We will develop an emotional mobile laboratory to build a foundation for the sustainable provision of stable healthcare by preventing burnout among healthcare professionals who provide medical care in critical situations such as the COVID-19 pandemic.
There have been many studies attempting to measure the emotions of healthcare professionals, mainly in North America, but they have been conducted in experimental laboratories not in the real world. We will create a mobile laboratory for measuring emotion data in the workplace of the professionals. Multiple wearable biometric sensor devices that do not interfere with their work are used to measure their emotions objectively and in real time. Specifically, we will develop electrodermal activity sensors that can be attached to a subject's foot, eye tracking system devices being attached to face shields as protective equipment against infection, and a new technique for recording facial expression videos by attaching a small camera to the face shields and analyzing them using machine learning programming. Through this study environment, we will build an emotional big data infrastructure by continuously and multilaterally measuring the emotions of healthcare professionals and create a prediction model for the onset of professionals' burnout using deep learning. This enables us to formulate the mental health improvement program that allows early recognition of signs of burnout and to improve the wellness of front-line professionals in crisis situations such as pandemics and disasters, thereby enabling the sustainable provision of healthcare.