TY - GEN
T1 - VLSI implementation for epileptic seizure prediction system based on wavelet and chaos theory
AU - Hung, Shao Hang
AU - Chao, Chih Feng
AU - Wang, Shu Kai
AU - Lin, Bor-Shyh
AU - Lin, Chin-Teng
PY - 2010/12/1
Y1 - 2010/12/1
N2 - This paper presents a very large scale integration (VLSI) circuit implementation for Epileptic Seizure Prediction System based combination of wavelet and chaos theory. The system consists with operation units of discrete wavelet transform (DWT), correlation dimension (CD), and correlation coefficient. This work discovered by certain bandwidth of signal extraction with DWT, and the combination with Chaotic features analysis, it can achieve a higher accuracy of epileptic prediction. Furthermore, the correlation coefficient between two correlation dimensions with different embedding dimensions was proposed as a novel feature for epileptic seizure prediction in this study. The proposed system was evaluated with intracranial Electrocorticography (ECoG) recordings from a set of eleven patients with refractory temporal lobe epilepsy (TLE). The accuracy of experiment result for all subjects can achieve 87%, and a false prediction rate is 0.24/h. In average warning time occur about 27 min ahead the ictal.
AB - This paper presents a very large scale integration (VLSI) circuit implementation for Epileptic Seizure Prediction System based combination of wavelet and chaos theory. The system consists with operation units of discrete wavelet transform (DWT), correlation dimension (CD), and correlation coefficient. This work discovered by certain bandwidth of signal extraction with DWT, and the combination with Chaotic features analysis, it can achieve a higher accuracy of epileptic prediction. Furthermore, the correlation coefficient between two correlation dimensions with different embedding dimensions was proposed as a novel feature for epileptic seizure prediction in this study. The proposed system was evaluated with intracranial Electrocorticography (ECoG) recordings from a set of eleven patients with refractory temporal lobe epilepsy (TLE). The accuracy of experiment result for all subjects can achieve 87%, and a false prediction rate is 0.24/h. In average warning time occur about 27 min ahead the ictal.
KW - Correlation Dimension
KW - Discrete Wavelet Transform
KW - ECoG
KW - Seizure Prediction
UR - http://www.scopus.com/inward/record.url?scp=79951596284&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2010.5686655
DO - 10.1109/TENCON.2010.5686655
M3 - Conference contribution
AN - SCOPUS:79951596284
SN - 9781424468904
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
SP - 364
EP - 368
BT - TENCON 2010 - 2010 IEEE Region 10 Conference
T2 - 2010 IEEE Region 10 Conference, TENCON 2010
Y2 - 21 November 2010 through 24 November 2010
ER -