Title :
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
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;
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
DOI :
10.1109/SECON.1994.324252
