Application of EEG-based Machine Learning in Stock Trading-related Emotion Recognition
Mingliang Zuo,
Bingbing Yu,
Li Sui
Abstract:This paper develops a stock emotion recognition system based on a valence/arousal model using electroencephalogram (EEG) signals. The dataset is collected from participants who engage in paper trading using real stock market data, virtual currencies, and emotional outputs. The dataset contains five frequency bands, features such as differential entropy (DE), differential asymmetry (DASM), and rational asymmetry (RASM). Feature selection is performed using mutual information-based filtering combined with chi-sq… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.