Prediction of balance function for stroke based on EEG and fNIRS features during ankle dorsiflexion
- PMID: 36061607
- PMCID: PMC9433808
- DOI: 10.3389/fnins.2022.968928
Prediction of balance function for stroke based on EEG and fNIRS features during ankle dorsiflexion
Abstract
Balance rehabilitation is exceedingly crucial during stroke rehabilitation and is highly related to the stroke patients' secondary injuries (caused by falling). Stroke patients focus on walking ability rehabilitation during the early stage. Ankle dorsiflexion can activate the brain areas of stroke patients, similar to walking. The combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) was a new method, providing more beneficial information. We extracted the event-related desynchronization (ERD), oxygenated hemoglobin (HBO), and Phase Synchronization Index (PSI) features during ankle dorsiflexion from EEG and fNIRS. Moreover, we established a linear regression model to predict Berg Balance Scale (BBS) values and used an eightfold cross validation to test the model. The results showed that ERD, HBO, PSI, and age were critical biomarkers in predicting BBS. ERD and HBO during ankle dorsiflexion and age were promising biomarkers for stroke motor recovery.
Keywords: EEG; balance rehabilitation; brain-computer interface; fNIRS; stroke.
Copyright © 2022 Liang, Song, Belkacem, Li, Liu, Chen, Wang, Wang and Wan.
Conflict of interest statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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