Detection and analysis of epileptic seizure based on wavelet transform and modulus maximum approach

Abstract

Epilepsy is a chronic disorder of brain dysfunction caused by sudden abnormal discharge of brain neurons. The detection of epileptic seizure can be achieved by the detection and analysis of spike waves. In this paper, a method of detection based on wavelet transform and modulus maximum is proposed. Firstly, it uses the continuous wavelet transform of epileptic EEG signals in a certain scale to divide the frequency bands. Secondly, it applys the modulus algorithm and refining algorithm to detect singular points of EEG signals, which are taken as the suspect points of spike waves. Finally, through screening based on power spectral density analysis and space surface fitting, the final characteristic spike waves are detected to determine whether the epileptic seizure occurres. The verification experimental results indicate the efficiency and reliability of the proposed method with a diagnostic accuracy as high as 92.5%. It provides a valuable reference method for epileptic seizure detection.

Keywords

• epileptic seizure
• EEG signal
• spike wave
• wavelet transform
• modulus maximum method