TY - GEN
T1 - New approach in features extraction for EEG signal detection
AU - Guerrero-Mosquera, Carlos
AU - Vazquez, Angel Navia
PY - 2009
Y1 - 2009
N2 - This paper describes a new approach in features extraction using time-frequency distributions (TFDs) for detecting epileptic seizures to identify abnormalities in electroencephalogram (EEG). Particularly, the method extracts features using the Smoothed Pseudo Wigner-Ville distribution combined with the McAulay-Quatieri sinusoidal model and identifies abnormal neural discharges. We propose a new feature based on the length of the track that, combined with energy and frequency features, allows to isolate a continuous energy trace from another oscillations when an epileptic seizure is beginning. We evaluate our approach using data consisting of 16 different seizures from 6 epileptic patients. The results show that our extraction method is a suitable approach for automatic seizure detection, and opens the possibility of formulating new criteria to detect and analyze abnormal EEGs.
AB - This paper describes a new approach in features extraction using time-frequency distributions (TFDs) for detecting epileptic seizures to identify abnormalities in electroencephalogram (EEG). Particularly, the method extracts features using the Smoothed Pseudo Wigner-Ville distribution combined with the McAulay-Quatieri sinusoidal model and identifies abnormal neural discharges. We propose a new feature based on the length of the track that, combined with energy and frequency features, allows to isolate a continuous energy trace from another oscillations when an epileptic seizure is beginning. We evaluate our approach using data consisting of 16 different seizures from 6 epileptic patients. The results show that our extraction method is a suitable approach for automatic seizure detection, and opens the possibility of formulating new criteria to detect and analyze abnormal EEGs.
UR - http://www.scopus.com/inward/record.url?scp=77951012145&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2009.5332434
DO - 10.1109/IEMBS.2009.5332434
M3 - Conference contribution
C2 - 19963450
AN - SCOPUS:77951012145
SN - 9781424432967
T3 - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
SP - 13
EP - 16
BT - Proceedings of the 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society
PB - IEEE Computer Society
T2 - 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009
Y2 - 2 September 2009 through 6 September 2009
ER -