A study on fuzzy C-means clustering-based systems in automatic spike detection

Inan Z. H., KUNTALP M.

COMPUTERS IN BIOLOGY AND MEDICINE, vol.37, no.8, pp.1160-1166, 2007 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 37 Issue: 8
  • Publication Date: 2007
  • Doi Number: 10.1016/j.compbiomed.2006.10.010
  • Journal Name: COMPUTERS IN BIOLOGY AND MEDICINE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1160-1166
  • Keywords: EEG, fuzzy C-means, clustering, spike detection, epilepsy, ARTIFICIAL NEURAL-NETWORK, EPILEPTIFORM DISCHARGES, EEG
  • Dokuz Eylül University Affiliated: Yes

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. (c) 2006 Elsevier Ltd. All rights reserved.