Respiratory rate estimation using respiratory sinus arrhythmia from photoplethysmography

Abstract

Respiratory rate (RR) is an important measurement for ambulatory care and there is high interest in its detection using unobtrusive mobile devices. For this study, we investigated the estimation of RR from a photoplethysmography (PPG) signal that originated from a pulse oximeter sensor and had a sub-optimal sampling rate. We explored the possibility of estimating RR by extracting respiratory sinus arrhythmia (RSA) from the PPG-derived heart rate variability (HRV) measurement using real-time algorithms. Data from 29 children and 13 adults undergoing general anesthesia were analyzed. We compared the RSA power derived from electrocardiography (ECG) with PPG at the reference RR derived from capnography. The power of the PPG was significantly higher than that of the ECG (182.42 ± 36.75 dB vs. 162.30 ± 43.66 dB). Further, the mean RR error for PPG was lower than ECG. Both PPG and ECG RR estimation techniques were more powerful and reliable in cases of spontaneous ventilation than when pressure controlled ventilation was used. The analysis of cases containing artifacts in the PPG revealed a significant increase in RR error, a trend that was less pronounced for controlled ventilation. These results indicate that the estimation of RR from the sub-optimally sampled PPG signal is possible and more reliable than from the ECG.

Pulse rate variability compared with heart rate variability in children with and without sleep disordered breathing

“…This decrease could be related to the RSA components or originated from the low sampling frequency of PPG signal. The RSA components (high frequency activity) might be more pronounced in the PPG signal [15] and accordingly, the LF/HF index of PRV may reduce. On the other hand, the low sampling frequency of ECG signal induces the bias and uncertainty in the estimation of HF and LF/HF parameters [16].…”

“…Furthermore the PPG signal recorded by the pulse oximeter can be used as an alternative signal for estimating respiratory rate [15] , heart rate and heart rate variability [8], [9].In this study, we assessed the accuracy of PRV as an estimate of HRV in children with and without sleep disordered breathing.…”

Bayesian fusion of physiological measurements using a signal quality extension

“…The Capnobase dataset (Karlen et al 2010) was collected during elective surgery and routine anaesthesia of 59 children (median age: 9, range: 1-17 years) and 35 adults (median age: 52, range: 26-76 years). Photoplethysmogram (PPG) recordings and reference capnometry data were collected at a sampling frequency of 300 Hz.…”

Cerebral Oximetry Versus Pulse Photoplethysmography to Monitor Respiration Rate

“…Direct methods to measure respiratory rate, such as spirometry or capnometry, may result obtrusive and/or impractical [2]. Therefore, methods of extracting respiratory information from commonly used noninvasive physiological signals have been developed, most of them based on Respiratory Sinus Arrhytmia (RSA) [2]. This avoids the use of additional equipment and may simplify many medical scenarios.…”

“…Indeed, respiratory rate is an essential vital sign for diagnosing serious illnesses like sleep apnea or respiratory insufficiency, or even an important predictor of cardiac arrest [1]. Direct methods to measure respiratory rate, such as spirometry or capnometry, may result obtrusive and/or impractical [2]. Therefore, methods of extracting respiratory information from commonly used noninvasive physiological signals have been developed, most of them based on Respiratory Sinus Arrhytmia (RSA) [2].…”