A Novel Constrained Topographic Independent Component Analysis for Separation of Epileptic Seizure Signals

Clicks: 298
ID: 56053
2007
Blind separation of the electroencephalogram signals (EEGs) using topographic independent component analysis (TICA) is an effective tool to group the geometrically nearby source signals. The TICA algorithm further improves the results if the desired signal sources have particular properties which can be exploited in the separation process as constraints. Here, the spatial-frequency information of the seizure signals is used to design a constrained TICA for the separation of epileptic seizure signal sources from the multichannel EEGs. The performance is compared with those from the TICA and other conventional ICA algorithms. The superiority of the new constrained TICA has been validated in terms of signal-to-interference ratio and correlation measurement.
Reference Key
jing2007acomputational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Jing, Min;Sanei, Saeid;
Journal Computational Intelligence and Neuroscience
Year 2007
DOI DOI not found
URL
http://dx.doi.org/10.1155/2007/21315
Keywords
Medicine Engineering (General). Civil engineering (General) Biotechnology Computer applications to medicine. Medical informatics Mechanical engineering and machinery Science neurosciences. biological psychiatry. neuropsychiatry telecommunication electronics mathematics

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.