Wavelet based analysis of multi-electrode EEG-signals in epilepsy

Daniel A. Hein; Ronald Tetzlaff

doi:10.1117/12.608649

29 June 2005 Wavelet based analysis of multi-electrode EEG-signals in epilepsy

Daniel A. Hein, Ronald Tetzlaff

Proceedings Volume 5839, Bioengineered and Bioinspired Systems II; (2005) https://doi.org/10.1117/12.608649
Event: Microtechnologies for the New Millennium 2005, 2005, Sevilla, Spain

Abstract

For many epilepsy patients seizures cannot sufficiently be controlled by an antiepileptic pharmacatherapy. Furthermore, only in small number of cases a surgical treatment may be possible. The aim of this work is to contribute to the realization of an implantable seizure warning device. By using recordings of electroenzephalographical(EEG) signals obtained from the department of epileptology of the University of Bonn we studied a recently proposed algorithm for the detection of parameter changes in nonlinear systems. Firstly, after calculating the crosscorrelation function between the signals of two electrodes near the epileptic focus, a wavelet-analysis follows using a sliding window with the so called Mexican-Hat wavelet. Then the Shannon-Entropy of the wavelet-transformed data has been determined providing the information content on a time scale in subject to the dilation of the wavelet-transformation. It shows distinct changes at the seizure onset for all dilations and for all patients.

Citation Download Citation

Daniel A. Hein and Ronald Tetzlaff "Wavelet based analysis of multi-electrode EEG-signals in epilepsy", Proc. SPIE 5839, Bioengineered and Bioinspired Systems II, (29 June 2005); https://doi.org/10.1117/12.608649

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