Preliminary Result For Electroencephalogram Signal For Sleep Deprivation Under Simulated Driving

Sleep deficiency or fatigue causes sleepy driving, which contributes to motor vehicle collisions. Numerous empirical studies have linked driver fatigue to traffic accidents. Sleepiness must start immediately to avoid a calamity. The measurement of biosignals can help explain this occurrence. However...

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Bibliographic Details
Published in2023 International Conference on Engineering Technology and Technopreneurship (ICE2T) pp. 293 - 298
Main Authors Yaakop, Muhyi, Abdul Kadir, Muhd Khairulzaman, Fauzi Abu Hassan, Mohd, Yaacob, Sazali, Suboh, Mohd Zubir, Azli, Muhammad
Format Conference Proceeding
LanguageEnglish
Published IEEE 15.08.2023
Subjects
biosensors
Cameras
Disasters
drowsiness
Electrocardiogram
Electroencephalography
Fatigue
Recording
Roads
signal processing
simulated driving
Sleep
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Summary:Sleep deficiency or fatigue causes sleepy driving, which contributes to motor vehicle collisions. Numerous empirical studies have linked driver fatigue to traffic accidents. Sleepiness must start immediately to avoid a calamity. The measurement of biosignals can help explain this occurrence. However, signal recording attachments for most biosensors are complicated. A wearable sensor could solve this problem. This work developed and tested a method for obtaining EEG and PPG data using non-wearable sensors and wearable sensors, respectively, to determine their relationship. The study uses a driving simulator to examine induced weariness. A party of ten had to drive a virtual road for 30 minutes without interruptions. The car's motions and individuals' conduct were recorded on video cameras using the PPG bio-signal and four EEG channels. Preprocessed EEG data was used to create three main indicators and three ratio index values. EEG Alpha/Theta waves, which show the transition from rest to exhaustion, differed significantly between drivers who sleep less than eight hours and those who sleep more than eight. The beta/gamma range of power spectrum density (PSD) showed a similar result with complete attention. The present study additionally evaluated EEG patterns before and after driving to assess cognitive vigilance and compare them to the subjective Karolinska Sleepiness Scale. The power spectral density (PSD) analysis and rate of sleepiness assessment show significant variations that suggest driver attention impairment between driving sessions.
DOI:10.1109/ICE2T58637.2023.10540542