Sleep Analysis by Using Minimum EEG Lead System

Abstract

Each and every day, thousands of people lose their lives in accidents occurring in roads and highways all over the world. Although there are many factors behind these collisions, one of the most significant reasons is drowsy driving. Drowsiness is a serious issue for the drivers since driving needs a sustained attention. So detection of drowsiness is necessary to prevent drowsy driving. By analyzing different bio-logical signals, we can point out drowsiness and fatigue level of a driver. Studies are going on to find systems capable of monitoring the biological condition of a driver and issuing warnings during the instance of drowsiness and inattention. Electroencephalogram (EEG) is the electrical activity of brain which is easily affected by fatigue and sleep deprivation. In this study, we are proposing a drowsiness detection system using frequency domain analysis and power spectral analysis of a single channel EEG signal. Here we propose an algorithm for differentiating between normal and sleepy condition. Thus drowsy driving and its subsequent catastrophe can be avoided by monitoring the brain activity of the driver and taking proper measures based upon the detection of drowsiness.