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Drowsiness detection while driving using fractal analysis and wavelet transform
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Parikh, Prachi. Drowsiness detection while driving using fractal analysis and wavelet transform. Retrieved from https://doi.org/doi:10.7282/T3QC03W9

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Uniform TitleDrowsiness detection while driving using fractal analysis and wavelet transform
NameParikh, Prachi (author); Micheli-Tzanakou, Evangelia (chair); Shoane, George (internal member); Drzeweicki, Gary (internal member); Rutgers University; Graduate School - New Brunswick
Date Created2007
Other Date2007 (degree)
SubjectBiomedical Engineering, Automobile drivers--Psychology, Drowsiness, Fractals, Wavelets (Mathematics)
Extentvii, 87 pages
DescriptionThe EEG signal plays a key role as a nondestructive testing method in the diagnosis and functional determination of the brain. EEG recordings represent changes in alertness, arousal, sleep and cognition. Boredom, fatigue and monotony of a task may induce drowsiness that leads to a decrease in alertness. This can have serious consequences in tasks involving constant vigilance and control such as driving. In the current study, EEG signals are recorded using a car simulator and analyzed using Fractal analysis and Wavelet Transform. It is observed that there is an increase in the alpha frequencies in the latter stages of driving indicating a state of drowsiness. The analysis techniques used provide results quickly, which is essential to provide instant feedback.
NoteM.S.
NoteIncludes bibliographical references (p. 82-87).
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/T3QC03W9
LanguageEnglish
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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