Preventive Detection of Driver Drowsiness from EEG Signals using Fuzzy Expert Systems

Authors

  • Rony Almiron Universidad Nacional de San Agustín de Arequipa, Perú https://orcid.org/0000-0002-3488-1761
  • Bruno Adolfo Castillo Universidad Nacional de San Agustín de Arequipa, Perú https://orcid.org/0000-0003-1135-2688
  • Andrés Montoya Angulo Universidad Nacional de San Agustín de Arequipa, Perú
  • Elvis Supo Universidad Nacional de San Agustín de Arequipa, Perú https://orcid.org/0000-0003-4749-8400
  • Jesús José Fortunato Talavera Universidad Nacional de San Agustín de Arequipa, Perú
  • Daniel Domingo Yanyachi Aco Cardenas Universidad Nacional de San Agustín de Arequipa, Perú

DOI:

https://doi.org/10.17488/RMIB.45.1.1

Keywords:

drive drowsiness, electroencephalogram, expert systems, sleepiness detection

Abstract

Currently, the percentage of traffic accidents has increased, and according to statistics, this percentage will continue to increase every year, so it is necessary to develop new technologies to prevent this kind of accidents. This paper presents a drowsiness detection system based on electroencephalogram (EEG) signals using a pair of channels (Fp1 and Fp2) applied to drivers before entering their vehicles. First, this model detects the relationship between the area under the curve (AUC) of alpha brain waves, an effective parameter for detecting drowsiness. Then, the extracted information is passed to a fuzzy expert system (FES) that classifies the subject's state as "alert" or "sleepy"; the criterion used was a threshold and training with subjective levels. The proposed system was compared with neural network models, such as support vector machine (SVM), K nearest neighbors (KNN), and random forest (RF). Measurements of one hundred and twenty minutes were performed on each of the ten drivers for two days to test the system. The tests confirm that this system is suitable for preventive measures and that the fuzzy system is superior to traditional neural network methods.

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Published

2024-02-29

How to Cite

Almiron, R., Castillo, B. A., Montoya Angulo, A., Supo, E., Talavera, J. J. F., & Yanyachi Aco Cardenas, D. D. (2024). Preventive Detection of Driver Drowsiness from EEG Signals using Fuzzy Expert Systems. Revista Mexicana De Ingenieria Biomedica, 45(1), 6–20. https://doi.org/10.17488/RMIB.45.1.1

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