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http://dx.doi.org/10.9717/kmms.2020.23.9.1147

Human Mental Condition Monitoring through Measurement of Physiological Signals  

Ulziibayar, Natsagdorj (Dept. of Electronic Engineering, Pukyong National University)
Kang, Sanghoon (Dept. of Electronic Engineering, Pukyong National University)
Park, Hanhoon (Dept. of Electronic Engineering, Pukyong National University)
Publication Information
Journal of Korea Multimedia Society / v.23, no.9, 2020 , pp. 1147-1154 More about this Journal
Abstract
Nowadays, one of the most common diseases is chronic mental fatigue syndrome. This can be caused by many factors, such as busy life, heavy workload, high population density, and adverse technological impact. Most office workers and students who are sitting all day long while being exposed to this kind of environments are likely to be involved in the mental illness. Therefore, to prevent the illness, it has been highly required to design a device that enables mental fatigue to be monitored continuously without human intervention. This paper proposes a linear regression method to reliably estimating the level of human mental fatigue using wearable physiological sensors, with an estimation error of 0.852. Also, this paper presents an Android application that is able to check mental health conditions in daily life.
Keywords
Arduino-based Mental Condition Measurement; Wearable Physiological Sensors; Mental Fatigue Level Analysis; Android Application;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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