• Electronics and Telecommunications Trends
• /
• v.36 no.5
• /
• pp.32-41
• /
• 2021

As the COVID-19 crisis continues, working environments and lifestyles have been changed unexpectedly, therefore the importance of mental health in the working environments has been highlighted. When the workers' mental health deteriorates, there will be personal losses but also human resources losses caused productivity decrements of the company or the organization. Many researchers have been tried to solve these issues with the help of ICT technologies such as wearable devices. Most wearable healthcare devices have been designed to detect the physiological status of users and collect the physical activities of users, and their applications are gradually expanding. Those devices may be good candidates to prevent loss of human resources from working environments especially under the COVID-19 situation by continuously monitoring mental health status in connection with mobile devices and managing the mental health on their own by combining mental well-being with support solutions. In this paper, the development trend of mental health measurement and mental well-being support technologies is analyzed, and development prospects are examined.

• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.29-36
• /
• 2022

The prevalence of stress and depression among emotional workers is increasing due to the rapid increase in emotional labor and service workers. However, the current mental health management of emotional workers is difficult to consider the emotional response at the time of stress situations, and the existing mental health management is limited because the individual's base state is not reflected. In this study, we present mental healthcare digital twin solution technology, a personalized stress risk management solution. For mental health risk management due to emotional labor, a solution simulation is performed to accurately predict stress risk through synchronization/modeling of dynamic objects in virtual space by extracting individual stress risk factors such as emotional/physical response and environment into various modalities. It provides a mental healthcare digital twin solution for predicting personalized mental health risks that can be configured with modalities and objects tailored to the environment of emotional workers and improved according to user feedback.