Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.
Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review.
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DOI：
10.1109/rbme.2017.2763681
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发表时间：
2018
影响因子：
17.6
通讯作者：
Clifton DA
中科院分区：
文献类型：
--
作者：
Charlton PH;Birrenkott DA;Bonnici T;Pimentel MAF;Johnson AEW;Alastruey J;Tarassenko L;Watkinson PJ;Beale R;Clifton DA
呼吸率（BR）是一个关键的生理参数，用于一系列的临床设置。尽管它的诊断和预后价值，它仍然是广泛测量人工计数呼吸。已经提出了大量的算法来从心电图（ECG）和脉搏血氧饱和度（光电容积描记图，PPG）信号估计BR。这些BR算法为医疗保健和健身监测中的BR自动化、电子化和非侵入性测量提供了机会。本文介绍了文献的BR估计从ECG和PPG。首先，BR算法的结构和在每个阶段使用的数学技术进行了描述。其次，已被用来评估BR算法的性能的实验方法进行了审查，和BR算法的评估方法框架。第三，我们概述了未来研究的最紧迫方向，包括在可穿戴传感器，远程视频监控和临床实践中使用BR算法所需的步骤。
Breathing rate (BR) is a key physiological parameter used in a range of clinical settings. Despite its diagnostic and prognostic value, it is still widely measured by counting breaths manually. A plethora of algorithms have been proposed to estimate BR from the electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. These BR algorithms provide opportunity for automated, electronic, and unobtrusive measurement of BR in both healthcare and fitness monitoring. This paper presents a review of the literature on BR estimation from the ECG and PPG. First, the structure of BR algorithms and the mathematical techniques used at each stage are described. Second, the experimental methodologies that have been used to assess the performance of BR algorithms are reviewed, and a methodological framework for the assessment of BR algorithms is presented. Third, we outline the most pressing directions for future research, including the steps required to use BR algorithms in wearable sensors, remote video monitoring, and clinical practice.