Designing a Model to Detect Beta Burst in EEG Using Nonlinear Dynamic Features Based on Machine Learning
Armin Hakkak Moghadam Torbati, Narges Davoudi, G. Longo
This paper develops a machine learning model to classify beta bursts in EEG using nonlinear dynamic features, achieving high accuracy in distinguishing burst durations and task conditions.
Biomedical Signal Processing and Control · Mar 23, 2026Peer-reviewedNeuroscience