Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/7790
Title: Wavelet transform feature extraction from human PPG, ECG, and EEG signal responses to ELF PEMF exposures: A pilot study
Authors: Cvetkovic, Dean
Übeyli, Elif Derya
Cosic, Irena
Keywords: feature extraction
PPG
ECG
EMG
discrete wavelet transform
PEMF
ELF
bioeffects
Issue Date: 2008
Publisher: Academic Press Inc Elsevier Science
Abstract: This paper presents the expefimental pilot study to investigate the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) in response to photoplethysmographic (PPG), electrocardiographic (ECG), electroencephalographic (EEG) activity. The assessment of wavelet transform (WT) as a feature extraction method was used in representing the electrophysiological signals. Considering that classification is often more accurate when the pattern is simplified through representation by important features, the feature extraction and selection play an important role in classifying systems such as neural networks. The PPG, ECG, EEG signals were decomposed into time-frequency representations using discrete wavelet transform (DWT) and the statistical features were calculated to depict their distribution. Our pilot study investigation for any possible electrophysiological activity alterations due to ELF PEMF exposure, was evaluated by the efficiency of DWT as a feature extraction method in representing the signals. As a result, this feature extraction has been justified as a feasible method. (c) 2007 Elsevier Inc. All rights reserved.
URI: https://doi.org/10.1016/j.dsp.2007.05.009
https://hdl.handle.net/20.500.11851/7790
ISSN: 1051-2004
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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