Faculty of Mechatronics, Armament and Aviation, Institute of Rocket Technology and Mechatronics, Military University of Technology, 2 gen. S. Kaliskiego Street, 00-908 Warsaw, Poland.
Faculty of Mechanical Engineering, Institute of Mechanics & Computational Engineering, Military University of Technology, 2 gen. S. Kaliskiego Street, 00-908 Warsaw, Poland.
Sensors (Basel). 2023 May 23;23(11):5004. doi: 10.3390/s23115004.
In the scientific literature focused on surface electromyography (sEMG) and functional near-infrared spectroscopy (fNIRS), which have been described together and separately many times, presenting different possible applications, researchers have explored a diverse range of topics related to these advanced physiological measurement techniques. However, the analysis of the two signals and their interrelationships continues to be a focus of study in both static and dynamic movements. The main purpose of this study was to determine the relationship between signals during dynamic movements. To carry out the analysis described, the authors of this research paper chose two sports exercise protocols: the Astrand-Rhyming Step Test and the Astrand Treadmill Test. In this study, oxygen consumption and muscle activity were recorded from the gastrocnemius muscle of the left leg of five female participants. This study found positive correlations between EMG and fNIRS signals in all participants: 0.343-0.788 (median-Pearson) and 0.192-0.832 (median-Spearman). On the treadmill, the signal correlations between the participants with the most active and least active lifestyle achieved the following medians: 0.788 (Pearson)/0.832 (Spearman) and 0.470 (Pearson)/0.406 (Spearman), respectively. The shapes of the changes in the EMG and fNIRS signals during exercise suggest a mutual relationship during dynamic movements. Furthermore, during the treadmill test, a higher correlation was observed between the EMG and NIRS signals in participants with a more active lifestyle. Due to the sample size, the results should be interpreted with caution.
在专注于表面肌电图 (sEMG) 和功能近红外光谱 (fNIRS) 的科学文献中，这两种技术已经被多次同时和分别描述，展示了不同的可能应用，研究人员探索了与这些先进生理测量技术相关的各种主题。然而，对两种信号的分析及其相互关系仍然是静态和动态运动研究的重点。本研究的主要目的是确定动态运动中信号之间的关系。为了进行描述的分析，本研究论文的作者选择了两种运动测试方案：Astrand-Rhyming 踏步测试和 Astrand 跑步机测试。在这项研究中，记录了 5 名女性参与者左腿腓肠肌的耗氧量和肌肉活动。本研究发现，所有参与者的 EMG 和 fNIRS 信号之间存在正相关：0.343-0.788（中位数-皮尔逊）和 0.192-0.832（中位数-斯皮尔曼）。在跑步机上，最活跃和最不活跃生活方式的参与者之间的信号相关性达到了以下中位数：0.788（皮尔逊）/0.832（斯皮尔曼）和 0.470（皮尔逊）/0.406（斯皮尔曼）。在运动过程中，EMG 和 fNIRS 信号的变化形状表明了动态运动中相互之间的关系。此外，在跑步机测试中，生活方式更活跃的参与者的 EMG 和 NIRS 信号之间的相关性更高。由于样本量较小，结果应谨慎解释。
