Sensors
Software quality
Surveys
Usability
User-Computer Interface
virtual caregiver
Japan
Germany
personalized healthcare
mobile chatbot
mind monitoring
virtual caregiver
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Abstract To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical health states through human–computer interaction in the form of dialogue. The purpose of this paper is to implement and evaluate a virtual caregiver system using mobile chatbot. Unlike the conventional health monitoring approach, our key idea is to integrate a rule-based virtual caregiver system (called “Mind Monitoring” service) with the physical, mental, and social questionnaires into the mobile chat application. The elderly person receives one question from the mobile chatbot per day, and answers it by pushing the optional button or using a speech recognition technique. Furthermore, a novel method is implemented to quantify the answers, generate visual graphs, and send the corresponding summaries or advice to the specific elder. In the experimental evaluation, we applied it to eight elderly subjects and 19 younger subjects within 14 months. As main results, its effects were significantly improved by the proposed method, including the above 80% in the response rate, the accurate reflection of their real lives from the responses, and high usefulness of the feedback messages with software quality requirements and evaluation. We also conducted interviews with subjects for health analysis and improvement.
AbstractList To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical health states through human–computer interaction in the form of dialogue. The purpose of this paper is to implement and evaluate a virtual caregiver system using mobile chatbot. Unlike the conventional health monitoring approach, our key idea is to integrate a rule-based virtual caregiver system (called “Mind Monitoring” service) with the physical, mental, and social questionnaires into the mobile chat application. The elderly person receives one question from the mobile chatbot per day, and answers it by pushing the optional button or using a speech recognition technique. Furthermore, a novel method is implemented to quantify the answers, generate visual graphs, and send the corresponding summaries or advice to the specific elder. In the experimental evaluation, we applied it to eight elderly subjects and 19 younger subjects within 14 months. As main results, its effects were significantly improved by the proposed method, including the above 80% in the response rate, the accurate reflection of their real lives from the responses, and high usefulness of the feedback messages with software quality requirements and evaluation. We also conducted interviews with subjects for health analysis and improvement.
To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical health states through human-computer interaction in the form of dialogue. The purpose of this paper is to implement and evaluate a virtual caregiver system using mobile chatbot. Unlike the conventional health monitoring approach, our key idea is to integrate a rule-based virtual caregiver system (called "Mind Monitoring" service) with the physical, mental, and social questionnaires into the mobile chat application. The elderly person receives one question from the mobile chatbot per day, and answers it by pushing the optional button or using a speech recognition technique. Furthermore, a novel method is implemented to quantify the answers, generate visual graphs, and send the corresponding summaries or advice to the specific elder. In the experimental evaluation, we applied it to eight elderly subjects and 19 younger subjects within 14 months. As main results, its effects were significantly improved by the proposed method, including the above 80% in the response rate, the accurate reflection of their real lives from the responses, and high usefulness of the feedback messages with software quality requirements and evaluation. We also conducted interviews with subjects for health analysis and improvement.To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical health states through human-computer interaction in the form of dialogue. The purpose of this paper is to implement and evaluate a virtual caregiver system using mobile chatbot. Unlike the conventional health monitoring approach, our key idea is to integrate a rule-based virtual caregiver system (called "Mind Monitoring" service) with the physical, mental, and social questionnaires into the mobile chat application. The elderly person receives one question from the mobile chatbot per day, and answers it by pushing the optional button or using a speech recognition technique. Furthermore, a novel method is implemented to quantify the answers, generate visual graphs, and send the corresponding summaries or advice to the specific elder. In the experimental evaluation, we applied it to eight elderly subjects and 19 younger subjects within 14 months. As main results, its effects were significantly improved by the proposed method, including the above 80% in the response rate, the accurate reflection of their real lives from the responses, and high usefulness of the feedback messages with software quality requirements and evaluation. We also conducted interviews with subjects for health analysis and improvement.
Audience Academic
Author Nakamura, Masahide
Saiki, Sachio
Yasuda, Kiyoshi
Chen, Sinan
Miura, Chisaki
AuthorAffiliation 4 Osaka Institute of Technology, 5-16-1 Omiya, Asahi-ku, Osaka 535-8585, Japan; yasukiyo.12@outlook.jp
2 Department of Data & Innovation, Kochi University of Technology, 185 Miyanigutu, Tosayamada-cho, Kami-shi, Kochi 782-8502, Japan; saiki.sachio@kochi-tech.ac.jp
3 RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
1 Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe 657-8501, Japan; cmiura@ws.cs.kobe-u.ac.jp (C.M.); masa-n@cs.kobe-u.ac.jp (M.N.)
AuthorAffiliation_xml – name: 3 RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
– name: 2 Department of Data & Innovation, Kochi University of Technology, 185 Miyanigutu, Tosayamada-cho, Kami-shi, Kochi 782-8502, Japan; saiki.sachio@kochi-tech.ac.jp
– name: 1 Graduate School of System Informatics, Kobe University, 1-1 Rokkodai-cho, Nada, Kobe 657-8501, Japan; cmiura@ws.cs.kobe-u.ac.jp (C.M.); masa-n@cs.kobe-u.ac.jp (M.N.)
– name: 4 Osaka Institute of Technology, 5-16-1 Omiya, Asahi-ku, Osaka 535-8585, Japan; yasukiyo.12@outlook.jp
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This paper is an extended version of the conference papers: Chisaki, M.; Sachio, S.; Masahide, N.; Kiyoshi, Y. Implementing and Evaluating feedback feature of Mind Monitoring Service for Elderly People at Home. In Proceedings of the iiWAS 2020, Online, 30 November–2 December 2020.
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Snippet To assist personalized healthcare of elderly people, our interest is to develop a virtual caregiver system that retrieves the expression of mental and physical...
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StartPage 3829
SubjectTerms Aged
Analysis
Caregivers
Delivery of Health Care
Feedback
Health aspects
Humans
Internet of Things
mind monitoring
Mobile Applications
mobile chatbot
Nursing care
Older people
Perception
personalized healthcare
Questionnaires
Robots
Sensors
Software quality
Surveys
Usability
User-Computer Interface
virtual caregiver
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Title Assisting Personalized Healthcare of Elderly People: Developing a Rule-Based Virtual Caregiver System Using Mobile Chatbot
URI https://www.ncbi.nlm.nih.gov/pubmed/35632238
https://www.proquest.com/docview/2670406403
https://www.proquest.com/docview/2671272457
https://pubmed.ncbi.nlm.nih.gov/PMC9146313
https://doaj.org/article/a058b5b3cbd449808f093381f5f2009f
Volume 22
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