A portable device for real time drowsiness detection using novel active dry electrode system.
Electroencephalogram (EEG) signals give important information about the vigilance states of a subject. Therefore, this study constructs a real-time EEG-based system for detecting a drowsy driver. The proposed system uses a novel six channels active dry electrode system to acquire EEG non-invasively. In addition, it uses a TMS320VC5510 DSP chip as the algorithm processor, and a MSP430F149 chip as a controller to achieve a real-time portable system. This study implements stationary wavelet transform to extract two features of EEG signal: integral of EEG and zero crossings as the input to a back propagation neural network for vigilance states classification. This system can discriminate alertness and drowsiness in real-time. The accuracy of the system is 79.1% for alertness and 90.91% for drowsiness states. When the system detects drowsiness, it will warn drivers by using a vibrator and a beeper.
Tsai
Pai-Yuan
PY
Chung Yuan Christian University, Chung Li, ROC. view@mhit.url.com.tw
Hu
Weichih
W
Kuo
Terry B J
TB
Shyu
Liang-Yu
LY
D000063:Accidents, Traffic / Q000517:prevention & control*; D000328:Adult; D001334:Automobile Driving; D003020:Clothing; D003195:Computer Communication Networks; D003199:Computer Systems; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D004867:Equipment Design; D006801:Humans; D016571:Neural Networks, Computer; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D012894:Sleep Stages; D014584:User-Computer Interface; D014851:Wakefulness