Epileptic seizure detection based on the instantaneous area of analytic intrinsic mode functions of EEG signals

作者: Varun Bajaj , Ram Bilas Pachori

DOI: 10.1007/S13534-013-0084-0

关键词: ElectroencephalographyTemporal lobePattern recognitionComputer scienceEEG-fMRIEpileptic seizureHilbert–Huang transformAnalytic signalEpilepsyArtificial intelligenceAnesthesiaWord error rateBiomedical engineering

摘要: Epileptic seizure is generated by abnormal synchronization of neurons the cerebral cortex patients, which commonly detected electroencephalograph (EEG) signals. In this paper, intracranial EEG signals have been used to detect focal temporal lobe epilepsy. This paper presents a new method based on empirical mode decomposition (EMD) for detection epileptic seizures. The proposed uses Hilbert transformation intrinsic functions (IMFs), obtained EMD process that provides analytic signal representation IMFs. instantaneous area measured from trace windowed IMFs rules-based experiment results are included show effectiveness performance evaluation has performed computing sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative (NPV) and error rate (ERD). compared existing methods detecting epilepsy provided with increased accuracy.

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