A multi-level wavelet approach for automatic detection of epileptic spikes in the electroencephalogram

被引：127

作者：

Indiradevi, K. P. ^{[1
]}

Elias, Elizabeth ^{[1
]}

Sathidevi, P. S. ^{[1
]}

Nayak, S. Dinesh ^{[2
]}

Radhakrishnan, K. ^{[2
]}

机构：

[1] Natl Inst Technol, Dept Elect & Commun Engn, Calicut 673601, Kerala, India

[2] Sree Chitra Tirunal Inst Med Sci & Technol, R Madhavan Nayar Ctr Comprehens Epilepsy Care, Trivandrum, Kerala, India

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2008年 / 38卷 / 07期

关键词：

automatic detection; electroencephalogram (EEG); epilepsy; epileptic spike; interictal epileptiforru discharges (IEDs); wavelet analysis;

D O I：

10.1016/j.compbiomed.2008.04.010

中图分类号：

Q [生物科学];

学科分类号：

07 [理学]; 0710 [生物学]; 09 [农学];

摘要：

We describe a strategy to automatically identify epileptiform activity in 18-channel human electroencephalogram (EEG) based on a multi-resolution, multi-level analysis. The signal on each channel is decomposed into six sub-bands using discrete wavelet transform. Adaptive threshold is applied on sub-bands 4 and 5. The spike portion of EEG signal is then extracted from the raw data and energy of the signal for locating the exact location of epileptic foci is determined. The key points of this process are identification of a suitable wavelet for decomposition of EEG signals, recognition of a proper resolution level, and computation of an appropriate dynamic threshold. (c) 2008 Elsevier Ltd. All rights reserved.

引用

页码：805 / 816

页数：12

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