Automatic BSS-based filtering of metallic interference in MEG recordings: definition and validation using simulated signals
Por:
Migliorelli C, Alonso JF, Romero-Lafuente S, Mañanas MA, Nowak R and Russi A
Publicada:
1 ago 2015
Ahead of Print:
27 may 2015
Resumen:
One of the principal drawbacks of magnetoencephalography (MEG) is its high sensitivity to metallic artifacts, which come from implanted intracranial electrodes and dental ferromagnetic prosthesis and produce a high distortion that masks cerebral activity. The aim of this study was to develop an automatic algorithm based on blind source separation (BSS) techniques to remove metallic artifacts from MEG signals.
Filiaciones:
Migliorelli C:
Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain. Biomedical Research Networking center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain
Open Access
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