Development of a Drowsiness Detector based on the Duration of Eye closure using A Low-Cost EMG

Authors

  • Dian Artanto Mekatronika, Politeknik Mekatronika Sanata Dharma, Yogyakarta - INDONESIA
  • Ign. Deradjad Pranowo Mekatronika, Politeknik Mekatronika Sanata Dharma, Yogyakarta - INDONESIA
  • M. Prayadi Sulistyanto Desain Produk Mekatronika, Politeknik Mekatronika Sanata Dharma, Yogyakarta - INDONESIA
  • Ervan Erry Pramesta Desain Produk Mekatronika, Politeknik Mekatronika Sanata Dharma, Yogyakarta - INDONESIA

Keywords:

traffic accidents, a drowsiness detector, an eye closure duration, a low-cost EMG, an eyeglass frame

Abstract

Many traffic accidents are caused by drivers who are less concentrated due to drowsiness. From existing reports, it is known that the loss due to traffic accidents is very large, not only bring bad impact to the victims, also for the family environment, community and country. Seeing the conditions of this traffic problem, a device that can wake the driver while sleepy can be a solution. From several studies on drowsiness, it has been found that there is a connection between the drowsiness with blinking and closing the eyes often and long. This paper proposes a device that can detect the duration and frequency of eye closure using a low-cost EMG. When the accumulated duration of the eye closure exceeds the specified limit, a buzzer will sound to wake the driver. Compared to other detection devices, the low-cost EMG-based drowsy detector is promising, as it can be mounted practically on an eyeglass frame, and does not damage or injure the eyes. The development of this device so that it can be a reliable and economical device becomes an interesting challenge for the author and his team.

References

Advancer Technologies, 2013. Muscle Sensor v3 User’s Manual. Available at: http://www.advancertechnologies.com/p/muscle-sensor-v3.html, accessed on September 5, 2017.

Agrawal, D.P., 2017. Embedded Sensor Systems. © Springer Nature Singapore Pte Ltd., ISBN 978-981-10-3037-6. ISBN 978-981-10-3038-3 (eBook) DOI 10.1007/978-981-10-3038-3.

Bandara, I. B., 2009. Driver drowsiness detection based on eye blink”, Faculty of Enterprise & Innovation, Buckinghamshire New University, Brunel University, March.

García, I., Bronte, S., Bergasa, L. M., Hernandez, N., Delgado, B., Sevillano, M., 2010. Vision-based drowsiness detector for a Realistic Driving Simulator. Intelligent Transportation Systems (ITSC), 13th International IEEE Conference on.

Ma’touq, J., Al-Nabulsi, J., Al-Kazwini, A., Baniyassien, A., Issa1, G. A., Mohammad, H., 2014. Eye blinkingbased method for detecting driver drowsiness. J Med Eng Technology 38(8): 416–419, ©2014 Informa UK Ltd., ISSN: 0309-1902 (print), 1464-522X (electronic).

Mardi, Z., Ashtiani, S.N., Mikaili, M., 2011. EEG-based Drowsiness Detection for Safe Driving Using Chaotic Features and Statistical Tests. J Med Signals Sens. May;1(2):130-7.

Puspasari, M. A., Muslim, E., Moch, B. N., Aristides, A., 2015. Fatigue Measurement in Car Driving activity using Physiological, Cognitive, and Subjective Approaches. International Journal of Technology 6: 971-975, ISSN 2086-9614.

Soehodho, S., 2017. Public Transportation Development and Traffic Accident Prevention in Indonesia. IATSS Research, 40, pp. 76-80.

Sugiyanto, G., 2017. The Cost of Traffic Accident and Equivalent Accident Number in Developing Countries (Case Study In Indonesia). ARPN Journal of Engineering and Applied Sciences, 12(2), pp. 389-397.

Svensson, U., 2004. Blink behaviour based drowsiness detection – method development and validation. Master’s thesis project in Applied Physics and Electrical Engineering, Swedish National Road and Transport Research Institute, ISSN 1102-626X.

World Health Organization, 2015. Global Status Report on Road Safety 2015. Available at: http://www.who.int/violence_injury_prevention/ road_safety_status/2015/en/, accessed on September 5, 2017.

Zuraida, R., Iridiastadi, H., Sutalaksan, I. Z., 2017. Indonesian driver's characteristics associated with road accidents. International Journal of Technology 2: 311-319, ISSN 2086-9614.

Published

2017-11-01

Issue

Section

FoITIC 2017