Unobtrusive Bed Monitor State of the Art
On average, people spend more than a quarter of their day in bed. If physiological information could be collected automatically while we sleep, it would be effective not only for health management but also for disease prevention. Unobtrusive bed monitoring devices have been developed over the past 3...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/6/1879 |
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| author | Toshiyo Tamura Ming Huang |
| author_facet | Toshiyo Tamura Ming Huang |
| author_sort | Toshiyo Tamura |
| collection | DOAJ |
| description | On average, people spend more than a quarter of their day in bed. If physiological information could be collected automatically while we sleep, it would be effective not only for health management but also for disease prevention. Unobtrusive bed monitoring devices have been developed over the past 30 years or so to detect physiological information without awareness, and this method attracted attention again in the 2020s, with the proliferation of deep learning, AI, and IoT. This section describes the current state of the art. |
| format | Article |
| id | doaj-art-e4f2c4675f2a4b8485097d0a0b7968e4 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-e4f2c4675f2a4b8485097d0a0b7968e42025-08-20T01:48:58ZengMDPI AGSensors1424-82202025-03-01256187910.3390/s25061879Unobtrusive Bed Monitor State of the ArtToshiyo Tamura0Ming Huang1Future Robotics Organization, Waseda University, Tokyo 162-0044, JapanShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaOn average, people spend more than a quarter of their day in bed. If physiological information could be collected automatically while we sleep, it would be effective not only for health management but also for disease prevention. Unobtrusive bed monitoring devices have been developed over the past 30 years or so to detect physiological information without awareness, and this method attracted attention again in the 2020s, with the proliferation of deep learning, AI, and IoT. This section describes the current state of the art.https://www.mdpi.com/1424-8220/25/6/1879unobtrusive bed monitorECGBCGsleep assessmentbody movement |
| spellingShingle | Toshiyo Tamura Ming Huang Unobtrusive Bed Monitor State of the Art Sensors unobtrusive bed monitor ECG BCG sleep assessment body movement |
| title | Unobtrusive Bed Monitor State of the Art |
| title_full | Unobtrusive Bed Monitor State of the Art |
| title_fullStr | Unobtrusive Bed Monitor State of the Art |
| title_full_unstemmed | Unobtrusive Bed Monitor State of the Art |
| title_short | Unobtrusive Bed Monitor State of the Art |
| title_sort | unobtrusive bed monitor state of the art |
| topic | unobtrusive bed monitor ECG BCG sleep assessment body movement |
| url | https://www.mdpi.com/1424-8220/25/6/1879 |
| work_keys_str_mv | AT toshiyotamura unobtrusivebedmonitorstateoftheart AT minghuang unobtrusivebedmonitorstateoftheart |