TY - GEN
T1 - Characterization of focal seizures in scalp electroencephalograms based on energy of signal and time-frequency analysis
AU - Cerquera, Alexander
AU - Guío, Laura V.
AU - Buitrago, Elías
AU - Gutiérrez, Rafael M.
AU - Medina, Carlos
PY - 2011
Y1 - 2011
N2 - This work presents a method for characterization of focal seizures from scalp digital electroencephalograms (EEG) obtained in the Central League Against Epilepsy in Bogotá, which were acquired from patients between 13 and 53 years old. This characterization was performed in segments of 500 ms with presence of focal seizures that had been initially identified and labeled by a specialist during their visual examination. After selection of the segments and channels for analysis, the energy of the signals were calculated with the idea that the energy of focal seizures could be larger than the one of their side waves in the segments. This procedure produced peaks of energy corresponding to the seizures and, some times, to noise and artifacts. In order to identify the peaks of energy of the seizures an analysis with continuous wavelet transform was performed. It was found that the mother wavelet 'bior2.2' allowed more easily the identification of such seizures from the seventh scale of the analysis. The method allowed the identification of the 65% of the seizures labeled by the specialist.
AB - This work presents a method for characterization of focal seizures from scalp digital electroencephalograms (EEG) obtained in the Central League Against Epilepsy in Bogotá, which were acquired from patients between 13 and 53 years old. This characterization was performed in segments of 500 ms with presence of focal seizures that had been initially identified and labeled by a specialist during their visual examination. After selection of the segments and channels for analysis, the energy of the signals were calculated with the idea that the energy of focal seizures could be larger than the one of their side waves in the segments. This procedure produced peaks of energy corresponding to the seizures and, some times, to noise and artifacts. In order to identify the peaks of energy of the seizures an analysis with continuous wavelet transform was performed. It was found that the mother wavelet 'bior2.2' allowed more easily the identification of such seizures from the seventh scale of the analysis. The method allowed the identification of the 65% of the seizures labeled by the specialist.
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U2 - 10.1007/978-3-642-21326-7_20
DO - 10.1007/978-3-642-21326-7_20
M3 - Conference contribution
AN - SCOPUS:79956332503
SN - 9783642213250
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 175
EP - 184
BT - New Challenges on Bioinspired Applications - 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011, Proceedings
T2 - 4th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011
Y2 - 30 May 2011 through 3 June 2011
ER -