Chest Movement and Respiratory Volume both Contribute to Thoracic Bioimpedance during Loaded Breathing
Chest Movement and Respiratory Volume both Contribute to Thoracic Bioimpedance during Loaded Breathing
复制标题
DOI：
10.1038/s41598-019-56588-4
复制
发表时间：
2019-12-27
影响因子：
4.6
通讯作者：
Jane, Raimon
中科院分区：
文献类型：
--
作者：
Blanco-Almazan, Dolores;Groenendaal, Willemijn;Jane, Raimon
由于生物阻抗与正常呼吸期间的呼吸量呈线性关系，因此生物阻抗已被广泛研究作为呼吸监测方法的替代方法。然而，其他身体组织和体液有助于生物阻抗测量。本研究的目的是调查胸部运动在胸部生物阻抗贡献中的相关性，以评估生物阻抗用于呼吸监测的适用性。我们测量了10名健康受试者在吸气负荷过程中的气流，生物阻抗在四个电极配置和胸部加速度计数据。该协议允许我们研究在不同水平的吸气肌活动的贡献。我们使用胸部运动和体积信号来表征生物阻抗信号，使用线性混合效应模型和神经网络来描述每个受试者和肌肉活动水平。使用每个呼吸周期的平均平均百分比误差评价性能。线性模型和神经网络的最低误差对应于胸部运动和体积的组合。特别是，神经网络的错误率较低（中位数低于4.29%）。在高水平的肌肉活动，模型性能的差异表明胸部运动的生物阻抗信号的贡献增加。因此，胸部运动对生物阻抗测量有很大贡献，并且在高肌肉活动水平下更显著。
Bioimpedance has been widely studied as alternative to respiratory monitoring methods because of its linear relationship with respiratory volume during normal breathing. However, other body tissues and fluids contribute to the bioimpedance measurement. The objective of this study is to investigate the relevance of chest movement in thoracic bioimpedance contributions to evaluate the applicability of bioimpedance for respiratory monitoring. We measured airflow, bioimpedance at four electrode configurations and thoracic accelerometer data in 10 healthy subjects during inspiratory loading. This protocol permitted us to study the contributions during different levels of inspiratory muscle activity. We used chest movement and volume signals to characterize the bioimpedance signal using linear mixed-effect models and neural networks for each subject and level of muscle activity. The performance was evaluated using the Mean Average Percentage Errors for each respiratory cycle. The lowest errors corresponded to the combination of chest movement and volume for both linear models and neural networks. Particularly, neural networks presented lower errors (median below 4.29%). At high levels of muscle activity, the differences in model performance indicated an increased contribution of chest movement to the bioimpedance signal. Accordingly, chest movement contributed substantially to bioimpedance measurement and more notably at high muscle activity levels.