Huang Ruisen, Shang Wenze, Lin Yongji, Liang Fengyan, Yin Ming, Lu Xiao-Ping, Wu Xinyu, Gao Fei
Annu Int Conf IEEE Eng Med Biol Soc. 2024 Jul;2024:1-6. doi: 10.1109/EMBC53108.2024.10782412.
Understanding the intricate relationship between brain activations and muscle activations during motor tasks is crucial for elucidating motor control mechanisms and designing effective rehabilitation strategies. In this study, we investigated this relationship using functional near-infrared spectroscopy (fNIRS) and surface electromyography (sEMG) technologies. Three healthy male subjects performed lower-limb motor tasks while their brain activations and muscle activations were recorded simultaneously. The fNIRS data were converted to optical densities and filtered by lowpass filter, detrending, and short-separation regression to remove artifacts. The filtered signals were fed to a general linear model with the desired hemodynamic responses (dHRFs) constructed with Balloon model and simulated physiological noises reconstructed with the parameters obtained from the spectrum analysis of baseline signals. Despite the extracted hemodynamic responses from fNIRS data, sEMG signals were lowpass and analyzed to detect muscle activations. Results revealed that cerebral activations during lateral leg flexion tasks were similar yet only partially consistent with those observed in stand-up tasks. Significant correlations between brain and muscle activations were also observed, highlighting the complex interplay between central and peripheral neural mechanisms during motor control. These findings provide valuable insights into the neural basis of motor control and have implications for developing personalized rehabilitation interventions and assistive technologies to enhance motor function in clinical populations.
了解运动任务期间大脑激活与肌肉激活之间的复杂关系对于阐明运动控制机制和设计有效的康复策略至关重要。在本研究中，我们使用功能近红外光谱（fNIRS）和表面肌电图（sEMG）技术研究了这种关系。三名健康男性受试者在进行下肢运动任务时，同时记录他们的大脑激活和肌肉激活情况。fNIRS数据被转换为光密度，并通过低通滤波、去趋势和短分离回归进行滤波以去除伪迹。将滤波后的信号输入到一个通用线性模型中，该模型具有用球囊模型构建的期望血液动力学响应（dHRF），并用从基线信号频谱分析获得的参数重建模拟生理噪声。尽管从fNIRS数据中提取了血液动力学响应，但对sEMG信号进行了低通滤波并分析以检测肌肉激活情况。结果显示，在侧腿屈曲任务期间的大脑激活与在站立任务中观察到的激活相似但仅部分一致。还观察到大脑和肌肉激活之间存在显著相关性，突出了运动控制过程中中枢和外周神经机制之间的复杂相互作用。这些发现为运动控制的神经基础提供了有价值的见解，并对开发个性化康复干预措施和辅助技术以增强临床人群的运动功能具有启示意义。
