Qitong Chu: School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300130, China.
Xin Guo: School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300130, China.
Tengyu Zhang: Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, National Research Center for Rehabilitation Technical Aids, Beijing 100176, China. ORCID
Congcong Huo: Beijing Advanced Innovation Centre for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Xuemin Zhang: Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, National Research Center for Rehabilitation Technical Aids, Beijing 100176, China.
Gongcheng Xu: Beijing Advanced Innovation Centre for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Zhaoxin Lun: School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300130, China.
Shengcui Cheng: Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
Ping Xie: Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province, School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.
Stroke is one of the primary causes of motor disorders, which can seriously affect the patient's quality of life. However, the assessment of the upper limb affected by Stroke is commonly based on scales, and the characteristics of brain reorganization induced by limb movement are not clear. Thus, this study aimed to investigate Stroke-related cortical reorganization based on functional near infrared spectroscopy (fNIRS) during upper limb multi-joint linkage movement with reference to the Fugl-Meyer Assessment of the upper extremities (FMA-UE). In total, 15 Strokepatients and 15 healthy subjects participated in this study. The functional connectivity (FC) between channels and the regions of interest (ROI) was calculated by Pearson's correlation coefficient. The results showed that compared with the control group, the FC between the prefrontal cortex and the motor cortex was significantly increased in the resting state and the affected upper limb's multi-joint linkage movements, while the FC between the motor cortex was significantly decreased during the unaffected upper limb's multi-joint linkage movements. Moreover, the significantly increased ROI FC in the resting state showed a significantly positive correlation with FMA-UE in Strokepatients ( < 0.05). This study highlights a new biomarker for evaluating the function of movement in Strokepatients and provides guidance for rehabilitation training.
