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Comparison of wavelet transform symlets (2-10) and daubechies (2-10) for an electroencephalographic signal analysis

Abstract:

The use of digital filters as the Wavelet Transform is widely recognized in signal processing; however, for the analysis of an electroencephalographic (EEG) signal, the most optimal filter to be used has not been definitively determined. This work presents a comparison between the results obtained by filtering an EEG signal recorded during an 8 minute foreign language class on 69 asymptomatic volunteers using Wavelet Symlets (sym2 - sym10) and Daubechies (db2 - db10). The EEG signals were divided into four sub-bands and an energy, frequency and time analysis was performed. The results obtained show that the filters respond in a different but not significant way. For the identification of the appropriate mother Wavelet for each scope of analysis, its similarity was considered with the average value of Symlets (sym2 - sym10) and this process was replicated for db Wavelets. Considering the energy of the EEG signals, the db4 filter had a higher presence in 5 electrodes in the Alpha and Delta frequency bands. In the frequency domain, the db5 family has a presence in 12 electrodes in the Beta, Alpha and Delta frequency bands. Regarding time, the sym9 filter has a higher presence in 4 electrodes in the Beta, Theta and Delta frequency bands. The purpose of this work is to provide more information for the proper choice of a mother Wavelet in the EEG signal analysis in asymptomatic volunteers.