Mobile Health System using Facial Image for Assessment of Work Engagement, Recovery and Reattachment

The number of workers' compensation claims and recognized cases related to mental disorders has been increasing annually. In response, the Ministry of Health, Labour and Welfare has mandated an annual stress check. However, while the focus has been on the damage sustained, little attention has been given to the recovery process from daily fatigue.
Meanwhile, there is growing interest in daily health monitoring using IoT devices. However, managing multiple devices and the need for active participation in measurements can lead to decreased user motivation.
To address this issue, this study aims to realize a health monitoring system that seamlessly integrates into daily life, eliminating the need for active measurement actions that may reduce motivation. Specifically, we propose a recovery estimation system that focuses on behaviors at the washbasin (washbasin activities), which is a routine part of daily life for many people.
In the proposed method, data is collected during washbasin activities using IoT-enabled washbasins and toothbrushes. The collected data is then processed through an estimation model to predict the level of recovery.

Published Papers

• Yoshimura, Satoshi, Hirohiko Suwa, and Teruhiro Mizumoto. "Mobile Health System using Facial Image for Assessment of Work Engagement, Recovery and Reattachment." 2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2023.