Comparative study between Sample Entropy and Detrended Fluctuation Analysis performance on EEG records under data loss.
This study compares two signal entropy measures, Sample Entropy (SampEn) and Detrended Fluctuation Analysis (DFA) over real EEG signals after a randomized sample removal. Both measures have demonstrated their ability to discern between, among others: control and pathologic EEG signals, seizure free or not, control and opened eyes EEG, and side of brain signals. Results show that SampEn behaves better when analyzing control signals, while DFA provides better segmentation results between epileptic signals, in the context of sample loss, particularly when discerning between seizure and seizure free signal intervals.
Computer Science Department (DISCA) at Polytechnic University of Valencia, Alcoy Campus (EPSA-UPV), 03801 Alcoy, Alicante, Spain. ecirugeda@giica.com
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Cirugeda-Roldán
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Molina-Picó
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Cuesta-Frau
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Oltra-Crespo
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Miró-Martínez
D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000502:physiology*; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D019277:Entropy; D015203:Reproducibility of Results; D018401:Sample Size; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted