Sleep Analysis by Using Minimum EEG Lead System

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dc.contributor.author Khan, Sifat Shahriar
dc.contributor.author Ahmed, Ashfak Uddin
dc.contributor.author Hasan, Rashedul
dc.date.accessioned 2021-10-01T07:03:01Z
dc.date.available 2021-10-01T07:03:01Z
dc.date.issued 2014-11-15
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dc.identifier.uri http://hdl.handle.net/123456789/1060
dc.description Supervised by Md. Taslim Reza, Assistant Professor, Department of Electrical and Electronic Engineering (EEE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh. en_US
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh en_US
dc.title Sleep Analysis by Using Minimum EEG Lead System en_US
dc.type Thesis en_US


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