The use of wavelet transform as a preprocessor for the neural network detection of EEG spikes

Author

Kalayci, Tulga ; Özdamar, Özcan ; Erdöl, Nurgün

Author_Institution

Dept. of Biomed. Eng., Miami Univ., FL, USA

fYear

1994

fDate

10-13 Apr 1994

Firstpage

1

Lastpage

3

Abstract

In this study, the wavelet transform is used to process EEG data as input to a feed forward neural network for the detection of epileptogenic transient waveforms. The compression capability of wavelet transform provided the inclusion of data before and after the spike for contextual information without increasing input size of the neural network. The network is trained for the detection of spikes and non-spikes. The results show that wavelet transform can be used to provide more relevant information for improving the detection of epileptogenic spikes for automated EEG monitoring of seizure patients

Keywords

electroencephalography; medical signal processing; wavelet transforms; EEG data processing; EEG spikes; automated EEG monitoring; contextual information; epileptogenic transient waveforms detection; neural network detection; nonspikes; seizure patients; wavelet transform preprocessor; Biological neural networks; Biomedical engineering; Computerized monitoring; Electroencephalography; Epilepsy; Feedforward neural networks; Neural networks; Patient monitoring; Scalp; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Southeastcon '94. Creative Technology Transfer - A Global Affair., Proceedings of the 1994 IEEE

Conference_Location

Miami, FL

Print_ISBN

0-7803-1797-1

Type

conf

DOI

10.1109/SECON.1994.324252

Filename

324252