Deep learning methods for electroencephalogram (eeg) spike detection
Lim, Guan You
Date of Issue2017-05-15
School of Electrical and Electronic Engineering
This project is about developing novel deep learning methods for detecting abnormalities in time series. Specifically, we will consider the problem of detecting spikes in the EEG of patients of epilepsy as well as recurrent neural networks. We will also analyze the EEG of healthy subjects, as a baseline. This project was concluded on April 2017 and it was found that long short term memory networks work decently well in the spike detection of epileptic spikes. Tuned parameters were also presented in this report.
Final Year Project (FYP)
Nanyang Technological University