Automobile Driver Stress Detection By Wearable Glove System
DOI:
https://doi.org/10.14419/ijet.v7i4.19.22039Keywords:
GSR, Skin conductance, Stress Detection, Automobile, Accidents.Abstract
This paper focuses on predicting the driver’s stress depending on the change in skin conductance. The Galvanic Skin Response (GSR) sensor is used for measuring the skin conductance. The electrical conductance varies with respect to the moisture of the skin produced by the sweat glands. The emotions of the driver such as normal state and stressed state are considered for monitoring. The electrical conductance of the skin helps to monitor the stress of the driver when driving the vehicle. Compared to other physiological signals such as ECG, EMG, EEG, EOG, Respiration Rate, this method is a simple and reliable method. Twenty subjects were exposed to the simulation driving environment under different scenarios such as  normal roads, highways and heavy traffic roads. The readings obtained from this study helps in detecting the driver’s stress level.
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References
[1] J. A. Healey, R. W. Picard, "Detecting stress during real-world driving tasks using physiological sensors", IEEE Trans. Intell. Transp. Syst., vol. 6, no. 2, pp. 156-166, Jun.2005
[2] R.Maheswari, S.Sheeba Rani, V.Gomathy and P.Sharmila,“Real Time Environment Simulation through Virtual Reality†in International Journal of Engineering and Technology(IJET) , Volume.7, No.7, pp 404-406, April 2018
[3] R. R. Singh, S. Conjeti, R. Banerjee, "Biosignal based on-road stress monitoring for automotive drivers", Proc. Nat. Conf. Commun., pp. 1-5, Feb. 2012.
[4] A. Lanata et al., "How the autonomic nervous system and driving style change with incremental stressing conditions during simulated driving", IEEE Trans. Intell. Transp. Syst., vol. 16, no. 3, pp. 1505-1517, Jun. 2015
[5] A. Khodayari, A. Ghaffari, S. Ameli, J. Flahatgar, "A historical review on lateral and longitudinal control of autonomous vehicle motions", Proc. 2nd Int. Conf. Mech. Elect. Technol., pp. 421-429, Sep. 2010.
[6] M. Singh, A. B. Queyam, "Stress detection in automobile drivers using physiological parameters: A review", Int. J. Eng. Edu., vol. 5, no. 2, pp. 1-5, Dec. 2013.
[7] S.Sheeba Rani, R.Maheswari, V.Gomathy and P.Sharmila “Iot driven vehicle license plate extraction approach†in International Journal of Engineering and Technology(IJET) , Volume.7, pp 457-459, April 2018
[8] R. Zheng, S. Yamabe, K. Nakano, Y. Suda, "Biosignal analysis to assess mental stress in automatic driving of trucks: Palmar perspiration and masseter electromyography", Sensors, vol. 15, no. 3, pp. 5136-5150, Mar. 2015
[9] G. Rigas, Y. Goletsis, D. I. Fotiadis, "Real-time driver’s stress event detection", IEEE Trans. Intell. Transp. Syst., vol. 13, no. 1, pp. 221-234, Mar. 2012.
[10] H. Gao, A. Yüce, J.-P. Thiran, "Detecting emotional stress from facial expressions for driving safety", Proc. IEEE Int. Conf. Image Process., pp. 5961-5965, Oct. 2014.
[11] J. S. Lerner, R. E. Dahl, A. R. Hariri, S. E. Taylor, "Facial expressions of emotion reveal neuroendocrine and cardiovascular stress responses", Biol. Psychiatry, vol. 61, no. 2, pp. 253-260, Jan. 2007.
[12] B.-G. Lee, W.-Y. Chung, "Driver alertness monitoring using fusion of facial features and bio-signals", IEEE Sensors J., vol. 12, no. 7, pp. 2416-2422, Jul. 2012.
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How to Cite
Received date: November 28, 2018
Accepted date: November 28, 2018
Published date: November 27, 2018