Feature Consistency Criterion for Motor Imagery-Based Neuromodulation
| Autor: | Eduardo Rocon, J. Ignacio Serrano, M. Dolores del Castillo, Gabriela Castellano, Carlos Alberto Stefano Filho, Romis Attux |
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| Rok vydání: | 2021 |
| Předmět: |
Protocol (science)
Computer science business.industry Consistency criterion Machine learning computer.software_genre medicine.disease Neuromodulation (medicine) Cerebral palsy Consistency (database systems) Motor imagery Feature (computer vision) medicine Artificial intelligence business computer Neurorehabilitation |
| Zdroj: | Biosystems & Biorobotics ISBN: 9783030703158 |
| DOI: | 10.1007/978-3-030-70316-5_86 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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