Topological classifier for detecting the emergence of epileptic seizures
  In this work we study how to apply topological data analysis to create a method suitable to classify EEGs of patients affected by epilepsy. The topological space constructed from the collection of EEGs signals is analyzed by Persistent Entropy acting as a global topological feature for discriminating between healthy and epileptic signals. The Physionet data-set has been used for testing the classifier. 
Marco Piangerelli, Matteo Rucco and Emanuela Merelli
q-bio.NC cs.IT math.IT