A New Framework Based on Recurrence Quantification Analysis for Epileptic Seizure Detection

This study presents applying recurrence quantification analysis (RQA) on EEG recordings and their subbands: delta, theta, alpha, beta, and gamma for epileptic seizure detection. RQA is adopted since it does not require assumptions about stationarity, length of signal, and noise. The decomposition of...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics 2013-05, Vol.17 (3), p.572-578
Hauptverfasser:	Niknazar, M., Mousavi, S. R., Vosoughi Vahdat, B., Sayyah, M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Case-Control Studies Databases, Factual Dynamical systems EEG subbands Electroencephalography Electroencephalography - methods Epilepsy Epilepsy - diagnosis Epilepsy - physiopathology Epileptic seizure detection Feature extraction Humans phase space reconstruction recurrence quantification analysis (RQA) Studies System identification Temporal lobe Wavelet Analysis wavelet decomposition
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