scrollbar

Recurrence Plots and Cross Recurrence Plots

RPs at a Glance Variations of RPs Quantification Introduction CRPs/JRPs Dynamical Invariants Pitfalls Further Reading Bibliography Software Related Methods RP Of The Day Symposium Forum Email List Imprint Privacy Disclaimer Accessibility

Hosted by:



Proceedings of the 22nd Signal Processing and Communications Applications Conference (SIU2014), 1387–1390p. (2014) DOI:10.1109/SIU.2014.6830497

Detection of epileptic seizure from EEG signals by using recurrence quantification analysis

F. Kutlu, C. Kose

The pre-diagnosis of diseases with computerized systems is widely used in recent years for reducing diagnosis time and ratio of misdiagnosis. In this study, a pre-diagnosis system has been proposed which separates of healthy and epileptic seizures periods. For the experiments, EEG signals acquired from healthy and epileptic individuals were used. In feature extraction stage, recurrence quantification analysis (RQA); in classification stage, support vector machines (SVM), multilayer perceptron neural networks (MLPNN) and Naive Bayes classifiers have been utilized. Accordingly, in case of using MLPNN, 96.67% classification performance was obtained.