Driver drowsiness detection using EEG power spectrum analysis

Muhammad Awais, Nasreen Badruddin, Micheal Drieberg

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)peer-review

34 Citations (Scopus)


Driver drowsiness is considered to be a very critical issue causing many fatal accidents, injuries and property damages. Therefore, it has been an area of intensive research in recent years. In this paper, a driving simulator based study was conducted to observe the significant changes that occur in the EEG power spectrum during monotonous driving. Nine healthy university students voluntarily participated in the experiment. The absolute band power of the EEG signal was computed by taking the FFT of the time series signal and then the power spectral density was computed using Welch method. Our findings conclude that alpha and theta band powers increase significantly (p<0.05) when a subject moves from alert state to drowsy state. These changes are more dominant in the occipital and parietal regions when compared to the other regions. The findings of this study provide a promising drowsiness indicator which can be used to prevent road accidents caused by driver drowsiness.

Original languageEnglish
Title of host publicationIEEE TENSYMP 2014 - 2014 IEEE Region 10 Symposium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781479920280
ISBN (Print)9781479920273, 9781479920280
Publication statusPublished - 24 Jul 2014
Event2014 IEEE Region 10 Symposium, IEEE TENSYMP 2014 - Kuala Lumpur, Malaysia
Duration: 14 Apr 201416 Apr 2014

Publication series

NameIEEE TENSYMP 2014 - 2014 IEEE Region 10 Symposium


Conference2014 IEEE Region 10 Symposium, IEEE TENSYMP 2014
CityKuala Lumpur


  • Alpha band power
  • Drowsiness
  • EEG


Dive into the research topics of 'Driver drowsiness detection using EEG power spectrum analysis'. Together they form a unique fingerprint.

Cite this