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

Elif Derya Ubeyli; Dean Cvetkovic; Irena Cosic

doi:10.1109/IEMBS.2007.4353036

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

Annu Int Conf IEEE Eng Med Biol Soc. 2007:2007:3304-7. doi: 10.1109/IEMBS.2007.4353036.

Authors

Elif Derya Ubeyli¹, Dean Cvetkovic, Irena Cosic

Affiliation

¹ TOBB Economics and Technology University, Faculty of Engineering, Department of Electrical and Electronics Engineering, Ankara, Turkey. edubeyli@etu.edu.tr

PMID: 18002702
DOI: 10.1109/IEMBS.2007.4353036

Abstract

This paper presents eigenvector methods for analysis of the photoplethysmogram (PPG), 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.

Publication types

Evaluation Study

MeSH terms

Algorithms*
Diagnosis, Computer-Assisted / methods*
Electrocardiography / methods*
Electroencephalography / methods*
Humans
Pattern Recognition, Automated / methods*
Photoplethysmography / methods*
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted*