Application of Empirical Mode Decomposition (Emd) for automated detection of epilepsy using Eeg signals

• Main Authors: Martis, Roshan Joy, Acharya, U. Rajendra, Tan, Jen Hong, Petznick, Andrea, Yanti, Ratna, Chua, Chua Kuang, Ng, Eddie Yin-Kwee, Tong, Louis
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2013
• Online Access: https://hdl.handle.net/10356/96823; http://hdl.handle.net/10220/11625
• Institution: Nanyang Technological University

Epilepsy is a global disease with considerable incidence due to recurrent unprovoked seizures. These seizures can be noninvasively diagnosed using electroencephalogram (EEG), a measure of neuronal electrical activity in brain recorded along scalp. EEG is highly nonlinear, nonstationary and non-Gauss...