Delft University of Technology, Circuits and Systems (CAS) group, Delft, 2600 AA, the Netherlands.
KU Leuven, Department of Electrical Engineering-ESAT, STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Leuven, 3001, Belgium.
Sci Rep. 2020 Mar 31;10(1):5704. doi: 10.1038/s41598-020-62624-5.
Cardiorespiratory monitoring is crucial for the diagnosis and management of multiple conditions such as stress and sleep disorders. Therefore, the development of ambulatory systems providing continuous, comfortable, and inexpensive means for monitoring represents an important research topic. Several techniques have been proposed in the literature to derive respiratory information from the ECG signal. Ten methods to compute single-lead ECG-derived respiration (EDR) were compared under multiple conditions, including different recording systems, baseline wander, normal and abnormal breathing patterns, changes in breathing rate, noise, and artifacts. Respiratory rates, wave morphology, and cardiorespiratory information were derived from the ECG and compared to those extracted from a reference respiratory signal. Three datasets were considered for analysis, involving a total 59 482 one-min, single-lead ECG segments recorded from 156 subjects. The results indicate that the methods based on QRS slopes outperform the other methods. This result is particularly interesting since simplicity is crucial for the development of ECG-based ambulatory systems.
心肺监测对于多种病症的诊断和管理至关重要，如压力和睡眠障碍。因此，开发能够提供连续、舒适和经济的监测手段的可移动系统是一个重要的研究课题。已有文献提出了多种从心电图信号中提取呼吸信息的技术。在多种条件下比较了 10 种计算单导联心电图衍生呼吸（EDR）的方法，包括不同的记录系统、基线漂移、正常和异常呼吸模式、呼吸频率变化、噪声和伪影。从心电图中提取呼吸率、波形态和心肺信息，并与参考呼吸信号中提取的信息进行比较。分析了三个数据集，共涉及从 156 名受试者记录的 59482 个一分钟单导联 ECG 片段。结果表明，基于 QRS 斜率的方法优于其他方法。这一结果特别有趣，因为简单性对于基于心电图的可移动系统的开发至关重要。
