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   Real‑time Detection of Precursors to Epileptic Seizures: Non‑Linear Analysis of System Dynamics  
   
نویسنده Nesaei Sahar ,Sharafat Ahmad R
منبع journal of medical signals and sensors - 2014 - دوره : 4 - شماره : 2 - صفحه:103 -112
چکیده    We propose a novel approach for detecting precursors to epileptic seizures in intracranial electroencephalograms (ieeg), which isbased on the analysis of system dynamics. in the proposed scheme, the largest lyapunov exponent of the discrete wavelet packettransform (dwpt) of the segmented eeg signals is considered as the discriminating features. such features are processed by asupport vector machine (svm) classifier to identify whether the corresponding segment of the eeg signal contains a precursor to anepileptic seizure. when consecutive eeg segments contain such precursors, a decision is made that a precursor is in fact detected.the proposed scheme is applied to the freiburg dataset, and the results show that seizure precursors are detected in a time frame that unlike other existing schemes is very much convenient to patients, with sensitivity of 100% and negligible false positive detection rates.
کلیدواژه Epileptic seizure precursor ,feature extraction ,intracranial electroencephalograms ,largest Lyapunov exponent ,nonlinear dynamics ,support vector machine classifier
آدرس tarbiat modares university, ایران, tarbiat modares university, ایران
 
     
   
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