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

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number968928
JournalFrontiers in Neuroscience
Volume16
DOIs
Publication statusPublished - Aug 18 2022

Keywords

  • EEG
  • balance rehabilitation
  • brain-computer interface
  • fNIRS
  • stroke

ASJC Scopus subject areas

  • Neuroscience(all)

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