Acute Mental Stress Measurement using Brain-IoT System

被引：0
|
作者：
Shirke, Bhagyashree [1 ]
George, Kiran [1 ]
Wong, Jonathan [1 ]
机构：
[1] Calif State Univ, Dept Comp Engn, Fullerton, CA USA
来源：
2019 IEEE FIRST INTERNATIONAL CONFERENCE ON COGNITIVE MACHINE INTELLIGENCE (COGMI 2019) | 2019年
关键词：
Electroencephalography (EEG); ThingSpeak Database; Galvanic Skin Response (GSR); Heart Rate Variability (HRV); Discrete Wavelet Transform (DWT);
D O I：
10.1109/CogMI48466.2019.00019
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Every individual experience stress of varied intensity while performing daily tasks. Excessive stress can be harmful to human health. Hence, stress assessment is essential in preventing detrimental long-term effects. In this study, we investigate the feasibility of EEG for the measurement of acute mental stress. Also, the post-stress analysis with four distinct cases on stress-induced subjects is carried out. The experiments accomplished were conducted using an EEG headset, ThingSpeak database, and a mobile application. The subject is required to play a mobile game, which induces stress as the game level progresses. This raw EEG data is pre-processed and analyzed in MATLAB and sent over to the ThingSpeak database. When the acute level of stress is detected, the individual gets notified by the mobile application to prompt soothing music and closing eyes. Overall, the experiment concluded with reduced stress levels of the subject after closing eyes with and without music.
引用
收藏
页码：81 / 86
页数：6
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