RT Conference Proceedings
T1 Evaluation of filtering techniques to extract movement intention information from low-frequency EEG activity
A1 Bibian, Carlos
A1 Lopez-Larraz, Eduardo
A1 Irastorza-Landa, Nerea
A1 Birbaumer, Niels
A1 Ramos-Murguialday, Ander
AB Low-frequency electroencephalographic (EEG) activity provides relevant information for decoding movement commands in healthy subjects and paralyzed patients. Brainmachine interfaces (BMI) exploiting these signals have been developed to provide closed-loop feedback and induce neuroplasticity. Several offline and online studies have already demonstrated that discriminable information related to movement can be decoded from low-frequency EEG activity. However, there is still not a well-established procedure to guarantee that this activity is optimally filtered from the background noise. This work compares different configurations of non-causal (i.e., offline) and causal (i.e., online) filters to classify movement-related cortical potentials (MRCP) with six healthy subjects during reaching movements. Our results reveal important differences in MRCP decoding accuracy dependent on the selected frequency band for both offline and online approaches. In summary, this paper underlines the importance of optimally choosing filter parameters, since their variable response has an impact on the classification of low EEG frequencies for BMI.
PB Institute of Electrical and Electronics Engineers Inc.
SN 9781509028092
SN 1557-170X
YR 2017
FD 2017-09-13
LK https://hdl.handle.net/11556/2561
UL https://hdl.handle.net/11556/2561
LA eng
NO Bibian , C , Lopez-Larraz , E , Irastorza-Landa , N , Birbaumer , N & Ramos-Murguialday , A 2017 , Evaluation of filtering techniques to extract movement intention information from low-frequency EEG activity . in 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society : Smarter Technology for a Healthier World, EMBC 2017 - Proceedings . , 8037478 , Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS , Institute of Electrical and Electronics Engineers Inc. , pp. 2960-2963 , 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 , Jeju Island , Korea, Republic of , 11/07/17 . https://doi.org/10.1109/EMBC.2017.8037478
NO conference
NO Publisher Copyright: © 2017 IEEE.
NO This study was funded by the Baden-Württemberg Stiftung (GRUENS ROB-1), the Deutsche Forschungsgemeinschaft (DFG, Koselleck), the Fortüne-Program of the University of Tübingen (2422-0-0), and the Bundesministerium für Bil-dung und Forschung BMBF MOTORBIC (FKZ 13GW0053) and AMORSA (FKZ 16SV7754). N. Irastorza-Landa’s work is supported by the Basque Government (IKERBASQUE, Basque Foundation for Science).
DS TECNALIA Publications
RD 26 jul 2024