Analysis and localization of epileptic events using wavelet packets

被引:17
作者
Gutiérrez, J
Alcántara, R
Medina, V
机构
[1] Univ Autonoma Metropolitana Iztapalapa, Dept Ingn Elect, Mexico City 09340, DF, Mexico
[2] Inst Natl Neurol & Neurocirug, Mexico City 14269, DF, Mexico
[3] Univ Nacl Autonoma Mexico, Fac Ingn, Div Estudios Posgrado, Mexico City 04510, DF, Mexico
关键词
epilepsy; epileptic foci; biomedical signal processing; time-scale; multiresolution decomposition; wavelet transform; time-frequency; wavelet packets;
D O I
10.1016/S1350-4533(01)00096-0
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This article compares results obtained in previous studies using time-frequency representations (Wigner-Ville, Choi-Williams and Parametric) and the wavelet transform with those obtained with wavelet packet functions to show new findings about their quality in the analysis of ECoG recordings in human intractable epilepsy: data from 21 patients have been analyzed and processed with four types of wavelet functions, including Orthogonal, Biorthogonal and Non-Orthogonal basis. These functions were compared in order to test their quality to represent spikes in the ECoG. The energy based on the wavelet coefficients to different scales was also calculated. The best results were found with the biorthogonal-6.8 wavelet on 5-7 scales, which gave 0.92 sensitivity, but with a high percentage of false positives; this representation was highly correlated with spike events on time and duration. To improve these results we have studied the wavelet packet coefficients energy. We found that reconstruction wavelet packet coefficients at 4 and 9 nodes contain significant information to characterize the spike event. These nodes' reconstruction coefficients were multiplied and this product was highly correlated with spikes events on time and duration. With this procedure we improved the sensitivity up to 0.96 with the same biorthogonal-6.8 wavelet at four levels. With this technique we do not sacrifice computation time: 896 samples are processed at only 0.16 s, so that it is possible to show the spike scattering path on line, because 896 samples (7 s)/16 channels are processed at 3.13 s. (C) 2002 IPEM. Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:623 / 631
页数:9
相关论文
共 20 条
[1]  
ALCANTARA R, 1998, C LAT ING BIOM, P159
[2]  
[Anonymous], 1974, Electroencephalogr Clin Neurophysiol, V37, P538
[3]  
BRUCE A, 1996, IEEE SPECTRUM OCT, P26
[4]  
Chui C.K., 1992, An introduction to wavelets, V1, DOI DOI 10.1109/99.388960
[5]  
CODY MA, 1992, DR DOBBS J APR, P16
[6]   Detection of epileptic events in electroencephalograms using wavelet analysis [J].
DAttellis, CE ;
Isaacson, SI ;
Sirne, RO .
ANNALS OF BIOMEDICAL ENGINEERING, 1997, 25 (02) :286-293
[7]  
Daubechies I., 1993, Ten Lectures of Wavelets, V28, P350
[8]   A MULTISTAGE SYSTEM TO DETECT EPILEPTIFORM ACTIVITY IN THE EEG [J].
DINGLE, AA ;
JONES, RD ;
CARROLL, GJ ;
FRIGHT, WR .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1993, 40 (12) :1260-1268
[9]   AUTOMATED INTERICTAL EEG SPIKE DETECTION USING ARTIFICIAL NEURAL NETWORKS [J].
GABOR, AJ ;
SEYAL, M .
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1992, 83 (05) :271-280
[10]  
GATH I, 1992, IEEE T BIOMEDICAL EN, V39, P45