Automatic detection of epileptiform discharges using an artificial neural network

作者：Liu Shu-Peng; Yan Zhuang-Zhi; He Xuan; Xie Feng

来源：Chinese Journal of Biomedical Engineering, 2003, 22(5): 433-437.

• False positive rate (FPR)

This paper presents an approach to assist doctors'diagnosis of epileptiform discharges(ED) in EEG. The approach achieved automatic detection of ED by using an artificial neural network (ANN). The ANN was trained by the ED patterns selected according to the distribution curve of the peak value of the ANN output, with the parameters characters extracted. Then the threshold was calculated. The experimental results of three patients'EEG showed that the average hit rate (HR) was 91% while the average false positive rate (FPR) was 15%.

• 出版日期2003
• 单位上海大学