PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring
There has been a subsequent increase in the number of elderly people living alone, with contribution from advancement in medicine and technology. However, hospitals and nursing homes are crowded, expensive, and uncomfortable, while personal caretakers are expensive and few in number. Home monitoring...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/18/6965 |
| _version_ | 1827656773191860224 |
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| author | Research Dawadi Teruhiro Mizumoto Yuki Matsuda Keiichi Yasumoto |
| author_facet | Research Dawadi Teruhiro Mizumoto Yuki Matsuda Keiichi Yasumoto |
| author_sort | Research Dawadi |
| collection | DOAJ |
| description | There has been a subsequent increase in the number of elderly people living alone, with contribution from advancement in medicine and technology. However, hospitals and nursing homes are crowded, expensive, and uncomfortable, while personal caretakers are expensive and few in number. Home monitoring technologies are therefore on the rise. In this study, we propose an anonymous elderly monitoring system to track potential risks in everyday activities such as sleep, medication, shower, and food intake using a smartphone application. We design and implement an activity visualization and notification strategy method to identify risks easily and quickly. For evaluation, we added risky situations in an activity dataset from a real-life experiment with the elderly and conducted a user study using the proposed method and two other methods varying in visualization and notification techniques. With our proposed method, 75.2% of the risks were successfully identified, while 68.5% and 65.8% were identified with other methods. The average time taken to respond to notification was 176.46 min with the proposed method, compared to 201.42 and 176.9 min with other methods. Moreover, the interface analyzing and reporting time was also lower (28 s) in the proposed method compared to 38 and 54 s in other methods. |
| first_indexed | 2024-03-09T22:34:01Z |
| format | Article |
| id | doaj.art-971a2ee99290479681772c41b91b274d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:34:01Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-971a2ee99290479681772c41b91b274d2023-11-23T18:52:15ZengMDPI AGSensors1424-82202022-09-012218696510.3390/s22186965PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly MonitoringResearch Dawadi0Teruhiro Mizumoto1Yuki Matsuda2Keiichi Yasumoto3Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma 630-0192, Nara, JapanGraduate School of Information Science and Technology, Osaka University, Suita 565-0871, Osaka, JapanGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma 630-0192, Nara, JapanGraduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma 630-0192, Nara, JapanThere has been a subsequent increase in the number of elderly people living alone, with contribution from advancement in medicine and technology. However, hospitals and nursing homes are crowded, expensive, and uncomfortable, while personal caretakers are expensive and few in number. Home monitoring technologies are therefore on the rise. In this study, we propose an anonymous elderly monitoring system to track potential risks in everyday activities such as sleep, medication, shower, and food intake using a smartphone application. We design and implement an activity visualization and notification strategy method to identify risks easily and quickly. For evaluation, we added risky situations in an activity dataset from a real-life experiment with the elderly and conducted a user study using the proposed method and two other methods varying in visualization and notification techniques. With our proposed method, 75.2% of the risks were successfully identified, while 68.5% and 65.8% were identified with other methods. The average time taken to respond to notification was 176.46 min with the proposed method, compared to 201.42 and 176.9 min with other methods. Moreover, the interface analyzing and reporting time was also lower (28 s) in the proposed method compared to 38 and 54 s in other methods.https://www.mdpi.com/1424-8220/22/18/6965elderly monitoringsuccessful agingmobile applicationgerontechnology |
| spellingShingle | Research Dawadi Teruhiro Mizumoto Yuki Matsuda Keiichi Yasumoto PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring Sensors elderly monitoring successful aging mobile application gerontechnology |
| title | PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring |
| title_full | PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring |
| title_fullStr | PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring |
| title_full_unstemmed | PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring |
| title_short | PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring |
| title_sort | patrol participatory activity tracking and risk assessment for anonymous elderly monitoring |
| topic | elderly monitoring successful aging mobile application gerontechnology |
| url | https://www.mdpi.com/1424-8220/22/18/6965 |
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