Wavelet basis functions in biomedical signal processing

Keywords: Biomedical signal processing Prosthetics Myoelectric control Psychophysiology Mother wavelet EMG EEG VPA Pattern recognition Daubechies (db 44) a b s t r a c t During the last two decades, wavelet transform has become a common signal processing technique in various areas. Selection of the most similar mother wavelet function has been a challenge for the application of wavelet transform in signal processing. This paper introduces Daubechies 44 (db44) as the most similar mother wavelet function across a variety of biological signals. Three-hundred and twenty four potential mother wavelet functions were selected and investigated in the search for the most similar function. The algorithms were validated by three categories of biological signals: forearm electromyo-graphic (EMG), electroencephalographic (EEG), and vaginal pulse amplitude (VPA). Surface and intramus-cular EMG signals were collected from multiple locations on the upper forearm of subjects during ten hand motions. EEG was recorded from three monopolar Ag–AgCl electrodes (Pz, POz, and Oz) during visual stimulus presentation. VPA, a useful source for female sexuality research, were recorded during a study of alcohol and stimuli on sexual behaviors. In this research, after extensive studies on mother wavelet functions, results show that db44 has the most similarity across these classes of biosignals. Biosignal processing has been rapidly developing, increasing the understanding of complex biological processes in a wide variety of areas. Wavelet transform (Daubechies, 1991) is a powerful time-frequency approach which has been applied to multiple domains of biosignal processing, such as EMG (e. has permitted rapid development in the field. However, the selection of the most appropriate mother wave-let to characterize commonalities amongst signals within a given domain is still lacking in biosignal processing. The main contributions to find the optimum basis function can be found in several papers (e. The mother wavelet function is the main base of wavelet transforms that would permit identification of correlated coefficients across multiple signals. The more similar the mother wavelet function is to the wavelet coefficients across signals, the more precisely the signal of interest can be identified and isolated; hence, identification of a mother wavelet function is of paramount significance. The Daubechies (db) wavelet functions (Daubechies, 1988) have been applied in several areas with the lower orders (db1 to db20) used most often (Rafiee & Tse, 2009). The few peer-reviewed papers about the application of higher order db refer to Antonino-Daviu, Riera-Guasp, Folch, and Palomares (2006) and Rafiee and Tse (2009) …