Title: Flail Detection by Electricity Data x AI
Speaker: Mr. Yoshinobu Nakahashi (VP of Data Science, JDSC Corporation)
Abstract: In recent years, frail has been the focus of much attention in the area of long-term care. Frail is a term that refers to the stage between healthy and in need of care. As people age, their ability to recover from physical, mental, and social damage declines, and they change into a state requiring nursing care in which they must receive assistance in order to lead their daily lives. However, if we can recognize physical and mental decline at an early stage, there is a possibility of returning to a healthy state through countermeasures. On the other hand, to detect frailty, it is necessary to check for such symptoms as decreased activity and fatigue, but since people do not have the habit of regularly measuring these symptoms, they are often overlooked until the symptoms progress. We have been working on the detection of frailty by analyzing electricity data, and our service using this frailty detection AI has now been introduced to local governments and is being implemented in society. Frailty detection AI extracts information from electricity data, such as the number of times a person goes out, sleeping hours, and activity level, to detect elderly people who are suspected of having frailty. This makes it possible to continuously monitor the risk of frailty in the elderly, enabling early detection and more efficient individualized support. In addition, since the electricity data is obtained by smart meters, no additional equipment is required, making it possible for many people to take measures against frailty in the course of their daily lives. In this workshop, we will introduce this flail detection AI. We look forward to your participation.
- Date
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March 7th, 2025（Fri.）18:00～20:00
- Venue
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Held online
- Organizer
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Co-organizer (HRAM The Japan Society for Industrial and Applied Mathematics, D-DRIVE National Network)
- Participation Fee
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Free（Advance registration required）
https://www-mmds.sigmath.es.osaka-u.ac.jp/structure/activity/ai_data.php?id=87
- web
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https://www-mmds.sigmath.es.osaka-u.ac.jp/structure/activity/ai_data.php?id=87
- Contact
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Takashi Suzuki
suzuki@sigmath.es.osaka-u.ac.jp