Feature Extraction of Linear Predictors at Spectral Bands of Interest

被引：0

作者：

Leondopulos, Stathis S. ^{[1
]}

Chaovalitwongse, Wanpracha A. ^{[1
]}

Micheli-Tzanakou, Evangelia ^{[1
]}

Wong, Stephen

Wu, Brenda Y. ^{[2
]}

机构：

[1] Rutgers State Univ, Piscataway, NJ 08854 USA

[2] Univ Med & Dent New Jersey, Robert Wood Johnson Med Sch, New Brunswick, NJ 08901 USA

来源：

2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20 | 2009年

关键词：

EPILEPTIC SEIZURES;

D O I：

10.1109/IEMBS.2009.5335397

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Intra-cranial electroencephalograms (EEG) from two patients diagnosed with epilepsy are sampled at 1kHz, enabling analysis and feature extraction at frequency bands above the gamma range. This study focuses on the extraction of linear features (including autoregressive, autoregressive-moving average and Fourier coefficients) obtained at both low (below 100Hz) and high (100-500Hz) bands of the signal spectrum. Comparisons of the performance of each feature are made based on a binary hypothesis test of statistical distributions from inter-ictal and pre-ictal epochs. Results are obtained from pre-ictal time periods as assessed by an expert epileptologist.

引用

页码：2612 / 2616

页数：5

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