Eigenvector methods for analysis of Human PPG, ECG and EEG signals

This paper presents eigenvector methods for analysis of the photoplethysmogram (PPG), eigenvector methods for analysis of human PPG, ECG and EEG signals Electrocardiogram (ECG), electroencephalogram (EEG) signals recorded in order to examine the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) upon the human electrophysiological signal behavior. The features representing the PPG, ECG, EEG signals were obtained by using the eigenvector methods. In addition to this, the problem of selecting relevant features among the features available for the purpose of discrimination of the signals was dealt with. Some conclusions were drawn concerning the efficiency of the eigenvector methods as a feature extraction method used for representing the signals under study.