Skip to main content
Log in

Driver’s drowsiness inhibition by subcutaneous stimulation based on SNS activity

  • Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

The overall aim of the study is to develop the ambient drowsiness control programs based on driver’s physiological states. this study is developed and verified of a system that controls a driver’s drowsiness a stimulus that is too small to be noticed by a driver. Most studies on driver drowsiness have focused on the detection or evaluation of psychological states in some way. Our system assumes that a small change in temperature affects peripheral thermoreceptors and that afferent fibers transmit this stimulus to the cerebral center via the spinal nerves. To evaluate the system, we constructed a virtual reality system for automobile driving using an experimental method described in our previous studies. In this study, drowsiness was controlled by our system, and the effectiveness of the system was tested. The results suggest that this is an efficient method for controlling driver drowsiness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Seki R (2007) Intelligent transport system (ITS). Automob Technol 61:165–171

  2. Yanagidaira M, Yasushi M (2005) Assisting technology for safe driving through a fusion of multi sensing in a vehicle-for preventing from falling asleep at the wheel on a cooperation of biological information and car navigation-related technology. J Soc Instrum Control Eng 44(3):210–215

    Google Scholar 

  3. Yanagidaira M, Yasushi M (2007) Method for predicting drowsiness. Pioneer R&D 17(1):1–8

    Google Scholar 

  4. Tsuchida A, Oguri K (2009) Estimation of drowsiness level based on eyelid closure and heart rate variability. IEICE technical report MBE, ME and bio-cybernetics, vol 109(123), pp 69–72

  5. Miyazawa T, Fukumoto I (2007) A basic study for development of drowsiness detecting algorithm by physiologic indices. IEICE technical report MBE, ME and bio-cybernetics, vol 107(218), pp 3–6

  6. Nakayama M, Yamamoto K, Kobayashi F (2008) Relationship between subjective sleepiness and powers of frequency components for pupillary response. IEICE technical report MBE, ME and bio-cybernetics, vol 108(126), pp 5–10

  7. Hayata Y, Kawanaka H, Oguri K (2013) Early prediction of the driver’s low arousal state using the biological information before and while driving. IEEJ Trans Electr Inf Syst 133(12):2160–2166

    Google Scholar 

  8. Omi T (2013) The image sensor which assess a sleepiness of the driver. JSAO 42(1):99–103

    Google Scholar 

  9. Tanaka H, Ide H, Nagashima Y (1999) Attempt of feeling estimation by analysis of nasal skin temperature and arousal level. Trans Hum Interf Soc 1(4):51–56

    Google Scholar 

  10. Sakamoto T, Nozawa A, Tanaka H (2006) Evaluation of the driver’s temporary arousal level by facial skin thermogram—effect of surrounding temperature and wingd on the thermogram. IEEJ Trans Electr Inf Syst 126(7):804–809

    Google Scholar 

  11. Nozawa A, Takano M (2009) Correlation analysis on alpha attenuation and nasal skin temperature. J Stat Mech 01:P01007

    Google Scholar 

  12. Asano H, Sakamoto N, Ide H (2010) Evaluation of driver’s temporary arousal level of driver with a facial blood image. IEEJ Trans Electr 130(1):133–138

    Google Scholar 

  13. Takahashi T (2009) The effects of intermittent bright light exposure during daytimeon daytime sleepiness, the multiple sleep latency test and P300. Hosei Univ Fac Lett Bull 60:113–119

    Google Scholar 

  14. JSPA (1996) Human being measurement handbook. Gihodobooks

  15. Kodawara K, Tsutsumi N, Ashitaka Y, Shimada H (2008) The effect of RRI on skill acquisition. Jpn J Ergon 44:262–263

    Article  Google Scholar 

  16. Uusitalo AL, Uusitalo AJ, Rusko HK (2000) Heart rate and blood pressure variability during heavy training and overtraining in the female athlete. Journal article, research support, non-U.S. Gov’t, vol 21(1), pp 45–53

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yasutaka Kajiwara.

Additional information

This work was presented in part at the 20th International Symposium on Artificial Life and Robotics, Beppu, Oita, January 21–23, 2015.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kajiwara, Y., Asano, H., Bando, S. et al. Driver’s drowsiness inhibition by subcutaneous stimulation based on SNS activity. Artif Life Robotics 20, 341–346 (2015). https://doi.org/10.1007/s10015-015-0236-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-015-0236-7

Keywords

Navigation