Combining Energy and Wavelet Transform for Epileptic Seizure Prediction in an Advanced Computational System

Seizure prediction in epileptic patients will allow a deep improvement in their quality of life. In the paper a new method using energy relative measures in wavelet coefficients is proposed and tested in several patients. The results show the potential of the technique, but also its limitations, stressing the needs for further work in a larger number of patients, using multimodal information and an advanced database with a large features set to be used in seizure prediction An advanced computational framework is under development, using multisensorial information to build a large set of features to be used in a classification system supporting seizure prediction. This system is composed of two main parts the algorithms base and the database, briefly described.