Acquisition and Semi-Automated Analysis of Respiratory Muscle Surface Electromyography.

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Jove-Journal of Visualized Experiments Pub Date : 2025-01-24 DOI:10.3791/67157
Antenor Rodrigues, Luc Janssens, Daniel Langer, Umi Matsumura, Dmitry Rozenberg, Laurent Brochard, W Darlene Reid
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Abstract

Evaluating respiratory drive presents challenges due to the obtrusiveness and impracticality of current methods like functional magnetic resonance imaging (fMRI). Electromyography (EMG) offers a surrogate measure of respiratory drive to the muscles, allowing the determination of both the magnitude and timing of muscle activation. The magnitude reflects the level of muscle activation, while the timing indicates the onset and offset of muscle activity relative to specific events, such as inspiratory flow and activation of other muscles. These metrics are critical for understanding respiratory coordination and control, especially under varying loads or in the presence of respiratory pathophysiology. This study outlines a protocol for acquiring and analyzing respiratory muscle EMG signals in healthy adults and patients with respiratory health conditions. Ethical approval was obtained for the studies, which included participant preparation, electrode placement, signal acquisition, preprocessing, and postprocessing. Key steps involve cleaning the skin, locating muscles via palpation and ultrasound, and applying electrodes to minimize electrocardiography (ECG) contamination. Data is acquired at a high sampling rate and gain, with synchronized ECG and respiratory flow recordings. Preprocessing includes filtering and transforming the EMG signal, while postprocessing involves calculating onset and offset differences relative to the inspiratory flow. Representative data from a healthy male participant performing incremental inspiratory threshold loading (ITL) illustrate the protocol's application. Results showed earlier activation and prolonged duration of extradiaphragmatic muscles under higher loads, correlating with increased EMG magnitude. This protocol facilitates a detailed assessment of respiratory muscle activation, providing insights into both normal and pathophysiologic motor control strategies.

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呼吸肌表面肌电图的采集与半自动化分析。
由于目前的方法如功能性磁共振成像(fMRI)的突发性和不实用性,评估呼吸驱动提出了挑战。肌电图(EMG)提供了对肌肉呼吸驱动的替代测量,允许确定肌肉激活的幅度和时间。幅度反映了肌肉激活的水平,而时间则表明肌肉活动相对于特定事件的开始和抵消,例如吸气流和其他肌肉的激活。这些指标对于理解呼吸协调和控制至关重要,特别是在不同负荷或呼吸病理生理学存在的情况下。本研究概述了获取和分析健康成人和呼吸系统疾病患者的呼吸肌肌电图信号的方案。这些研究获得了伦理批准,包括受试者准备、电极放置、信号采集、预处理和后处理。关键步骤包括清洁皮肤,通过触诊和超声定位肌肉,并应用电极以尽量减少心电图(ECG)污染。数据以高采样率和增益获得,并伴有同步ECG和呼吸流量记录。预处理包括过滤和转换肌电信号,而后处理包括计算相对于吸气流的起始和偏移差异。一名健康男性参与者进行增量吸气阈值负荷(ITL)的代表性数据说明了该方案的应用。结果显示,在高负荷下,膈外肌的激活时间早,持续时间长,与肌电图的增加有关。该方案促进了呼吸肌激活的详细评估,提供了对正常和病理生理运动控制策略的见解。
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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
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