Title :
Neural network detection of antiepileptic drugs from a single EEG trace
Author :
Echauz, Javier ; Vachtsevanos, George
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
Three systems-a Bayes quadratic classifier (BQ), a self-organizing polynomial network (PN), and a backpropagation neural network (NN)-were created for subject-independent classification into either no-drug or antiepileptic drug categories from a single 2.1-second EEG trace at the Pz/A1+A2 channel. Spectral features were derived from the raw signals, and then preprocessed using singular value decomposition prior to their classification. Recognition rates on an independent data set were 63.5%, 60.4%, and 74.0% for the BQ, PN, and NN respectively
Keywords :
Bayes methods; backpropagation; electroencephalography; medical signal processing; neural nets; singular value decomposition; Bayes quadratic classifier; antiepileptic drugs; backpropagation neural network; classification; neural network detection; self-organizing polynomial network; single EEG trace; singular value decomposition; spectral features; subject-independent classification; Biological neural networks; Computer networks; Drugs; Electroencephalography; Feature extraction; Frequency; Humans; Neural networks; Pharmaceutical technology; Scalp;
Conference_Titel :
Electro/94 International. Conference Proceedings. Combined Volumes.
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-2630-X
DOI :
10.1109/ELECTR.1994.472689
