Abstract
Motor imagery (MI) has been increasingly studied for neurorehabilitation purposes. However, issues such as large intra- and inter-subject variability still limit its practical, and more clinical, applications. Seeking appropriate features for MI-neuromodulation training is thus a crucial step. This work presents a protocol that selects features related to the MI mental patterns maximizing consistency (i.e., minimizing variability) across two recordings in different days. We apply our methodology to 3 healthy adults and 3 children with cerebral palsy, illustrating its feasibility for MI training protocols.
This work was supported by: FAPESP (São Paulo Research Foundation) grants #2019/18409-9 and #2013/07559-3; CNPq (Brazilian’s National Council for Scientific and Technological Development) grant #308811/2019-4; Programas de Actividades I+D en la Comunidad de Madrid and Structural Funds of the EU (S2018/NMT-4331); Ministry of Economy and Competitiveness (DPI2015-68664-C4-1-R).
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Stefano Filho, C.A., Ignacio Serrano, J., Attux, R., Castellano, G., Dolores del Castillo, M., Rocon, E. (2022). Feature Consistency Criterion for Motor Imagery-Based Neuromodulation. In: Torricelli, D., Akay, M., Pons, J.L. (eds) Converging Clinical and Engineering Research on Neurorehabilitation IV. ICNR 2020. Biosystems & Biorobotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-030-70316-5_86
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DOI: https://doi.org/10.1007/978-3-030-70316-5_86
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