title: Spike detection algorithm automatically adapted to individual patients applied to spike-and-wave percentage quantification.
abstract: OBJECTIVE
  To report an innovative spike detection algorithm that tailors its detection to the patient. Interictal epileptiform activity quantification was accomplished in the setting of epileptic syndromes with continuous spike and waves during slow sleep, which is a time-consuming task for the EEG analysis.
  
  
  METHODS
  The algorithm works in three steps. Firstly, a first spike detection is made with generic parameters. Secondly, the detected spikes are used to tailor the detection algorithm to the patient; and thirdly, the resulting patient-specific detection algorithm is used to analyze individual patient with high-quality detection. Therefore, the algorithm produces a patient-specific template -hence exhibiting improved performance metrics, without the need of a priori knowledge from the experts.
  
  
  RESULTS
  The system was first evaluated for EEG of three patients, against the scoring of three EEG experts, demonstrating similar performance. Later, it was evaluated against the spike and wave percentage evaluation of another expert for 17 additional records. The difference between the two evaluations was 4.4% on average, which is almost the same as the interexpert difference (4.7%).
  
  
  CONCLUSIONS
  We designed a fully automated and efficient spike detection algorithm, which is liable to trim down the specialist's diagnostic time.
authors.affiliation: Bio, Electro and Mechanical Systems (BEAMS), CP165/56, université Libre de Bruxelles, 50, avenue F.-Roosevelt, 1050 Bruxelles, Belgium. anoncler@ulb.ac.be
authors.forename: A
authors.initials: A
authors.lastname: Nonclercq
authors.forename: M
authors.initials: M
authors.lastname: Foulon
authors.forename: D
authors.initials: D
authors.lastname: Verheulpen
authors.forename: C
authors.initials: C
authors.lastname: De Cock
authors.forename: M
authors.initials: M
authors.lastname: Buzatu
authors.forename: P
authors.initials: P
authors.lastname: Mathys
authors.forename: P
authors.initials: P
authors.lastname: Van Bogaert
mesh_terms: D000293:Adolescent; D000465:Algorithms; D002648:Child; D004569:Electroencephalography; D004827:Epilepsy / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008297:Male; D008991:Monitoring, Physiologic / Q000379:methods*; D015588:Observer Variation; D017286:Polysomnography / Q000379:methods*; D015203:Reproducibility of Results; D020919:Sleep Disorders, Intrinsic / Q000503:physiopathology*