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Analysis of epileptic EEG signals using higher order spectra
- Source :
- Journal of Medical Engineering and Technology
- Publication Year :
- 2009
- Publisher :
- Informa Healthcare, 2009.
-
Abstract
- The unpredictability of the occurrence of epileptic seizures contributes to the burden of the disease to a major degree. An automatic system that detects seizure onsets would allow patients or the people near them to take appropriate precautions, and could provide more insight into these phenomena, thereby revealing important clinical information. Thus, various methods have been proposed to predict the onset of seizures based on EEG recordings. A seemingly promising approach involves nonlinear features motivated by the higher order spectra (HOS). The goal in this paper is to find the different HOS features for normal, pre-ictal (background) and epileptic EEG signals. This may help in the detection of seizure onset as early as possible with maximal accuracy. In this work, 300 EEG data, each belonging to the three classes, are studied. Our results show that the HOS based measures show unique ranges for the different classes with high confidence level (p = 0.002).
- Subjects :
- Computer science
Speech recognition
Biomedical Engineering
Electroencephalography
EEG, Epilepsy, pre-ictal, entropy, bispectrum, bicoherence
Epilepsy
Seizure onset
Eeg data
Seizures
Clinical information
090399 Biomedical Engineering not elsewhere classified
090609 Signal Processing
medicine
Epileptic eeg
Humans
Diagnosis, Computer-Assisted
Bicoherence
080109 Pattern Recognition and Data Mining
Analysis of Variance
medicine.diagnostic_test
General Medicine
medicine.disease
090300 BIOMEDICAL ENGINEERING
Bispectrum
Algorithms
Subjects
Details
- ISSN :
- 23813652
- Database :
- OpenAIRE
- Journal :
- IndraStra Global
- Accession number :
- edsair.doi.dedup.....167dd6ef2637c8ed9599ae611496d9a2