EEG single-channel seizure recognition using Empirical Mode Decomposition and Normalized Mutual Information

摘要：

In this document features taken from Empirical Mode Decomposition (EMD) are selected by mutual information for the discrimination between Ictal and Seizure-Free EEG singlechannel signals. Some features are based on the instantaneous or average frequency and amplitude of each EMD component. Also, skewness, kurtosis and Shannons entropy are taken as features from the energy obtained using the Teager Energy Operator (TEO). TEO is calculated over each EMD component. Then a subset of relevant and non-redundant features is selected by normalized mutual information. Finally these selected features are used to train a linear Bayes classifier, and a 5-fold cross validation is performed for different clinical cases. We used a publicly available database to compare each feature extraction approach. Accuracies around 98％ are reached by the implemented methodology.

作者: Cristian Guarnizo Edilson Delgado

作者单位: Research CenterInstituto Tecnologico Metropolitano Research Center Instituto Tecnologico Metropolitano

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 1749-1752

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）