Journal of Medical Systems

, Volume 32, Issue 3, pp 201–206 | Cite as

AR Spectral Analysis Technique for Human PPG, ECG and EEG Signals

Original Paper


In this study, Fast Fourier transform (FFT) and autoregressive (AR) methods were selected for processing 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 parameters in the autoregressive (AR) method were found by using the least squares method. The power spectra of the PPG, ECG, and EEG signals were obtained by using these spectral analysis techniques. These power spectra were then used to compare the applied methods in terms of their frequency resolution and the effects in extraction of the features representing the PPG, ECG, and EEG signals. Some conclusions were drawn concerning the efficiency of the FFT and least squares AR methods as feature extraction methods used for representing the signals under study.


PPG ECG EEG Least squares AR method 


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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Elif Derya Übeyli
    • 1
  • Dean Cvetkovic
    • 2
  • Irena Cosic
    • 2
  1. 1.Faculty of Engineering, Department of Electrical and Electronics EngineeringTOBB Economics and Technology UniversityAnkaraTurkey
  2. 2.School of Electrical and Computer EngineeringRMIT UniversityMelbourneAustralia

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