Statistical Feature Based Comparison of EEG in Meditation for Various Wavelet

Abstract

The brain is most complicated framework which involves association of billions of nerve cells (neurons) which displays rich spatiotemporal flow. Among all techniques for inspecting human brain, an immediate measure of cortical movement with a resolution less than millisecond is only obtained with EEG. Brain and meditation have a connection for centuries. This study involves statistical analysis of EEG spectral power during meditation and non-meditation. This study also deals with regular meditators in two conditions first are during meditation and second is during normal condition. The EEG signal is recorded for 40 subjects in which 20 are regular meditators and 20 are non-meditators. This recorded data is preprocessed to remove the artifacts. After that wavelet transform is applied for different wavelet functions and then Fourier transform is performed to achieve power spectrum density. It was found that theta power increases during meditation and also haar wavelet provides better results than other wavelet functions. This study signifies that with meditation there is a considerable change in EEG of person is observed.