Abnormal Low-Frequency Corticokinematic Coherence in Stroke: An Electroencephalography and Acceleration Study - Ping Xie; Ying Wang; Jian Yu; Yan Lv; Shengcui Cheng; Yingying Hao; Xiaoling Chen; Tengyu Zhang; Jie Chen (IEEE, 2024)
Motor control is a complex process of coordination and information interaction among neural, motor, and sensory functions. Investigating the correlation between motor-physiological information helps to understand the human motor control mechanisms and is important for the assessment of motor function status. In this manuscript, we investigated the differences in the neuromotor coupling analysis between healthy controls and stroke patients in different movements. We applied the corticokinematic coherence (CKC) function between the electroencephalogram (EEG) and acceleration (ACC) data. First, we collected the EEG and ACC data from 10 healthy controls and 10 stroke patients under the task of movement execution (ear touch and knee touch) and movement maintenance (ear touch and knee touch). After the preprocessing of raw data, we used frequency domain coherence method to analyze the full-frequency EEG and ACC data, which could be concluded that the CKC intensity in the movement execution was higher than that in the movement maintenance. However, there was no significant difference between healthy subjects and stroke patients. Secondly, the coherence results in local frequency bands showed that low-frequency bands could better reflect the difference between movement execution and maintenance. The intensity of coherence in healthy subjects was significantly higher than that in other bands, but not in stroke patients. Further comparison of coherence results in local frequency bands showed that the intensity of theta band in healthy controls was significantly higher than other rhythms, especially in the knee touch phase. Therefore, we infer that neurodynamic coupling analysis based on EEG and ACC data can show the differences between healthy subjects and stroke patients. Such researches could add to the understanding of neuro-motor control mechanisms and provide new quantitative indicators on the motor function assessment.