Bi-LSTM neural network for EEG-based error detection in musicians’ performance

• Published in: Biomedical signal processing and control Vol. 78; p. 103885
• Main Authors: Ariza, Isaac, Tardón, Lorenzo J., Barbancho, Ana M., De-Torres, Irene, Barbancho, Isabel
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2022
• Subjects: Bidirectional Long Short Term Memory (Bi-LSTM) network; Electroencephalogram (EEG); Mel-Frequency Cepstral Coefficients (MFCC); Musician performance; Bidirectional Long Short Term Memory (Bi-LSTM) network; Electroencephalogram (EEG); Mel-Frequency Cepstral Coefficients (MFCC); Musician performance

Electroencephalography (EEG) is a tool that allows us to analyze brain activity with high temporal resolution. These measures, combined with deep learning and digital signal processing, are widely used in neurological disorder detection and emotion and mental activity recognition. In this paper, a n...