Real Time Driver’s Drowsiness Detection by Processing the EEG Signals Stimulated with External Flickering Light
نویسندگان
چکیده
The objective of this study is development of driver's sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between closed eyes and opened eyes. Fourier transforms and power spectrum density features extracted from signals and Multilayer perceptron and radial basis function neural networks used for classification. The experimental results show an accuracy of 97% for test data.
منابع مشابه
Real Time Driver’s Drowsiness Detection by Processing the EEG Signals Stimulated with External Flickering Light
The objective of this study is development of driver’s sleepiness using Visually Evoked Potentials (VEP). VEP computed from EEG signals from the visual cortex. We use the Steady State VEPs (SSVEPs) that are one of the most important EEG signals used in human computer interface systems. SSVEP is a response to visual stimuli presented. We present a classification method to discriminate between...
متن کاملطراحی و ساخت یک سیستم تشخیص خواب آلودگی راننده مبتنی بر پردازشگر سیگنال TMS320C5509A
Every year, many people lose their lives in road traffic accidents while driving vehicles throughout the world. Providing secure driving conditions highly reduces road traffic accidents and their associated death rates. Fatigue and drowsiness are two major causes of death in these accidents; therefore, early detection of driver drowsiness can greatly reduce such accidents. Results of NTSB inves...
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