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access icon free Effect of drowsiness on mechanical arm admittance and driving performances

Drowsiness as one of the impaired driving behaviour is an important area of concern in ground transportation safety. It can coincide with skill-demanding situations that may lead to vehicle control loss and possibly traffic accidents. Although drowsiness effects on driving performances have been widely investigated, there are few studies that propose a description of its effect on human neuromuscular state. To address this issue, this study aims to investigate the effects of drowsiness on driver neuromuscular state via the estimation of mechanical arm admittance. Mechanical arm admittance is a car dedicated parameter that gives information about arm stiffness of driver and its corresponding response in the frequency domain. Ten participants performed an experiment on a driving simulator, where they experienced steering disturbances, which aims to estimate variations of mechanical arm admittance as well as variations of driving performances between alert and drowsy states. Moreover, variation in driving performances were assessed by the variation of steering reversal rate and standard deviation of lane position. Results indicate that drowsiness increases the gain of mechanical arm admittance for arm movements <2.5 Hz and also deteriorates car steering control, increasing the steering operations amplitude and leading to larger vehicle lateral deviations.

References

    1. 1)
      • 1. World Health Organization: ‘Global status report on road safety 2013: supporting a decade of action’, 2013.
    2. 2)
      • 28. Abbink, D., Mulder, M., Van Paassen, M.M.: ‘Measurements of muscle use during steering wheel manipulation’, IEEE Int. Conf. Systems, Man, and Cybernetics, Anchorage, AK, USA, 2011, pp. 16521657.
    3. 3)
      • 29. Joly, A., Nakano, K., Zheng, R., et al: ‘Effects of drowsiness on driver's mechanical arm admittance’, Seisan Kenkyu, 2015, 67, (2), pp. 199204.
    4. 4)
      • 2. Jordan, W., Hajak, G.:‘Gestörter Schlaf - was tun?’ (München Arcis Editions, Munich, 1997).
    5. 5)
      • 20. Katzourakis, D., Abbink, D., Velenis, E., et al: ‘Driver's arms’ time-variant neuromuscular admittance during real car test-track driving’, IEEE Trans. Instrum. Meas., 2014, 63, (1), pp. 221230.
    6. 6)
      • 5. Ingre, M., ÅKerstedt, T., Peters, B., et al: ‘Subjective sleepiness, simulated driving performance and blink duration: examining individual differences’, J. Sleep Res., 2006, 15, pp. 4753.
    7. 7)
      • 14. Kar, S., Bhagat, M., Routray, A.: ‘EEG signal analysis for the assessment and quantification of driver's fatigue’, Transp. Res. F,Traffic Psychol.Behav., 2010, 13, (5), pp. 297306.
    8. 8)
      • 31. Verster, J.C., Roth, T.: ‘Standard operation procedures for conducting the on-the-road driving test, and measurement of the standard deviation of lateral position (SDLP)’, Int. J. Gen. Med., 2011, 4, p. 359.
    9. 9)
      • 10. McDonald, A.D., Schwarz, C., Lee, J.D., et al: ‘Real-time detection of drowsiness related lane departures using steering wheel angle’. Proc. Human Factors and Ergonomics Society, Boston, USA, 2012, vol. 56, (1), pp. 22012205.
    10. 10)
      • 3. Johns, M. W., Tucker, A., Chapman, R., et al: ‘Monitoring eye and eyelid movements by infrared reflectance oculography to measure drowsiness in drivers’, Somnologie (Berl), 2007, 11, (4), pp. 234242.
    11. 11)
      • 22. Thiffault, P., Bergeron, J.: ‘Monotony of road environment and driver fatigue: a simulator study’, Accid. Anal. Prevent., 2003, 35, (3), pp. 381391.
    12. 12)
      • 11. Federal Highway Administration: ‘Commercial motor vehicle driver fatigue and alertness study’ (U.S. Department of Transportation, Washington, DC), pp. 315.
    13. 13)
      • 4. Kokonozi, A. K., Michail, E. M., Chouvarda, I. C., et al: ‘Study of heart rate and brain system complexity and their interaction in sleep-deprived subjects’. Proc. Conf. Computers in Cardiology, Bologna, Italy, September 2008, pp. 969971.
    14. 14)
      • 7. Wells, A. S., Read, N. W., Craig, A.: ‘Influences of dietary and intraduodenal lipid on alertness, mood, and sustained concentration’, Br. J. Nutr., 1995, 74, (01), pp. 115123.
    15. 15)
      • 6. Sahayadhas, A., Sundaraj, K., Murugappan, M.: ‘Detecting driver drowsiness based on sensors: a review’, Sensors, 2012, 12, (12), pp. 1693716953.
    16. 16)
      • 23. Dolan, D.C., Taylor, D. J., Okonkwo, R., et al: ‘The time of day sleepiness scale to assess differential levels of sleepiness across the day’, J. Psychosom. Res., 2009, 67, (2), pp. 127133.
    17. 17)
      • 13. Abu N Basim, M., Sathyabalan, P., Suresh, P.: ‘Analysis of EEG signals and facial expressions to detect drowsiness and fatigue using Gabor filters and SVM linear classifier’, Int. J. Comput. Appl., 2015, 115, (11), pp. 914.
    18. 18)
      • 15. Jung, S.J., Shin, H. S., Chung, W.Y.: ‘Driver fatigue and drowsiness monitoring system with embedded electrocardiogram sensor on steering wheel’, IET Intell. Transp. Syst., 2014, 8, (1), pp. 4350.
    19. 19)
      • 21. De Vlugt, E., Schouten, A.C., Van Der Helm, F., et al: ‘Adaptation of reflexive feedback during arm posture to different environments’, Biol. Cybern., 2002, 87, (1), pp. 1026.
    20. 20)
      • 17. Caffier, P.P., Erdmann, U., Ullsperger, P.: ‘Experimental evaluation of eye-blink parameters as a drowsiness measure’, Eur. J. Appl. Physiol., 2003, 89, (3), pp. 319325.
    21. 21)
      • 24. Jenkins, G., Watts, D.: ‘Spectral analysis and its applications’ (Holden-day, San Francisco, 1968).
    22. 22)
      • 26. Sommer, D., Golz, M.: ‘Evaluation of PERCLOS based current fatigue monitoring technologies’. IEEE Annual Int. Conf. Engineering in Medicine and Biology Society, Buenos Aires, Argentina, 2010, pp. 44564459.
    23. 23)
      • 32. Cheng, B., Zhang, W., Lin, Y., et al: ‘Driver drowsiness detection based on multisource information’, Hum. Factors Ergon. Manuf., Serv. Ind., 2012, 22, (5), pp. 450467.
    24. 24)
      • 18. Liu, D., Sun, P., Xiao, Y., et al: ‘Drowsiness detection based on eyelid movement’. Second Int. Workshop on Education Technology and Computer Science (ETCS), 2010, vol. 2, pp. 4952.
    25. 25)
      • 19. Johns, M.W.: ‘The amplitude-velocity ratio of blinks: a new method for monitoring drowsiness’, Sleep, 2003, 26, pp. 5152.
    26. 26)
      • 8. Bubenik, G.A., Ball, R.O., Pang, S.F.: ‘The effect of food deprivation on brain and gastrointestinal tissue levels of tryptophan, serotonin, 5-hydroxyindoleacetic acid, and melatonin’, J. Pineal Res., 1992, 12, (1), pp. 716.
    27. 27)
      • 16. Wang, X., Xu, C.: ‘Driver drowsiness detection based on non-intrusive metrics considering individual specifics’, Accid. Anal. Prevent., 2015, 95, pp. 350357.
    28. 28)
      • 9. Forsman, P.M., Vila, B. J., Short, R.A., et al: ‘Efficient driver drowsiness detection at moderate levels of drowsiness’, Accid. Anal. Prevent., 2013, 50, pp. 341350.
    29. 29)
      • 12. Johnson, R.R., Popovic, D.P., Olmstead, R.E., et al: ‘Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model’, Biol. Psychol., 2011, 87, (2), pp. 241250.
    30. 30)
      • 30. McLean, J.R., Hoffmann, E.R.: ‘Steering reversals as a measure of driver performance and steering task difficulty’, Hum. Factors J. Hum. Factors Ergon. Soc., 1975, 17, (3), pp. 248256.
    31. 31)
      • 25. Ahlstrom, C., Nyström, M., Holmqvist, K., et al: ‘Fit-for-duty test for estimation of drivers’ sleepiness level: eye movements improve the sleep/wake predictor’, Transp. Res. C Emerging Technol., 2013, 26, pp. 2032.
    32. 32)
      • 27. Najafi, B., Aminian, K., Paraschiv-Ionescu, A., et al: ‘Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly’, IEEE Trans. Biomed. Eng., 2003, 50, (6), pp. 711723.
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