Automatic detection of epileptic seizures using independent component analysis algorithm

IEEE-International Conference on Advances in Engineering, Science and Management, ICAESM-2012

Volumn , Issue , 2012, Pages 542-544

  Arunkumar, N ^a   Balaji, V S ^a   Ramesh, Subhashree ^a   Natarajan, Sharmila ^a   Likhita, Vellanki Ratna ^a   Sundari, Sivakama ^a  

^a SASTRA UNIVERSITY   (India)

Author keywords

EEG; epileptic seizure; Hurst exponent (H); Independent Component Analysis (ICA); Principle Component Analysis (PCA)

Indexed keywords

AUTOMATIC DETECTION; BRAIN CELLS; DETECTION RATES; ELECTRICAL SIGNAL; EPILEPTIC SEIZURES; EPILEPTIC SPIKES; HURST EXPONENTS; INDEPENDENT COMPONENTS; PRINCIPLE COMPONENT ANALYSIS;

ELECTROENCEPHALOGRAPHY; PRINCIPAL COMPONENT ANALYSIS;

INDEPENDENT COMPONENT ANALYSIS;

EID: 84863978040     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (5)

1. S. Popescu, Trained wavelets used to detect epileptic spikes: timefrequency and time-scale analysis. Proc IEEE-SF International Symposium 1998, 285-288.
2. Sergiy Vorobyov and Andrzej Cichocki., Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis. Biological Cybernetics, vol. 86, no. 4, Apr. 2002, 293-303.
3. Hyvarinan. A and Oja. E "Independent Component Analysis: A tutorial", 1999 http://www.cis.hut.fi/projects/ica/
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