Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10322399 | Expert Systems with Applications | 2012 | 7 Pages |
Abstract
⺠We present a novel automatic technique for epileptic EEG classification into the normal, interictal, and ictal activities. ⺠We use eigenvalues extracted from wavelet coefficients as features. ⺠Several supervised learning based classifiers were trained using selected features. ⺠We demonstrate that our proposed technique can yield 99% classification accuracy.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
U. Rajendra Acharya, S. Vinitha Sree, Ang Peng Chuan Alvin, Jasjit S. Suri,