Abstract
Stroke-induced motor deficits need personalized rehabilitation therapies to maximize motor recovery. Integrating Brain-Computer Interface (BCI) technology with robotized exoskeletons, enabling a closed-loop proprioceptive feedback loop to the injured brain, represents a promising approach for enhancing rehabilitation outcomes. However, understanding the longitudinal impact of this integrated approach on stroke recovery is paramount importance. Monitoring through electroencephalography (EEG) patterns holds promise in providing valuable insights into the neurophysiological adaptations occurring during rehabilitation, thereby providing valuable data for personalized treatment strategies and therefore, for optimizing the recovery process.
A longitudinal study was conducted to assess the effect of integrating a BCI-robotized orthesic hand in stroke rehabilitation, leveraging clinical evaluation and quantitative EEG analysis for monitoring. This study aims to elucidate neural mechanisms underlying rehabilitation and optimize treatment strategies to enhance stroke recovery, with EEG changes serving as valuable indicators of neuroplasticity.
This work was supported by the Ministry of Science and Innovation, belonging to the Agencia Estatal de Innovación (AEI) through the projects PLEC2022-009424 and PID2022-139957OB-I00, and by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, through the project CIPROM/2022/12.
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Abbreviations
- ATH:
-
Atherotrombotic
- BCI:
-
Brain-Computer Interface
- EEG:
-
Electroencephalography
- ERD:
-
Event-related desynchronization
- ERP:
-
Event-related potencial
- ERS:
-
Event-related synchronization
- FMA-UE:
-
Fugl-Meyer Assessment for upper extremity
- MCA:
-
Middle Cerebral Artery
- MRC:
-
Medical Research Council
- MRI:
-
Magnetic Resonance Imaging
- PCA:
-
Posterior Cerebral Artery
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This work involved human subjects in its research. Approval of all ethical and experimental procedures and protocols was granted by the Miguel Hernandez University’s Ethical Committee under Application No. 2017.32.E.OEP.
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Vales, Y., Catalan, J.M., Blanco-Ivorra, A., Barios, J.A., Garcia-Aracil, N. (2024). Comprehensive Evaluation of Stroke Rehabilitation Dynamics: Integrating Brain-Computer Interface with Robotized Orthesic Hand and Longitudinal EEG Changes. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Artificial Intelligence for Neuroscience and Emotional Systems. IWINAC 2024. Lecture Notes in Computer Science, vol 14674. Springer, Cham. https://doi.org/10.1007/978-3-031-61140-7_17
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