header
Local cover image
Local cover image
Image from OpenLibrary

Automatic detection of driver drowsiness during simulated driving using brainwaves changes as indicator / Ahmed Abdelhamid Mohamed Torki ; Supervised Ayman M. Eldeib

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ahmed Abdelhamid Mohamed Torki , 2018Description: 79 P. : charts , facsimiles ; 30cmOther title:
  • الكشف الاوتوماتيكي لنعاس السائق اثناء القيادة بالمحاكاة باستخدام التغييرات في الموجات الدماغية كمؤشر [Added title page title]
Subject(s): Online resources: Available additional physical forms:
  • Issued also as CD
Dissertation note: Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering Summary: Driver drowsiness contributes widely in vehicle accidents. Studies assessed drowsiness indicators at different driving setups. The first objective was to establish an experiment to obtain generic datasets of brainwaves epochs recorded by electroencephalogram (EEG) at forehead sites labeled with alertness and drowsiness for subjects using facial expressions recorded by videos. Subjects perform simulated driving for two hours after 6 PM. The second and third objective were to extract and select significant features that yield to highest classification accuracy between alert and drowsy using statistical and classification methods. The results showed the classification accuracy was 85.8 %
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2018.Ah.A (Browse shelf(Opens below)) Not for loan 01010110076124000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.03.Ph.D.2018.Ah.A (Browse shelf(Opens below)) 76124.CD Not for loan 01020110076124000

Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

Driver drowsiness contributes widely in vehicle accidents. Studies assessed drowsiness indicators at different driving setups. The first objective was to establish an experiment to obtain generic datasets of brainwaves epochs recorded by electroencephalogram (EEG) at forehead sites labeled with alertness and drowsiness for subjects using facial expressions recorded by videos. Subjects perform simulated driving for two hours after 6 PM. The second and third objective were to extract and select significant features that yield to highest classification accuracy between alert and drowsy using statistical and classification methods. The results showed the classification accuracy was 85.8 %

Issued also as CD

There are no comments on this title.

to post a comment.

Click on an image to view it in the image viewer

Local cover image