EEG Based Generative Depression Discriminator

arXiv:2402.09421v1 Announce Type: cross
Abstract: Depression is a very common but serious mood disorder.In this paper, We built a generative detection network(GDN) in accordance with three physiological laws. Our aim is that we expect the neural network to learn the relevant brain activity based on the EEG signal and, at the same time, to regenerate the target electrode signal based on the brain activity. We trained two generators, the first one learns the characteristics of depressed brain activity, and the …

abstract aim arxiv brain brain activity cs.lg depression detection eeg eess.sp expect generative laws learn mood network neural network paper signal type