Effect of drowsiness on mechanical arm admittance and driving performances

Effect of drowsiness on mechanical arm admittance and driving performances

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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.


    1. 1)
      • 1. World Health Organization: ‘Global status report on road safety 2013: supporting a decade of action’, 2013.
    2. 2)
      • 2. Jordan, W., Hajak, G.:‘Gestörter Schlaf - was tun?’ (München Arcis Editions, Munich, 1997).
    3. 3)
      • 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.
    4. 4)
      • 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.
    5. 5)
      • 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.
    6. 6)
      • 6. Sahayadhas, A., Sundaraj, K., Murugappan, M.: ‘Detecting driver drowsiness based on sensors: a review’, Sensors, 2012, 12, (12), pp. 1693716953.
    7. 7)
      • 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.
    8. 8)
      • 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.
    9. 9)
      • 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.
    10. 10)
      • 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.
    11. 11)
      • 11. Federal Highway Administration: ‘Commercial motor vehicle driver fatigue and alertness study’ (U.S. Department of Transportation, Washington, DC), pp. 315.
    12. 12)
      • 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.
    13. 13)
      • 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.
    14. 14)
      • 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.
    15. 15)
      • 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.
    16. 16)
      • 16. Wang, X., Xu, C.: ‘Driver drowsiness detection based on non-intrusive metrics considering individual specifics’, Accid. Anal. Prevent., 2015, 95, pp. 350357.
    17. 17)
      • 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.
    18. 18)
      • 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.
    19. 19)
      • 19. Johns, M.W.: ‘The amplitude-velocity ratio of blinks: a new method for monitoring drowsiness’, Sleep, 2003, 26, pp. 5152.
    20. 20)
      • 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.
    21. 21)
      • 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.
    22. 22)
      • 22. Thiffault, P., Bergeron, J.: ‘Monotony of road environment and driver fatigue: a simulator study’, Accid. Anal. Prevent., 2003, 35, (3), pp. 381391.
    23. 23)
      • 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.
    24. 24)
      • 24. Jenkins, G., Watts, D.: ‘Spectral analysis and its applications’ (Holden-day, San Francisco, 1968).
    25. 25)
      • 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.
    26. 26)
      • 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.
    27. 27)
      • 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.
    28. 28)
      • 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.
    29. 29)
      • 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.
    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)
      • 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.
    32. 32)
      • 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.

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