title: A study on fuzzy C-means clustering-based systems in automatic spike detection.
abstract: In this study, different systems based on the fuzzy C-means (FCM) clustering algorithm are utilized for the detection of epileptic spikes in electroencephalogram (EEG) records. The systems are constructed as either single or two-stages. In contrast to single-stage systems, the two-stage system comprises a pre-classifier stage realized by a neural network. The FCM based two-stage system is also compared to a similar system implemented using the K-means clustering algorithm. The results imply that an FCM based two-stage system should be preferred as the spike detection system.
authors.affiliation: DVD VD Group-Digital R&D-Vestel Kom, Turkey. zeynep.inan@vestel.com.tr
authors.forename: Z Hilal
authors.initials: ZH
authors.lastname: Inan
authors.forename: Mehmet
authors.initials: M
authors.lastname: Kuntalp
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D004569:Electroencephalography / Q000706:statistics & numerical data*; D017143:Fuzzy Logic; D006801:Humans; D012680:Sensitivity and Specificity