• DocumentCode
    1572779
  • Title

    Spatio-Temporal Clustering of Epileptic ECOG

  • Author

    Hegde, Anant ; Erdogmus, Deniz ; Principe, Jose C.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL
  • fYear
    2006
  • Firstpage
    4199
  • Lastpage
    4202
  • Abstract
    The spatio-temporal mechanisms underlying the generation of epileptic seizures is not yet clearly understood. In this study, we attempt to quantify the spatio-temporal interactions of an epileptic brain by using a previously proposed SOM-based similarity index (SI) measure. We further show that spectral clustering approach can be appropriately used to determine the average spatial mappings in the brain at different stages of a seizure, by interpreting the SOM-SI values as affinity matrices. Results involving two pairs of seizures of an epileptic patient suggest that there may not be a regular pattern associated with channels´s spatio-temporal dynamics during the inter-ictal to pre-post ictal transition
  • Keywords
    bioelectric potentials; brain; diseases; medical signal processing; spatiotemporal phenomena; SOM-based similarity index; affinity matrices; average spatial mappings; brain; epileptic ECOG; epileptic seizures; spatiotemporal clustering; spatiotemporal dynamics; spectral clustering; Biomedical engineering; Clustering methods; Data analysis; Data mining; Delay effects; Epilepsy; Euclidean distance; Kernel; Signal generators; Time measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-8741-4
  • Type

    conf

  • DOI
    10.1109/IEMBS.2005.1615390
  • Filename
    1615390