Tsallis Entropy Based Seizure Detection

MISS. KADAMBARI G. NARAYANKAR
2017 Zenodo  
This paper presents EEG signal analysis using Tsallis entropy and then it will make available for comparison with any another method along with KNN class ification. Electroencephalogram (EEG) remains the most immediate,easy and rich source of information for accepting phenomena related to brain electrical activities [1] . Important information,about the state of patient under observation,must be extracted from calculated DSD (Decimated signal diagonalization) bispectrum [2] . For this aim,it is
more » ... For this aim,it is useful to delineate an assessment index about the dynamic process associated with the analysed signal. This information is measure by means of entropy,since the degree of order or disorder of the recorded EEG signal will be replicate d in the obtained DSD bispectrum [3] . Tsallis entropy is better than Shannon one because it maximizes the probabilities of the events of the interest through the selection of the entropic index,and so it permits to detect in more perfect way,spikes r elated to epileptic seizure. https://www.ijiert.org/paper-details?paper_id=141090
doi:10.5281/zenodo.1459079 fatcat:nzfw3bywzve2pannzsnv2ggbq4