Wavelet basis functions in biomedical signal processing
► Daubechies 44 wavelet basis is the most similar function across various biosignals. ► High order Daubechies functions are useful to extract features from 1-D biosignals. ► For wavelet signal processing, selection of mother function similar to signal is not always a proper strategy. During the last...
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Published in | Expert systems with applications Vol. 38; no. 5; pp. 6190 - 6201 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.05.2011
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Subjects | |
Online Access | Get full text |
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Summary: | ► Daubechies 44 wavelet basis is the most similar function across various biosignals. ► High order Daubechies functions are useful to extract features from 1-D biosignals. ► For wavelet signal processing, selection of mother function similar to signal is not always a proper strategy.
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 electromyographic (EMG), electroencephalographic (EEG), and vaginal pulse amplitude (VPA). Surface and intramuscular 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. |
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ISSN: | 0957-4174 1873-6793 |
DOI: | 10.1016/j.eswa.2010.11.050 |