Prediction of balance function for stroke based on EEG and fNIRS features during ankle dorsiflexion

Jun Liang; Yanxin Song; Abdelkader Nasreddine Belkacem; Fengmin Li; Shizhong Liu; Xiaona Chen; Xinrui Wang; Yueyun Wang; Chunxiao Wan

doi:10.3389/fnins.2022.968928

Prediction of balance function for stroke based on EEG and fNIRS features during ankle dorsiflexion

Front Neurosci. 2022 Aug 18:16:968928. doi: 10.3389/fnins.2022.968928. eCollection 2022.

Authors

Jun Liang^{1

2}, Yanxin Song³, Abdelkader Nasreddine Belkacem⁴, Fengmin Li¹, Shizhong Liu¹, Xiaona Chen¹, Xinrui Wang¹, Yueyun Wang¹, Chunxiao Wan¹

Affiliations

¹ Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin, China.
² Laboratory of Neural Engineering and Rehabilitation, Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
³ Tianjin Tianshi College, Tianjin, China.
⁴ Department of Computer and Network Engineering, College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates.

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.