title: Joining the benefits: combining epileptic seizure prediction methods.
abstract: OBJECTIVE
  In recent years, a variety of methods developed in the field of linear and nonlinear time series analysis have been used to obtain reliable predictions of epileptic seizures. Because individual methods for seizure prediction so far have shown statistical significance but insufficient performance for clinical applications, we investigated possible improvements by combining algorithms capturing different aspects of electroencephalogram (EEG) dynamics.
  
  
  METHODS
  We applied the mean phase coherence and the dynamic similarity index to long-term continuous intracranial EEG data. The predictive performance of both methods was assessed and statistically evaluated separately, as well as by using logical "AND" and "OR" combinations.
  
  
  RESULTS
  Used independently, either method resulted in a statistically significant prediction performance in only a few patients. Particularly the "AND" combination led to improved prediction performances, leading to an increase in sensitivity and/or specificity. For a maximum false prediction rate of 0.15/h, the mean sensitivity improved from about 25% for the individual methods to 43.2% for the "AND" and to 35.2% for the "OR" combination.
  
  
  CONCLUSIONS
  This study shows that combinations of prediction methods are promising new approaches to enhance seizure prediction performance considerably. It allows merging the individual benefits of prediction methods in a complementary manner. Because either sensitivity or specificity of seizure prediction methods can be improved depending on the needs of the desired clinical application, the combination opens a new window for future use in a clinical setting.
authors.affiliation: Bernstein Center for Computational Neuroscience Freiburg, University of Freiburg, Freiburg, Germany. feldwisch@bccn.uni-freiburg.de
authors.forename: Hinnerk
authors.initials: H
authors.lastname: Feldwisch-Drentrup
authors.forename: Björn
authors.initials: B
authors.lastname: Schelter
authors.forename: Michael
authors.initials: M
authors.lastname: Jachan
authors.forename: Jakob
authors.initials: J
authors.lastname: Nawrath
authors.forename: Jens
authors.initials: J
authors.lastname: Timmer
authors.forename: Andreas
authors.initials: A
authors.lastname: Schulze-Bonhage
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D004569:Electroencephalography / Q000379:methods; D004827:Epilepsy / Q000175:diagnosis*; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D017711:Nonlinear Dynamics; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted