Evaluation of filtering techniques to extract movement intention information from low-frequency EEG activity

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URI: https://hdl.handle.net/11556/2561
ISSN: 1557-170X
ISBN: 9781509028092
DOI: 10.1109/EMBC.2017.8037478
Publication date
2017-09-13
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Institute of Electrical and Electronics Engineers Inc.
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Abstract
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.
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Publisher Copyright: © 2017 IEEE.
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Signal Processing , Biomedical Engineering , Computer Vision and Pattern Recognition , Health Informatics
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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
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