Respiratory Rate Monitoring Research Articles

A New Ka-Band Doppler Radar in Robust and Precise Cardiopulmonary Remote Sensing

In this paper, a new Ka-band Doppler radar with an ability to remotely monitor respiration rate, heartbeat rate (HR), and heart rate variability (HRV) is presented. Exploiting the advantage of high sensitivity of Ka-band radar in sensing of chest-wall movement, we make more accurate reconstruction of cardiopulmonary activities from low-quality received signal. The advantage of using Ka-band radar is obtained by paying a penalty, which is harmonic interferences that make measuring of cardiopulmonary details infeasible in lots of real scenarios. In this paper, by using a more complete model of return signal, a new routine is introduced for the robust detection of breathing and HR that extremely alleviates the problems associated with harmonic interferences. Besides, a more suitable model is proposed, which can cover time-variability cardiorespiratory features. Taking advantage of this model and based on the unconditional orthonormal representation of band-limited signals, a filter with time-varying coefficients is proposed to extract HRV. This extraction is done without resorting to tracking HR trace that makes it more precise and robust than the conventional approach. The indicated filter enables us to suggest a novel approach to remove random body motion effects. By experimental data, the applicability of the new radar for a wide range of real world scenarios is investigated, and its advantages beside conventional approaches are proved practically in different aspects.

Development of solution processible organic-inorganic hybrid materials with core-shell framework for humidity monitoring

Abstract A novel organic-inorganic hybrid material with the core-shell framework was prepared by modifying the poly(vinylsulfonic acid, sodium salt) (PSS) on vinyl functionalized silica nanoparticles (VSNs) via the free radical polymerization. SNs with different contents of PSS were prepared and the structures were carefully characterized. The hybrid material could enhance the durability of PSS under high humidity environment. Meanwhile, the SNs skeleton provides interstitial channels in the PSS@SNs films, which are available for water molecules transport. The PSS coated SNs (PSS@SNs) films were formed by drop-coating and their sensing properties were investigated. The impedance of the optimal humidity sensor changed more than four orders of magnitude over the relative humidity range of 33–95%, with good linearity under semi-logarithm scale (R2 = 0.950) and a small humidity hysteresis of 2% RH. The obtained sensor also showed rapid response to humidity change (the response and recovery time were 2 and 65 s, respectively). Finally, the resultant sensor was explored for respiratory rate monitoring.

Impact of absence of critical respiratory rate change on oxygen desaturation following tracheal extubation after general anaesthesia: a propensity score-matched analysis.

It has been suggested that oxygen desaturation may be paradoxically related to the absence of an abnormal respiratory rate (RR) during acoustic respiratory rate (RRa) monitoring in a postoperative setting. We retrospectively compared the incidence of desaruration in patients without an abnormal RR with that in patients with an abnormal RR using propensity scorer matching. We also explored the factors contributing to oxygen desaturation without an RR monitoring alert. We used ≤ 8 h postoperative data of the first 935 patients. Outcomes of patients with and without critical RR changes (RR > 30 or < 8 beats per min for > 2 min) (critical RR change vs. noncritical RR change) were first compared according to oxygen desaturation levels (SpO₂< 90% for > 10 s). Multivariate analysis was used to determine oxygen desaturation-associated explanatory factors. Propensity score matching yielded 259 patients without critical RR changes and 259 patients with critical RR changes, respectively. Oxygen desaturation rates were higher in patients without critical RR changes [noncritical RR change vs. critical RR change: 39/220 (15.1%) vs. 16/243 (6.2%)]. An odds ratio and 95% CI for the noncritical RR change was 2.56 (1.38-4.55, P = 0.002). A critical change in the RRa was not observed in 576 patients; of these, oxygen desaturation was observed in 76 (13.2%) patients. Surgery duration (OR, 1.018 per 10 min increase; 95% CI, 1.002 to 1.035) was independently associated with oxygen desaturation without critical RR change. Postoperative oxygen desaturation paradoxically occurred more frequently in patients without critical RR changes, whose RR was monitored by the RRa under oxygen therapy. The duration of surgery may explain the possibility of postoperative oxygen desaturation without an RRa device alert.

Monitoring of nocturnal central sleep apnea in Heart failure patients using noncontact respiratory differences.

Monitoring of respiration patterns allows the early detection of various breathing disorders and may better identify those at risk for adverse acute outcomes in a variety of clinical settings. In this paper, we report on the use of SleepMinder (SM), a bedside non-contact Doppler-based biomotion recording sensor, to monitor remotely the nocturnal respiration patterns of 50 patients with systolic Heart failure (HF) while undergoing a lab based Polysomnography (PSG) test. A new respiration rate (RR) monitoring algorithm was developed based on the collected overnight radar signals. Two schemes of RR scoring were utilized: respiratory rate count (RRC) and instantaneous respiratory rates (IRR). Analysis of SM vs. PSG revealed that the mean/median IRR scored by SM is highly correlated with that scored on the nasal flow/effort signals from the corresponding PSG studies on all patients, with a significant correlation coefficient of 0.98 (average absolute difference of 0.31 breaths/min), and 0.97 (p<;0.01, average absolute difference of 0.38 breaths/min) for the median and mean of RR respectively. Our experimental results also show that the difference between the RR estimations from IRR and RRC schemes can be utilized to identify central sleep apnea (CSA)/Cheyne-Stokes respiration (CSR) sections without additional apnea detection modules. As a result, with a sensitivity and specificity of 71% and 88% respectively, and an accuracy of 86%, our CSA/CSR screener, plugged with our RR estimation, can play an important role in the remote management of HF patients.

A wearable textile for respiratory monitoring: Feasibility assessment and analysis of sensors position on system response.

The interest on wearable textiles to monitor vital signs is growing in the research field and clinical scenario related to the increasing demands of long-term monitoring. Despite several smart textile-based solutions have been proposed for assessing the respiratory status, only a limited number of devices allow the respiratory monitoring in a harsh environment or in different positions of the human body. In this paper, we investigated the performances of a smart textile for respiratory rate monitoring characterized by 12 fiber optic sensors (i.e., fiber Bragg grating) placed on specific landmarks for compartmental analysis of the chest wall movements during quiet breathing. We focused on the analysis of the influence of sensor position on both peak-to-peak amplitude of sensors output and accuracy of respiratory rate measurements. This analysis was performed on two participants, who wore the textile in two positions (i.e., standing and supine). Bland-Altman analysis on respiratory rate showed promising results (better than 0.3 breaths per minute). Referring to the peak-to-peak output amplitude, the abdomen compartment showed the highest excursions in both the enrolled participants and positions. Our findings open up new approaches to design and develop smart textile for respiratory rate monitoring.

Real Time Respiration Rate Measurement Using Temperature Sensor

Respiration rate is a vital indicator of an individual's health, and therefore it is monitored when performing clinical evaluations. There are many different approaches for respiration monitoring, but usually, they can be classed as contact or non-contact. Respiration Rate is one of the important signs that need regular monitoring among unhealthy individuals. There are a variety of medical devices developed to observe human health condition among them respiration rate monitor is one. The Respiration rate monitor is a device that measures the individual’s respiration rate non-invasively. The objective of the planned work is to design and develop an affordable Respiration rate monitor for clinical applications. The respiration rate of the patient is measured with the assistance of temperature sensor that measures even the slightest change in the temperature while an individual is inhaling or exhalation. And according to the reading obtained the alert message will be sent to the patient’s mobile phone via GSM module that is connected to the device.

Automated Real-Time Processing of Single Lead Electrocardiogram for Simultaneous Heart Rate and Respiratory Rate Monitoring

In this article, the design and development of a real-time heart rate (HR) and respiratory rate (RR) monitoring device is reported. The proposed device is designed to impose minimum data acquisition hazards on the subject. In standard bedside monitors, HR and RR are derived from electrocardiogram (ECG) and respiration signals, respectively, and different electrodes are required for capturing the 12-lead ECG and respiration via a chest belt, which is cumbersome for patients and healthcare providers. Respiration signal has an impact on ECG due to anatomical proximity of the heart and lung, and ECG is modulated by respiration, a phenomenon known as respiratory sinus arrhythmia (RSA). In the proposed method, the ECG signal is acquired using clip electrodes at the wrists and the respiration signal is extracted from the ECG using an Arduino Uno microcontroller-based real-time processing of ECG. RR is then derived from ECG-derived respiration (EDR). The prototype is tested on healthy subjects and compared to measurements taken using a standard MP45 data acquisition device associated with a Biopac Student Lab (BSL). A mean percentage error of 5.54 ± 8.48% was observed under normal breathing conditions and an error of −3.41 ± 3.27% was observed for a single subject tested under a variety of breathing conditions, such as resting, stair-climbing, and paced breathing. The proposed algorithm can also be used in combination with standard ECG monitoring systems to measure HR and RR, without any data acquisition hazard to the subject.

Journal of Clinical Monitoring and Computing 2016 end of year summary: respiration.

This paper reviews 16 papers or commentaries published in Journal of Clinical Monitoring and Computing in 2016, within the field of respiration. Papers were published covering peri- and post-operative monitoring of respiratory rate, perioperative monitoring of CO2, modeling of oxygen gas exchange, and techniques for respiratory monitoring.

Linshom thermodynamic sensor is a reliable alternative to capnography for monitoring respiratory rate.

Monitoring ventilation accurately is a technically challenging, yet indispensable aspect of patient care in the intra- and post-procedural settings. A new prototypical device known as the Linshom Respiratory Monitoring Device (LRMD) has been recently designed to non-invasively, inexpensively, and portably measure respiratory rate. The purpose of this study was to measure the accuracy and variability of LRMD measurements of respiratory rate relative to the measurement of capnography. In this prospective study, participants were enrolled and individually fitted with a face mask monitored by the LRMD and capnography. With a baseline oxygen flow rate and digital metronome to pace their respiratory rate, the participants were instructed to breathe at 10 breaths per minute (bpm) for 3min, 20bpm for 3min, 30bpm for 3min, 0bpm for 30s, and resume regular breathing for 30s. Both sensors were connected to a computer for continuous temperature and carbon dioxide waveform recordings. The data were then retrospectively analyzed. Twenty-six healthy volunteers, mean (range) age 27.8 (23-37) and mean (range) BMI 23.1 (18.8-29.2) kg/m2 were recruited. There were 15 males (57.7%) and 11 females (42.3%). After excluding 3 subjects for technical reasons, 13,800s of breathing and 4,140 expiratory breaths were recorded. Throughout the protocol, the average standard deviation (SD) for the LRMD and capnography was 1.11 and 1.81bpm, respectively. The overall mean bias (±2SD) between LRMD and capnography was -0.33 (±0.1.56) bpm. At the lowest and intermediate breathing rates reflective of hypoventilation and normal ventilation, the LRMD variance was 0.55 and 1.23 respectively, compared to capnography with 5.54 and 7.47, respectively. At higher breathing rates indicative of hyperventilation, the variance of the test device was 4.52, still less than that of capnography at 5.73. This study demonstrated a promising correlation between the LRMD and capnography for use as a respiratory rate monitor. The LRMD technology may be a significant addition to monitoring vital signs because it offers a minimally intrusive opportunity to detect respiratory rate and apnea, without expensive or complex anesthetic equipment, before the need for life-saving resuscitation arises.

Cardiorespiratory instability in monitored step-down unit patients: using cluster analysis to identify patterns of change.

Cardiorespiratory instability (CRI) in monitored step-down unit (SDU) patients has a variety of etiologies, and likely manifests in patterns of vital signs (VS) changes. We explored use of clustering techniques to identify patterns in the initial CRI epoch (CRI1; first exceedances of VS beyond stability thresholds after SDU admission) of unstable patients, and inter-cluster differences in admission characteristics and outcomes. Continuous noninvasive monitoring of heart rate (HR), respiratory rate (RR), and pulse oximetry (SpO2) were sampled at 1/20Hz. We identified CRI1 in 165 patients, employed hierarchical and k-means clustering, tested several clustering solutions, used 10-fold cross validation to establish the best solution and assessed inter-cluster differences in admission characteristics and outcomes. Three clusters (C) were derived: C1) normal/high HR and RR, normal SpO2 (n = 30); C2) normal HR and RR, low SpO2 (n = 103); and C3) low/normal HR, low RR and normal SpO2 (n = 32). Clusters were significantly different based on age (p < 0.001; older patients in C2), number of comorbidities (p = 0.008; more C2 patients had ≥ 2) and hospital length of stay (p = 0.006; C1 patients stayed longer). There were no between-cluster differences in SDU length of stay, or mortality. Three different clusters of VS presentations for CRI1 were identified. Clusters varied on age, number of comorbidities and hospital length of stay. Future study is needed to determine if there are common physiologic underpinnings of VS clusters which might inform clinical decision-making when CRI first manifests.

Influences of environmental noise level and respiration rate on the accuracy of acoustic respiration rate monitoring.

We tested the hypothesis that the environmental noise generated by a forced-air warming system reduces the monitoring accuracy of acoustic respiration rate (RRa). Noise levels were adjusted to 45-55, 56-65, 66-75, and 76-85 dB. Healthy participants breathed at set respiration rates (RRset) of 6, 12, and 30/min. Under each noise level at each RRset, the respiration rates by manual counting (RRm) and RRa were recorded. Any appearance of the alarm display on the RRa monitor was also recorded. Each RRm of all participants agreed with each RRset at each noise level. At 45-55 dB noise, the RRa of 13, 17, and 17 participants agreed with RRset of 6, 12, and 30/min, respectively. The RRa of 14, 17, and 16 participants at 56-65 dB noise, agreed with RRset of 6, 12, and 30/min, respectively. At 66-75 dB noise, the RRa of 9, 15, and 16 participants agreed with RRset of 6, 12, and 30/min, respectively. The RRa of one, nine, and nine participants at 76-85 dB noise agreed with RRset of 6, 12, and 30/min, respectively, which was significantly less than the other noise levels (P < 0.05). Overall, 72.9% of alarm displays highlighted incorrect values of RRa. In a noisy situation involving the operation of a forced-air warming system, the acoustic respiration monitoring should be used carefully especially in patients with a low respiration rate.

Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions

BackgroundCurrently, many imaging photoplethysmography (IPPG) researches have reported non-contact measurements of physiological parameters, such as heart rate (HR), respiratory rate (RR), etc. However, it is accepted that only HR measurement has been mature for applications, and other estimations are relatively incapable for reliable applications. Thus, it is worth keeping on persistent studies. Besides, there are some issues commonly involved in these approaches need to be explored further. For example, motion artifact attenuation, an intractable problem, which is being attempted to be resolved by sophisticated video tracking and detection algorithms.MethodsThis paper proposed a blind source separation-based method that could synchronously measure RR and HR in non-contact way. A dual region of interest on facial video image was selected to yield 6-channels Red/Green/Blue signals. By applying Second-Order Blind Identification algorithm to those signals generated above, we obtained 6-channels outputs that contain blood volume pulse (BVP) and respiratory motion artifact. We defined this motion artifact as respiratory signal (RS). For the automatic selections of the RS and BVP among these outputs, we devised a kurtosis-based identification strategy, which guarantees the dynamic RR and HR monitoring available.ResultsThe experimental results indicated that, the estimation by the proposed method has an impressive performance compared with the measurement of the commercial medical sensors.ConclusionsThe proposed method achieved dynamic measurement of RR and HR, and the extension and revision of it may have the potentials for more physiological signs detection, such as heart rate variability, eye blinking, nose wrinkling, yawn, as well as other muscular movements. Thus, it might provide a promising approach for IPPG-based applications such as emotion computation and fatigue detection, etc.

A Retrospective Analysis of Oxygen Desaturation during Acoustic Respiratory Rate Monitoring in Non-ICU Patients following Tracheal Extubation after General Anesthesia.

Purpose. Acoustic respiratory rate (RRa) monitoring provides an accurate estimation of the respiratory rate (RR). We investigated the incidence of oxygen desaturation under RRa monitoring in a postoperative setting and identified its related factors. Methods. This study was a retrospective chart review of postoperative patients outside an intensive care unit setting. Using the data collected during the first 8 h postoperatively, patients were divided into oxygen desaturated (SpO2 < 90% for >10 s) and nondesaturated groups under oxygen administration. Multivariate analysis was used to determine oxygen desaturation-associated explanatory factors. Results. Oxygen desaturation was detected in 102 of 935 patients (10.9%). % vital capacity [odds ratio (OR), 0.885 per 10% increase; 95% confidence interval (CI), 0.790 to 0.992], coexisting chronic obstructive pulmonary disease (OR, 2.195; 95% CI, 1.088 to 4.428), and absence of a critical RRa change (RR > 30 or <8 beats/min for >2 min) (OR, 1.972; 95% CI, 1.226 to 3.172) were independently associated with oxygen desaturation. Conclusion. Postoperative oxygen desaturation was observed in more than 10% of the patients whose RR was monitored by RRa under oxygen therapy. It is more likely to occur in patients with impaired pulmonary function or morbid pulmonary status and can also occur in the absence of abnormal RR.

Dexmedetomidine as the Component of Multimodal Analgesia in Vitreoretinal Surgery

The study of efficacy and safety of using of the dexmedetomidine related to the group of central agonists of α2-adrenoceptor as the component of multimodal analgesia in vitreoretinal surgery was carried out. Objectives. For this purpose 2 groups of patients after vitreoretinal surgical interventions were examined prospectively. Materials and methods. Evaluation of anesthesia adequacy was performed using the following parameters: depth of sedation level and consciousness depression, which were estimated by means of Richmond Agitation-Sedation Scale. The degree of collaboration with physician was also evaluated. Monitoring of arterial pressure, heart rate, respiratory rate and SpO2 were conducted. Assessment of pain syndrome was performed with use of verbal descriptive scale of pain intraoperatively and at early postoperative period. The perioperative consumption of fentanyl was taken into consideration. Conclusions. Analysis of the results allowed to conclude that the usage of dexmedetomidine reduced perioperative consumption of opioid analgesics and severity of hemodynamic responses, it helped to maintain consciousness at a comfortable level both for patients and operators.

Serum Interleukin-6 Level after Cyclooxygenase-2 Inhibitor Treatment in Moderate Traumatic Brain Injury

The most clinical scoring of traumatic brain injury patient is Glasgow Coma Scale (GCS) score. Lower GCS score higher IL-6 level and higher morbidity and mortality. Neuroinflammation is one mechanism of secondary brain injury. Selective cyclooxygenase (sCOX-2) inhibitors are drugs commonly used in treatment of postoperative pain but also possess an anti-inflammatory effect. The aim of this study is to determine the role of sCOX-2 inhibitors as inhibitors of inflammatory processes in patients with head injury measured by IL-6. This is a double blind randomized controlled study involving patients with moderate head injuries who underwent surgery in Dr. Hasan Sadikin Hospital Bandung Indonesia since December 2013 until December 2015. After obtaining approval of research ethics committees from School of Medicine Universitas Padjadjaran/Dr. Hasan Sadikin Hospital, samples were divided randomly into 5 groups: control group, COX2-group I (given sCOX-2 inhibitor ones), COX2-group II (given sCOX-2 inhibitor twice), COX2-group III (given sCOX-2 inhibitor thrice), and COX2- group IV (given sCOX-2 inhibitor four times), each group containing 6 patients. All patients received standard therapy as recommended by Traumatic Brain Foundation in 2007 as well as monitoring of GCS, blood pressure, pulse rate, respiratory rate, oxygen saturation, temperature and blood sugar in pre and postoperative stages. The data was analyzed using statistical tests Paired Samples T-test and One Way Anova, p-value <0.05 as statistical significant. Result shows that data pretest IL-6, data posttest and IL-6 changes of both groups is not significance (p>0.05). In treatment group (Cox-2 I, Cox-2 II, Cox-2 III dan Cox-2 IV) overall are decrease of IL-6=10%, which is p 0.083 0.05). The study is concluded that sCOX-2 inhibitor has a brain protective effect by lowering IL-6 level in patients with moderate head injury.

Novel signal processing method for vital sign monitoring using FMCW radar

Abstract Purpose To prove that frequency modulated continuous wave (FMCW) radar can be applied for continuous and timely monitoring of vital signs for multi-human targets. Methods The chest-wall periodic vibration information resulting from respiration and heartbeat is modulated in the reflected electromagnetic wave of radar from the surface of human bodies or tissue boundaries. The range and vibration information of multi-targets is acquired by a Fourier transform and demodulation processing. To further extract the respiration and heartbeat signals from the mixed vibration phase signal when the respiration signal has several significant harmonics and variant frequencies, a novel recovery and separation method based on a double parameter least mean square (LMS) filter is developed. Results The FMCW wide-band radar is capable of multiple vital signal monitoring and subject localization under a low signal to noise ratio (SNR). Compared with the bandpass filtering (BPF) method and wavelet transform (WT) method, the proposed method based on a double parameter LMS filter can obtain more accurate respiration and heartbeat signals. Conclusions The FMCW wide-band radar is a reliable, robust, and harmless tool for continuous and timely monitoring of cardiac and respiratory rates for multi-human targets, which has a potential to be applied in wards or home healthcare.

Sensitive and Fast Humidity Sensor Based on A Redox Conducting Supramolecular Ionic Material for Respiration Monitoring.

Real-time monitoring of respiratory rate (RR) is highly important for human health, clinical diagnosis, and fundamental scientific research. Exhaled humidity-based RR monitoring has recently attracted increased attention because of its accuracy and portability. Here, we report a new design of an exhaled humidity sensor for the real-time monitoring of the RR based on a synthetic redox conducting supramolecular ionic material (SIM). The humidity-dependent conducting SIM is prepared by ionic self-assembly in aqueous solutions of electroactive 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 1,10-bis(3-methylimidazolium-1-yl) decane (C10(mim)2). By taking full advantage of the high hygroscopicity and water stability arising from the ionic and hydrophobic interactions between two building blocks (i.e., ABTS and C10(mim)2), the SIM-based humidity sensor exhibits both high sensitivity (less than 0.1% relative humidity) and fast response time (∼37 ms). These excellent properties allow this humidity sensor to noninvasively monitor the RRs of not only humans but also rats that have a much faster RR and much smaller tidal volume than humans. Moreover, this sensor could also be efficiently used for the real-time monitoring of the recovery process of rats from anesthesia.

A method of detection of respiration rate on Android using UWB Impulse Radar

Monitoring respiration rate is important because it can help to detect and prevent abnormal respiratory rates that can lead to cardiac arrest and chronic obstructive pulmonary disease. Nowadays, most medical measurement and monitoring devices are either invasive or wired but people are hesitant to attach physiological sensors to their body. In this study, we investigated whether real-time medical measurement of breathing using Novelda’s Ultra-Wideband Impulse Radio (IR-UWB)–which does not need to be attached to the human body and is also non-invasive–is possible on Android. Experimental results obtained were found to be comparable to those of a commercial healthcare device.

Fast and Robust Real-Time Estimation of Respiratory Rate from Photoplethysmography.

Respiratory rate (RR) is a useful vital sign that can not only provide auxiliary information on physiological changes within the human body, but also indicate early symptoms of various diseases. Recently, methods for the estimation of RR from photoplethysmography (PPG) have attracted increased interest, because PPG can be readily recorded using wearable sensors such as smart watches and smart bands. In the present study, we propose a new method for the fast and robust real-time estimation of RR using an adaptive infinite impulse response (IIR) notch filter, which has not yet been applied to the PPG-based estimation of RR. In our offline simulation study, the performance of the proposed method was compared to that of recently developed RR estimation methods called an adaptive lattice-type RR estimator and a Smart Fusion. The results of the simulation study show that the proposed method could not only estimate RR more quickly and more accurately than the conventional methods, but also is most suitable for online RR monitoring systems, as it does not use any overlapping moving windows that require increased computational costs. In order to demonstrate the practical applicability of the proposed method, an online RR estimation system was implemented.

A pulse transit time based fusion method for the noninvasive and continuous monitoring of respiratory rate.

The purpose of this study was to investigate whether pulse transit time (PTT) can be used for continuous monitoring of respiratory rate (RR). We derived PTT from the electrocardiogram and photoplethysmogram obtained from 42 recordings of CapnoBase, a publicly available benchmark data set for validating respiratory related measurements. The number of breaths in a minute (RR#) was estimated from the heart rate interval (HRI), pulse rate interval (PRI), and from PTT. In addition, to improve the estimation reliability, we investigated a fusion of the three HRI, PRI and PTT derived estimations. The root mean squared error (RSME) and a Bland-Altman plot were calculated using RR from capnography as reference. Finally, the proposed method was compared against the CapnoBase Smart Fusion RR benchmark estimation which estimates RR with three parameters extracted from the PPG signal alone. Thirty-seven recordings showed sufficient signal quality to estimate RR from PTT. The fused RR (RMSE 1.76 breaths/min) was more accurate than the estimations from PTT (RMSE 2.63 breaths/min), HRI (RMSE 1.96 breaths/min), and PRI (RMSE 2.73 breaths/min) alone. The proposed method also outperformed the CapnoBase benchmark (RMSE 3.08 breaths/min) algorithm. This study demonstrates that PTT is a valuable noninvasive parameter from which RR can be estimated.