Abstract
Brain is the most vital organ that necessitates transmission of electrical signals(information) all over the body. Electrical signals generated from neurons is recorded by means of method known as Electroencephlography(EEG). These signal recordings usually takes around 2–8 hours of continuous monitoring and can extends. over a week. So it places a huge problem on transmission and storage of EEG data. EEG signal compression has gaining more importance in biomedical field, because of limited storage capacity. The main objective of this work is to compare the performance of different Fractional compression tools on compression of an EEG signal. This paper exploits tools such as Compression ratio, Mean square Error, Peak Signal to Noise Ratio on Fractional Fourier Transform and Fractional Wavelet transform for efficient compression of EEG signal. Fractional wavelet based time-fractional-frequency transform delivers a better compression, with compression ratio in the range of 27.23 with minimal mean square error for all EEG signals.
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