공포영상 및 소음자극에 의한 스트레스의 전기피부반응, 심박변이도 및 뇌파 해석
GSR, HRV and EEG Analysis of Stress caused by Horror Image and Noise Stimulation
1
조회
0
다운로드
5
인용
0
참고문헌
키워드
초록
직장에서의 스트레스는 많은 직업, 생활환경 및 연령대의 사람들에게 영향을 끼치는 심각한 문제가 되었다. 스트레스 관리는 스트레스가 질병을 일으키기 시작하기 훨씬 전에 시작해야 한다. 본 연구에서는 영상 및 소음 자극 시 발생하는 전기피부반응도, 심전도 및 뇌파를 측정하여 스트레스를 평가하는 연구를 수행하였다. GRS 진폭은 스트레스 상황이 안정 상태(baseline)보다 27.9% 높게 나타났다. 그리고 자극 후 baseline의 응답시간은 스트레스 상황 보다 71.6% 이상 시간이 더 길었다. 심박변이도에서 스트레스 응답 특성은 RMSSD의 변화율이 16.4% 차이가 났으며, HF power의 변화율은 29.7% 차이를 보였다. 뇌파는 스트레스 자극 시 주파수 대역이 θ파 대역으로 점점 변함을 알 수 있었다. 우리는 영상자극 및 소음자극이 스트레스와 상관관계를 파악함으로써 객관적지표로 활용 가능할 것이다.
Abstract
Stress at work has become a serious problem affecting many people of different professions, life situations, and age groups. Stress management should start far before the stress start causing illnesses. In this study, studies were conducted to evaluate stress by measuring the Galvanic skin Response(GRS), Electrocardiograph(ECG), and Electroencephalogram(EEG) generated during images and noise stimuli. The GRS amplitude showed that the stress situation was 27.9 % higher than the baseline. And after the stimulus period, the response time of baseline was longer than 71.6 % than the stress situation. The stress response characteristics of the HRV showed that the rate of change in RMSSD was 16.4 %, and the rate of change of the HF Power was 29.7 %. EEG showed that the frequency band was gradually changed to the θ wave band during stress stimulation. We will be able to utilize image stimuli and noise stimuli as an objective indicator of stress and correlation.
참고문헌 (16)
- S. Selye, "Handbook of Stress", pp.7~17 (1982), Fress Press
- C. Setz, "Discriminating Stress From Cognitive Load Using a Wearable EDA Device", IEEE Transactions on Information Technology in Biomedicine, 14(2), pp.410~417 (2010), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- Fernando Seoane, "Wearable Biomedical Measurement Systems for Assessment of Mental Stress of Combatants in Real Time", Sensors, 14(4), pp.7120~7141 (2014), MDPI AG[DOI]
- M. Villarejo, "A stress sensor based on Galvanic Skin Response controlled by ZigBee", Sensor, 12(5), pp.6075~6101 (2012)
- E. Labbe, "Coping with stress: the effectiveness of different types of music", Applied Psychophysiology and Biofeedback, 32(3-4), pp.163~168 (2007)[DOI]
- J.A. Healey, "Detecting Stress During Real-World Driving Tasks Using Physiological Sensors", IEEE Transactions on Intelligent Transportation Systems, 6(2), pp.156~166 (2005), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
- G. Clifford, "Signal processing methods for heart rate variability", Doctor, pp.2002
- U. Rajendra Acharya, "Heart rate variability: a review", Medical & Biological Engineering & Computing, 44(12), pp.1031~1051 (2006), Springer Nature[DOI]
- A. Saidatul, "Automated system for stress evaluation on based on EEG signal: A prospective review", proceedings of IEEE 7th International Colloquium on signal processing and Its Applications, pp.167~171 (2011)
- Rod K. Dishman, "Heart rate variability, trait anxiety, and perceived stress among physically fit men and women", International Journal of Psychophysiology, 37(2), pp.121~133 (2000), Elsevier BV[DOI]
- S. Reisman, "Measurement of Physiological stress", Bioengineering Conference (1997)
- H. Anand, "Effect of meditation on alpha EEG and galvanic skin response: Measurement of an altered state of consciousness", Indian Journal of Positive Psychology, 5(3), pp.255~259 (2014)
- 유승은, "안전 운전을 위한 뇌파 감지를 통한 운전 습관 관리시스템의 설계 및 구현", 전기전자학회논문지, 18(3), pp.368~375 (2014), 한국전기전자학회[DOI]
- 조영창, "스트레스 평가를 위한 심박 변이도, 전기피부반응 및 피부온도 특성", 한국산업정보학회논문지, 20(3), pp.11~18 (2015), 한국산업정보학회
- OLAF KOHLISCH, "Physiological changes during computer tasks: responses to mental load or to motor demands?", Ergonomics, 39(2), pp.213~224 (1996), Informa UK Limited[DOI]
- A. Gevins, "Monitoring working memory load during computer based tasks with EEG pattern recognition methods", Human Factors, 40(2), pp.79~91 (1998)