Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks

• Published in: Journal of neuroscience methods Vol. 193; no. 1; pp. 156 - 163
• Main Authors: Guo, Ling, Rivero, Daniel, Pazos, Alejandro
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 30.10.2010
• Subjects: Approximate entropy (ApEn); Artificial neural network (ANN); Electroencephalogram (EEG); Electroencephalography - methods; Epileptic seizure detection; Humans; Multiwavelet transform (MWT); Nerve Net - physiopathology; Neural Networks (Computer); Seizures - diagnosis; Seizures - physiopathology; Signal Processing, Computer-Assisted; Approximate entropy (ApEn); Artificial neural network (ANN); Electroencephalogram (EEG); Epileptic seizure detection; Multiwavelet transform (MWT)

▶ Multiwavelet is superior to scalar wavelet for EEG signal analysis. ▶ Approximate entropy based on multiwavelet represents the characteristic of EEGs. ▶ Artificial neural network is used as a classifier for EEGs discrimination. Epilepsy is the most prevalent neurological disorder in humans after s...