Virtual Spirometry and Activity Monitoring Using Multichannel Electrical Impedance Plethysmographs in Ambulatory Settings.
Virtual Spirometry and Activity Monitoring Using Multichannel Electrical Impedance Plethysmographs in Ambulatory Settings.
复制标题
在动态环境中使用多通道电阻体积描记器进行虚拟肺活量测定和活动监测。
DOI：
10.1109/tbcas.2017.2688339
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发表时间：
2017
影响因子：
5.1
通讯作者：
Chakrabartty,Shantanu
中科院分区：
文献类型：
--
作者：
Khan,HassanAqeel;Gore,Amit;Ashe,Jeffrey;Chakrabartty,Shantanu
对呼吸模式和身体活动水平的连续监测可用于患有心脏病和慢性阻塞性肺病等疾病的患者的远程健康管理。在临床环境中，肺活量计是监测呼吸模式（如呼吸频率和肺容量变化）的金标准。然而，使用肺活量计的直接测量需要将传感器放置在患者的气道中，并且因此对于非临床、流动设置中的连续监测是不可行的。在这些条件下，使用电阻抗体积描记器（EIP）的间接呼吸监测更合适，但易受运动伪影的影响。在本文中，我们调查是否可以使用多通道EIP进行虚拟肺功能测定在门诊设置。本文中提出的实验是基于从19个成年人受试者收集的初步数据，在现实的流动和非流动设置。我们首先强调从标准肺量计获得的信号的显著特征。然后，我们比较了不同的生物信号处理算法的性能，估计使用多个EIP传感器的肺活量计信号，并在存在运动伪影和现实世界的干扰。我们证明，除了可靠地确定不同的呼吸模式和状态，多通道EIP还可以用于可靠地提取有关不同患者身体活动状态（如弯曲或伸展）的信息。
Continuous monitoring of respiratory patterns and physical activity levels can be useful for remote health management of patients with conditions such as heart disease and chronic obstructive pulmonary disease. In a clinical setting, spirometers serve as the gold standard for monitoring respiratory patterns such as breathing rate and changes in lung volume. However, direct measurements using a spirometer requires placement of a sensor in the patient's airway and is thus infeasible for continuous monitoring in nonclinical, ambulatory settings. Under these conditions, indirect respiration monitoring using electrical impedance plethysmographs (EIP) is more suitable but are susceptible to motion artifacts. In this paper, we investigate whether multichannel EIP can be used to perform virtual spirometry under ambulatory settings. The experiments presented in this paper are based on preliminary data collected from 19 adult human subjects under realistic ambulatory and nonambulatory settings. We first highlight the salient features of the signal acquired from a standard spirometer. We then compare the performance of different biosignal processing algorithms in estimating the spirometer signal using multiple EIP sensors and in the presence of motion artifacts and real-world interferences. We demonstrate that in addition to reliably determining different respiratory patterns and states, multichannel EIP could also be used to reliably extract information regarding different patient physical activity states like bending or stretching.