Published Paper Details:

Now a days people spend their most of the time overthinking and are not attentive in many situations such as while driving, in classrooms, studying, flying airplane and many other situations. Therefore, we can make them alert then they can increase their attentiveness and be cautious and avoid risks. This task of alerting an individual to be attentive can be achieved with the help of analysis of EEG signals. The EEG signals are collected from the scalp of human brain. The part of human brain from where we collect these signals is called as frontal cortex. This part of brain generates signals which can give us the accurate value of attention level of our brain. These EEG signals are generated as activity of neurons and it is measured in volts The attentive state of an individual is predicted by using the raw EEG signals and processing by techniques like denoising which include FIR filter, Wavelet Transform and Hilbert Transform, feature extraction, feature selection and classification techniques like SVM, Tri layered Neural Network and Medium KNN available in MATLAB. Therefore, using these EEG signals we can efficiently train our algorithm to classify the state of human being as attentive or non - attentive.