DocumentCode :
1601830
Title :
Neural Codes in Human Extracranial EEG: Identification of Epilepsy Features
Author :
Valiante, Taufik ; Chiu, Alan W L ; Bardakjian, Berj L.
Author_Institution :
Dept. of Surg., Toronto Univ., Ont.
fYear :
2006
Firstpage :
432
Lastpage :
435
Abstract :
Features of epilepsy from human extracranial EEG recordings were obtained using the wavelet artificial neural network (WANN). The WANN is also a robust signal processing tool for the estimation of nonlinear time-frequency relation and it had previously been shown to be able to classify and predict state transitions in the in vitro hippocampal slice model exhibiting spontaneous epilepsy. The variations in the power-frequency spectrum were analyzed. The accuracy of state classification was improved when more training data was used, the corresponding changes in synaptic weights between artificial neural units associated with more training data was studied to determine the correlations between learning in WANN and frequency information in human epilepsy
Keywords :
diseases; electroencephalography; medical signal processing; neural nets; signal classification; time-frequency analysis; wavelet transforms; epilepsy features; human extracranial EEG; neural codes; nonlinear time-frequency relation; power-frequency spectrum; robust signal processing tool; state classification; synaptic weights; wavelet artificial neural network; Artificial neural networks; Electroencephalography; Epilepsy; Humans; In vitro; Robustness; Signal processing; State estimation; Time frequency analysis; Training data; artificial neural network; human extracranial recording; neural code; spontaneous seizures; wavelet transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
Type :
conf
DOI :
10.1109/IEMBS.2005.1616438
Filename :
1616438
Link To Document :
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