Neuropathology Classifier Based on Higher Order Spectra

• 作者: Antonino Caralli Cesar Seijas Sergio Villazana
• 来源期刊: 电脑和通信(英文)
• 学科: 医学
• 关键词: HIGHER Order SPECTRA Classification Support Vector Machines EEG EPILEPSY
• 年，卷（期）: 2013,（4）
• 页码范围: 28-32
• 页数: 5页
• 分类号: R73

摘要

Epilepsy is the most common neuropathology. Statistical studies related to the disease reported that 20% - 25% of epileptic patients with occurrence of seizures were even under treatment with drugs. This article presents a strategy for improved detection of the neuropathology, based on electroencephalogram (EEG), using a classifier built with support vector machines (SVC). The SVC is designed based on feature extraction of higher order spectra of time series derived from the EEG applied to epileptic patients and control patients. As demonstrated in the study presented, the EEG time series are highly nonlinear and non-Gaussian, therefore, exhibit higher order spectra, which are extracted features that improve the accuracy in the performance of SVC. The results of this study suggest the development of highly accurate computational tools for the diagnosis of this dreaded neuropathology.