Abstract
In the field of medical science, the EEG signal is a tool for measuring the brain activity which reflects the condition of the brain. The electrical activity in brain using small, flat metal discs (electrodes) attached to the scalp is detected by a test called EEG (Electro Encephalogram). The main aim of this thesis is to help the doctors by reducing the time complexity in analyzing EEG signal which produces better results. Brain cells communicate through electrical impulses are active all the time, even when asleep or awake. The brain signals can be analyzed by using five bands of frequency which are namely alpha, beta, gamma, delta, and theta. Each band has a respective frequency range, which determines mental states and condition of human activities. Different activities of the brain will generate different EEG signal. Transform domain techniques like Discrete Fourier Transform (DFT), Fast Fourier Transform (FFT), and Wavelet transforms are used to determine the frequency value of each frequency band. The exact mental state and conditions of the brain such as sleep, drowsiness, stress, and mental ability can be determined. A total of 12 EEG signals are taken from MIT-BIH EEG scalp database and the approach is implemented in MATLAB (R2014a) software.
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Ebraheem Khaleelulla, S., Rajesh Kumar, P. (2018). EEG Signal Analysis for Mental States and Conditions of Human Brain. In: Satapathy, S., Bhateja, V., Chowdary, P., Chakravarthy, V., Anguera, J. (eds) Proceedings of 2nd International Conference on Micro-Electronics, Electromagnetics and Telecommunications. Lecture Notes in Electrical Engineering, vol 434. Springer, Singapore. https://doi.org/10.1007/978-981-10-4280-5_15
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DOI: https://doi.org/10.1007/978-981-10-4280-5_15
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