Acquiring Respiration Rate from Photoplethysmographic Signal by Recursive Bayesian Tracking of Intrinsic Modes in Time-Frequency Spectra

Abstract

Respiration rate (RR) provides useful information for assessing the status of a patient. We propose RR estimation based on photoplethysmography (PPG) because the blood perfusion dynamics are known to carry information on breathing, as respiration-induced modulations in the PPG signal. We studied the use of amplitude variability of transmittance mode finger PPG signal in RR estimation by comparing four time-frequency (TF) representation methods of the signal cascaded with a particle filter. The TF methods compared were short-time Fourier transform (STFT) and three types of synchrosqueezing methods. The public VORTAL database was used in this study. The results indicate that the advanced frequency reallocation methods based on synchrosqueezing approach may present improvement over linear methods, such as STFT. The best results were achieved using wavelet synchrosqueezing transform, having a mean absolute error and median error of 2.33 and 1.15 breaths per minute, respectively. Synchrosqueezing methods were generally more accurate than STFT on most of the subjects when particle filtering was applied. While TF analysis combined with particle filtering is a promising alternative for real-time estimation of RR, artefacts and non-respiration-related frequency components remain problematic and impose requirements for further studies in the areas of signal processing algorithms an PPG instrumentation.

Photoplethysmography based atrial fibrillation detection: a review

“…22 Respiratory rate is one of the fundamental vital signs and can be determined from the time-frequency representation of a PPG signal. 23 Some hemodynamic parameters such as augmentation index (AIx) and pulse wave velocity (PWV) are important biomarkers of arterial stiffness, which is a direct cause of hypertension and a major risk factor for cardiovascular events such as myocardial infarction and stroke. Both AIx and PWV could be derived from PPG, 24,25 Subendocardial Viability Ratio (SEVR %) and Ejection Time Index (ETI) are two hemodynamic parameters used in the evaluation of cardiac workload that can be estimated with PPG analysis.…”

A Novel Non-Invasive Estimation of Respiration Rate From Motion Corrupted Photoplethysmograph Signal Using Machine Learning Model

“…In [29], PPG-RR calculations were retrospectively conducted on PPG waveforms derived from the data warehouse and compared with RR reference values during the validation stage of the algorithm. In [30], the use of amplitude fluctuations of the transmittance mode finger PPG signal in RR estimation by comparing four time-frequency (TF) signal representation approaches cascaded with a particle filter was studied.…”

“…This manuscript is divided into four sections where Sec- [10] Fast Fourier Transformation (FFT) Orphanidou et al [19] Ensemble Empirical Mode Decomposition Pimentel et al [12], [37] Auto-regressive Model Philip et al [16] Spot Assessment Mirmohamadsadegh et al [20] Instantaneous Frequency Tracking Algorithm Lin et al [38] Wavelet-Based Algorithm Fleming et al [39] Auto-regressive Model Zhou et al [40] Independent Component Analysis (ICA) Algorithm Moreno et al [41] Digital Filtering Nilsson et al [42] Digital Filtering Motin et al [27], [28] Empirical Mode Decomposition Jarchi et al [31] Accelerometer Based Hartmann et al [32] Fast Fourier Transformation (FFT) Pirhonen et al [30] Wavelet-Based Zhang et al [26], [43] Joint Sparse Signal Reconstruction Madhav et al [44] Modified multi scale principal component analysis (MMSPCA)…”

PPGTempStitch: A MATLAB Toolbox for Augmenting Annotated Photoplethsmogram Signals

“…Photoplethysmography can be used to evaluate heart rate [3,4], blood oxygen saturation [5], respiration rate [6], hypertension [7,8], the ankle-brachial pressure index [9], vascular aging [10,11], and other cardiovascular parameters.…”