RT Conference Proceedings
T1 Bi-LSTM Neural Network for EEG-based detection of musical characteristics
A1 Ariza Cervera, Isaac
A1 Guillén, Sergio
A1 Tardón-García, Lorenzo José
A1 Barbancho-Pérez, Ana María
A1 Barbancho-Pérez, Isabel
K1 Redes neuronales (Informática)
K1 Aprendizaje
K1 Música - Estudio y enseñanza
AB Electroencephalography (EEG) combined with Deep Learning and digital signal processing allows for mental activity recognition. In our study, a new feature extraction model-based is presented when combined with Bi-LSTM Neural Networks for EEG musical characteristics classification. This method can be used for both intra- and inter-subject scenarios reaching compelling accuracy values.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/29209
UL https://hdl.handle.net/10630/29209
LA eng
NO This publication is part of project PID2021-123207NB-I00, funded by MCIN / AEI / 10.13039 / 501100011033 / FEDER, UE. Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026