Estimation of Respiratory Rate From Photoplethysmogram Data Using Time-Frequency Spectral Estimation
Estimation of Respiratory Rate From Photoplethysmogram Data Using Time-Frequency Spectral Estimation
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DOI：
10.1109/tbme.2009.2019766
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发表时间：
2009-08-01
影响因子：
4.6
通讯作者：
Ju, Kihwan
中科院分区：
文献类型：
--
作者：
Chon, Ki H.;Dash, Shishir;Ju, Kihwan
我们提出了一种新的方法，使用脉搏血氧仪信号来估计呼吸率。该方法使用最近开发的时间-频率谱估计方法，变频复解调（VFCDM），以识别频率调制（FM）的光电容积描记图波形。该FM具有可测量的周期性，其提供呼吸周期的估计。我们比较了VFCDM的连续小波变换（CWT）和自回归（AR）模型的方法的性能。CWT方法还利用由FM或AM表示的呼吸性窦性心律不齐效应来估计呼吸率。CWT和AR模型方法之前都已被证明可以提供正常范围（12-26次呼吸/分钟）内的呼吸速率的合理良好估计。然而，据我们所知，高于26次呼吸/分钟的呼吸率以及这些算法的实时性能尚未经过测试。我们基于15名健康受试者的分析表明，VFCDM方法在准确性（更小的中位误差）、一致性（更小的中位值四分位范围）和计算效率（使用MATLAB实现的1分钟数据小于0.3 s）方面提供了最佳结果，以提取12-36次呼吸/min的呼吸率。
We present a new method that uses the pulse oximeter signal to estimate the respiratory rate. The method uses a recently developed time-frequency spectral estimation method, variable-frequency complex demodulation (VFCDM), to identify frequency modulation (FM) of the photoplethysmogram waveform. This FM has a measurable periodicity, which provides an estimate of the respiration period. We compared the performance of VFCDM to the continuous wavelet transform (CWT) and autoregressive (AR) model approaches. The CWT method also utilizes the respiratory sinus arrhythmia effect as represented by either FM or AM to estimate respiratory rates. Both CWT and AR model methods have been previously shown to provide reasonably good estimates of breathing rates that are in the normal range (12-26 breaths/min). However, to our knowledge, breathing rates higher than 26 breaths/min and the real-time performance of these algorithms are yet to be tested. Our analysis based on 15 healthy subjects reveals that the VFCDM method provides the best results in terms of accuracy (smaller median error), consistency (smaller interquartile range of the median value), and computational efficiency (less than 0.3 s on 1 min of data using a MATLAB implementation) to extract breathing rates that varied from 12-36 breaths/min.