ABSTRACT
Controlling driver stress level is going popular research and put it very important factor to reduce risk of road accident. The aim of the paper is to analysis the impact of road complexity on driver stress level based on physiological factor of Heart Rate Variability (HRV). The first step of the research is literature study on human stress, Heart Rate Variability (HRV), Electrocardiograph (ECG), and NASA TLX mental work load. The driver will use ECG to monitor and then recorded at every heart rate change at any time from three different road conditions of city road, rural road, and motorways. The collected sampling data are 26 male drivers with the average age of 21 years old and average driving experience of 4.08 years. Mental stress evaluation of driver was assessed by frustration level (F) in NASA TLX questioner (subjective measurenment) and HRV in time domain analysis mRR (objective measurenment). The statistic test demontrated that there are not signifficant different mental stress level for driver between mRR and F - NASA TLX. The city road produced avarage F - NASA TLX = 3.92 and mRR = 612.40ms, rural road produced avarage F - NASA TLX = 3.46 and mRR = 621.26 ms, and motorway produced avarage F - NASA TLX = 2.50 and mRR = 820.20 ms. In sort, the mRR of HRV data can be used to monitor the mental stress level of driver in real time as consequence it baneficely implemented in car alert safety system.
- World Health Organization. (2015). Global status report on road safety. Injury Prevention, 318. https://doi.org/http://www.who.int/violence_injury_prevention/road_safety_status/2015/en/Google Scholar
- Soehodho, S. (2017). Public transportation development and traffic accident prevention in Indonesia. IATSS Research.Google Scholar
- Taylor, A. H., & Dorn, L. (2006). Stress, Fatigue, Health, and Risk of Road Traffic Accidents among Professional Drivers: The Contribution of Physical Inactivity. Annual Review of Public Health, 27(1), 371--391.Google ScholarCross Ref
- Mesken, J., Hagenzieker, M. P., Rothengatter, T., & de Waard, D. (2007). Frequency, determinants, and consequences of different drivers' emotions: An on-the-road study using self-reports, (observed) behaviour, and physiology. Transportation Research Part F: Traffic Psychology and Behaviour, 10(6), 458--475.Google ScholarCross Ref
- Patil, K., Singh, M., Singh, G., & Sharma, N. (2015). Mental Stress Evaluation using Heart Rate Variability Analysis: A Review. International Journal Of Public Mental Health And Neurosciences IJPMN, 2(1), 2394--4668. Retrieved from http://www.sarvasumana.in/files/13.pdfGoogle Scholar
- Reisman, S. (1997). Measurement of physiological stress. Proceedings of the IEEE 23rd Northeast Bioengineering Conference.Google ScholarCross Ref
- Kofman, O., Meiran, N., Greenberg, E., Balas, M., & Cohen, H. (2006). Enhanced performance on executive functions associated with examination stress: Evidence from task-switching and Stroop paradigms. Cognition and Emotion, 20(5), 577--595.Google ScholarCross Ref
- Crowley, O. V., McKinley, P. S., Burg, M. M., Schwartz, J. E., Ryff, C. D., Weinstein, M., Sloan, R. P. (2011). The interactive effect of change in perceived stress and trait anxiety on vagal recovery from cognitive challenge. International Journal of Psychophysiology, 82(3), 225--232.Google ScholarCross Ref
- Sun, F. F.-T., Kuo, C., Cheng, H. H.-T., Buthpitiya, S., Collins, P., & Griss, M. (2012). Activity-Aware Mental Stress Detection Using Physiological Sensors. In Mobile Computing, (Vol. 76, pp. 211--230).Google Scholar
- Healey, J., & Picard, R. (2000). Smart Car: Detecting Driver Stres. In 15th International Conference on Pattern Recognition (pp. 218--221). Google ScholarDigital Library
- Vrijkotte, T. G. M., van Doornen, L. J. P., & de Geus, E. J. C. (2000). Effects of Work Stress on Ambulatory Blood Pressure, Heart Rate, and Heart Rate Variability. Hypertension, 35(4), 880--886.Google ScholarCross Ref
- Teisala, T., Mutikainen, S., Tolvanen, A., Rottensteiner, M., Leskinen, T., Kaprio, J., ... Kujala, U. M. (2014). Associations of physical activity, fitness, and body composition with heart rate variability-based indicators of stress and recovery on workdays: A cross-sectional study. Journal of Occupational Medicine and Toxicology, 9(1).Google ScholarCross Ref
- Reed, M. J., Robertson, C. E., & Addison, P. S. (2005). Heart rate variability measurements and the prediction of ventricular arrhythmias. QJM - Monthly Journal of the Association of Physicians.Google Scholar
- Cao, A., Chintamani, K. K., Pandya, A. K., & Ellis, R. D. (2009). NASA TLX: Software for assessing subjective mental workload. Behavior Research Methods, 41(1), 113--117.Google ScholarCross Ref
- Taelman, J., Vandeput, S., Spaepen, A., & Van Huffel, S. (2008). Influence of mental stress on Heart Rate and Heart Rate Variability. In 4th European conference of the international federation for medical and biological engineering (IFMBE) (pp. 1366--1369).Google Scholar
- McDuff, D., Gontarek, S., & Picard, R. (2014). Remote measurement of cognitive stress via heart rate variability. Conference Proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2014, 2957--2960.Google Scholar
- Sun, F., Kuo, C., Cheng, H., Buthpitiya, S., Collins, P., & Griss, M. (2012). Activity-aware Mental Stress Detection Using Physiological Sensors. Mobile Computing, Applications, and Services, 76, 1--20.Google Scholar
- Pomer-Escher, A. G., De Souza, M. D. P., & Filho, T. F. B. (2014). Methodology for analysis of stress level based on asymmetry patterns of alpha rhythms in EEG signals. In ISSNIP Biosignals and Biorobotics Conference, BRC.Google ScholarCross Ref
- Boonnithi, S., & Phongsuphap, S. (2011). Comparison of heart rate variability measures for mental stress detection. Computing in Cardiology, 38, 85--88.Google Scholar
- Sugiono, S., Widhayanuriyawan, D., & Andriani, D. P. (2017). Investigating the impact of road condition complexity on driving workload based on subjective measurement using NASA TLX. In MATEC Web of Conferences (Vol. 136).Google ScholarCross Ref
Index Terms
- Mental Stress Evaluation of Car Driver in Different Road Complexity Using Heart Rate Variability (HRV) Analysis
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