• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.9-15
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• 2019

As the human population increases in the world, the ratio of health doctors is rapidly decreasing. Therefore, it is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies. Usually this happens due to stressful situations during everyday activities including work. This paper presents a machine learning approach to reliably estimating the level of human mental stress using wearable physiological sensors. And also, this paper presents an Android- and Arduino-based stress monitoring and relief system.

• Korean Journal of Human Ecology
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• v.22 no.2
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• pp.257-266
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• 2013

The purpose of this study was to test the multiple mediating effects between attachment and life quality among university freshmen, regards on positive and negative affect, stress, social support and mental health as mediating factors. 200 freshmen were selected for the questionnaire study in a university in Busan. There were significant correlations among positive and negative affect, stress, social support, mental health and life quality with attachment. The maximum likelihood estimation revealed that attachment had no direct link with life quality. Attachment had indirect effects on life quality, mediated by positive affect and mental health. The results and limitations of this study were also discussed, from the perspective of attachment theory and previous studies.