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المؤلفFani, Mohammad
المؤلفAzemi, Ghasem
المؤلفBoashash, Boualem
تاريخ الإتاحة2014-04-27T19:18:41Z
تاريخ النشر2011
اسم المنشور2011 7th International Workshop on Signal Processing and their Applications (WOSSPA)
الاقتباسM. Fani, G. Azemi, and B. Boashash, "EEG-based automatic epilepsy diagnosis using the instantaneous frequency with sub-band energies," in Proc. of Systems, Signal Processing and their Applications (WOSSPA), 2011 7th International Workshop on, 2011, pp. 187-190
معرّف المصادر الموحدhttp://hdl.handle.net/10576/10995
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/WOSSPA.2011.5931447
الملخصThis paper presents a novel approach for classifying the electroencephalogram (EEG) signals as normal or abnormal. This method uses features derived from the instantaneous frequency (IF) and energies of EEG signals in different spectral sub-bands. Results of applying the method to a database of real signals reveal that, for the given classification task, the selected features consistently exhibit a high degree of discrimination between the EEG signals collected from healthy and epileptic patients. The analysis of the effect of window length used during feature extraction indicates that features extracted from EEG segments as short as 5 seconds achieve a high average total accuracy of 95.3%.
اللغةen
الناشرIEEE
الموضوعelectroencephalography
feature extraction
medical signal processing
patient diagnosis
signal classification
العنوانEEG-based automatic epilepsy diagnosis using the instantaneous frequency with sub-band energies
النوعConference Paper
الصفحات187-190
dc.accessType Abstract Only


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