Real Time System to Detect Human Stress Using EEG Signals

EEG (Electroencephalogram) signal is a neuro-signal which is generated due the different electrical activities in the brain. Different types of electrical activities correspond to different states of the brain. These signals can be captured and processed to get the useful information that can be used in early detection of some mental diseases. Raw EEG signals are captured by using Neurosky Mindwave EEG headset and sent to an android application via Bluetooth. The application generates a CSV file which is exported to MATLAB for further processing. FFT is used to convert the signal from time domain to frequency domain and Butterworth filter is used to extract various frequency bands like alpha, beta, delta and theta. For each of these frequency bands, Relative Energy Ratio (RER) in terms of Energy Spectral Density is calculated which indicates the dominant frequency band and the corresponding stress level.

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