Inter-breath Interval Research Articles

Breathing pattern alteration from weanling to old age in male Sprague-Dawley rats

Respiratory patterns were investigated in male Sprague-Dawley rats throughout their lifespan, from weanling (1 month) to old age (24 months), under natural conditions. Both inter-breath interval (IBI) and respiratory volume (RV) were examined. Sample entropy suggested increasing irregularity in IBI but decreasing irregularity in RV until 12 months. According to detrended fluctuation analysis, alpha exponent of the IBI showed a bimodal pattern around the value 0.7. From 1–15 months, the alpha exponent for RV generally decreased to the value 0.5, but it increased again as the animals neared the end of their lifespan. Cross-sample entropy revealed increasing synchronization between IBI and RV until 12 months, then plateauing. Many measures demonstrated a transition around 12 months, potentially reflecting maturation of respiratory control mechanisms. The findings characterize complex dynamics of respiratory patterns across the rat lifespan, providing a normative foundation to identify deviations indicative of dysfunction or disease.

Investigating the effects of underwater noise from two vessels on the behaviour of short-finned pilot whales

Multiple whale-watching vessels may operate around cetaceans at any one time, and targeted animals may experience underwater noise effects. We hypothesised that the cumulative noise of two vessels with low source levels (SLs) will elicit lower behavioural disturbance in short-finned pilot whales (Globicephala macrorhynchus) compared to a single vessel with a higher SL. We measured the behaviour of whales during 26 controls (stationary vessel >300 m) and 44 treatments off Tenerife (Canary Islands, Spain). Treatments consisted of vessel approaches mimicking whale-watch scenarios (distance ∼60 m, speed 1.5 kn). Approaches with two simultaneous vessels, with maximum cumulative mid and low-frequency (0.2–110 kHz) weighted source levels (SLsMF-LF) 137–143 dB, did not affect mother-calf pairs’ resting, nursing, diving, respiration rate or inter-breath interval. However, a louder single vessel approach with twin petrol engines at SLsMF-LF 139–151 dB significantly decreased the proportion of time resting for the mother. The results suggest that if a single or two vessels are present, if the cumulative SL is < 143 dB, the behavioural disturbance on the whales will be negligible. By examining noise effects from multiple vessels on the behaviour of pilot whales, the importance of incorporating a noise threshold into whale-watching guidelines was emphasised.

Breathing patterns and associated cardiovascular changes in intermittently breathing animals: (Partially) correcting a semantic quagmire.

Many animal species do not breathe in a continuous, rhythmic fashion, but rather display a variety of breathing patterns characterized by prolonged periods between breaths (inter-breath intervals), during which the heart continues to beat. Examples of intermittent breathing abound across the animal kingdom, from crustaceans to cetaceans. With respect to human physiology, intermittent breathing-also termed 'periodic' or 'episodic' breathing-is associated with a variety of pathologies. Cardiovascular phenomena associated with intermittent breathing in diving species have been termed 'diving bradycardia', 'submersion bradycardia', 'immersion bradycardia', 'ventilation tachycardia', 'respiratory sinus arrhythmia' and so forth. An examination across the literature of terminology applied to these physiological phenomena indicates, unfortunately, no attempt at standardization. This might be viewed as an esoteric semantic problem except for the fact that many of the terms variously used by different authors carry with them implicit or explicit suggestions of underlying physiological mechanisms and even human-associated pathologies. In this article, we review several phenomena associated with diving and intermittent breathing, indicate the semantic issues arising from the use of each term, and make recommendations for best practice when applying specific terms to particular cardiorespiratory patterns. Ultimately, we emphasize that the biology-not the semantics-is what is important, but also stress that confusion surrounding underlying mechanisms can be avoided by more careful attention to terms describing physiological changes during intermittent breathing and diving.

Cervical spinal cord hemisection impacts sigh and the respiratory reset in male rats.

Cervical spinal cord injury impacts ventilatory and non-ventilatory functions of the diaphragm muscle (DIAm) and contributes to clinical morbidity and mortality in the afflicted population. Periodically, integrated brainstem neural circuit activity drives the DIAm to generate a markedly augmented effort or sigh-which plays an important role in preventing atelectasis and thus maintaining lung function. Across species, the general pattern of DIAm efforts during a normal sigh is variable in amplitude and the extent of post-sigh "apnea" (i.e., the post-sigh inter-breath interval). This post-sigh inter-breath interval acts as a respiratory reset, following the interruption of regular respiratory rhythm by sigh. We examined the impact of upper cervical (C2 ) spinal cord hemisection (C2 SH) on the transdiaphragmatic pressure (Pdi ) generated during sighs and the post-sigh respiratory reset in rats. Sighs were identified in Pdi traces by their characteristic biphasic pattern. We found that C2 SH results in a reduction of Pdi during both eupnea and sighs, and a decrease in the immediate post-sigh breath interval. These results are consistent with partial removal of descending excitatory synaptic inputs to phrenic motor neurons that results from C2 SH. Following cervical spinal cord injury, a reduction in the amplitude of Pdi during sighs may compromise the maintenance of normal lung function.

The effect of vibrotactile stimulation on hypoxia-induced irregular breathing and apnea in preterm rabbits.

Manual tactile stimulation is used to counteract apnea in preterm infants, but it is unknown when this intervention should be applied. We compared an anticipatory to a reactive approach using vibrotactile stimulation to prevent hypoxia induced apneas. Preterm rabbit kittens were prematurely delivered and randomized to either group. All kittens breathed spontaneously with a positive airway pressure of 8 cmH2O while they were imaged using phase contrast X-ray. Irregular breathing (IB) was induced using gradual hypoxia. The anticipatory group received stimulation at the onset of IB and the reactive group if IB transitioned into apnea. Breathing rate (BR), heart rate (HR) and functional residual capacity (FRC) were compared. Anticipatory stimulation significantly reduced apnea incidence and maximum inter-breath intervals and increased BR following IB, compared to reactive stimulation. Recovery in BR but not HR was more likely with anticipatory stimulation, although both BR and HR were significantly higher at 120 s after stimulation onset. FRC values and variability were not different. Anticipated vibrotactile stimulation is more effective in preventing apnea and enhancing breathing when compared to reactive stimulation in preterm rabbits. Stimulation timing is likely to be a key factor in reducing the incidence and duration of apnea. Anticipated vibrotactile stimulation can prevent apnea and stimulate breathing effort in preterm rabbits. Anticipated vibrotactile stimulation increases the likelihood of breathing rate recovery following hypoxia induced irregular breathing, when compared to reactive stimulation. Automated stimulation in combination with predictive algorithms may improve the treatment of apnea in preterm infants.

RespirAnalyzer: an R package for analyzing data from continuous monitoring of respiratory signals.

The analysis of data obtained from continuous monitoring of respiratory signals (CMRS) holds significant importance in improving patient care, optimizing sports performance, and advancing scientific understanding in the field of respiratory health. The R package RespirAnalyzer provides an analytic tool specifically for feature extraction, fractal and complexity analysis for CMRS data. The package covers a wide and comprehensive range of data analysis methods including obtaining inter-breath intervals (IBI) series, plotting time series, obtaining summary statistics of IBI series, conducting power spectral density, multifractal detrended fluctuation analysis (MFDFA) and multiscale sample entropy analysis, fitting the MFDFA results with the extended binomial multifractal model, displaying results using various plots, etc. This package has been developed from our work in directly analyzing CMRS data and is anticipated to assist fellow researchers in computing the related features of their CMRS data, enabling them to delve into the clinical significance inherent in these features. The package for Windows is available from both Comprehensive R Archive Network (CRAN): https://cran.r-project.org/web/packages/RespirAnalyzer/index.html and GitHub: https://github.com/dongxinzheng/RespirAnalyzer.

Bradycardia May Decrease Cardiorespiratory Coupling in Preterm Infants.

Bradycardia, frequently observed in preterm infants, presents significant risks due to the immaturity of their autonomic nervous system (ANS) and respiratory systems. These infants may face cardiorespiratory events, leading to severe complications like hypoxemia and neurodevelopmental disorders. Although neonatal care has advanced, the influence of bradycardia on cardiorespiratory coupling (CRC) remains elusive. This exploratory study delves into CRC in preterm infants, emphasizing disparities between events with and without bradycardia. Using the Preterm Infant Cardio-Respiratory Signals (PICS) database, we analyzed interbeat (R-R) and inter-breath intervals (IBI) from 10 preterm infants. The time series were segmented into bradycardic (B) and non-bradycardic (NB) segments. Employing information theory measures, we quantified the irregularity of cardiac and respiratory time series. Notably, B segments had significantly lower entropy values for R-R and IBI than NB segments, while mutual information was higher in NB segments. This could imply a reduction in the complexity of respiratory and cardiac dynamics during bradycardic events, potentially indicating weaker CRC. Building on these insights, this research highlights the distinctive physiological characteristics of preterm infants and underscores the potential of emerging non-invasive diagnostic tools.

Cardiorespiratory coupling in the bottlenose dolphin (Tursiops truncatus).

Introduction: The bottlenose dolphin (Tursiops truncatus) is an intermittent breather, where the breath begins with an exhalation followed by inhalation and an extended inter-breath interval ranging from 10 to 40s. Breathing has been shown to alter both the instantaneous heart rate (if H) and stroke volume (iSV) in the bottlenose dolphin, with a transitory ventilatory tachycardia following the breath, and an exponential decrease to a stable if H around 40 beats • min-1 during the inter-breath period. As the total breath duration in the dolphin is around 1s, it is not possible to assess the contribution of exhalation and inhalation to these changes in cardiac function during normal breathing. Methods: In the current study, we evaluated the if H response by separating expiration and inspiration of a breath, which allowed us to distinguish their respective contribution to the changes in if H. We studied 3 individual male bottlenose dolphins trained to hold their breath between the different respiratory phases (expiration and inhalation). Results: Our data show that inspiration causes an increase in if H, while expiration appears to result in a decrease in if H. Discussion: These data provide improved understanding of the cardiorespiratory coupling in dolphins, and show how both exhalation and inhalation alters if H.

Interictal respiratory variability predicts severity of hypoxemia after generalized convulsive seizures.

Severe respiratory dysfunction induced by generalized convulsive seizures (GCS) is now thought to be a common mechanism for sudden unexpected death in epilepsy (SUDEP). In a mouse model of seizure-induced death, increased interictal respiratory variability was reported in mice that later died of respiratory arrest after GCS. We studied respiratory variability in epilepsy patients as a predictive tool for severity of postictal hypoxemia, a potential biomarker for SUDEP risk. We then explored the relationship between respiratory variability and central CO2 drive, measured by the hypercapnic ventilatory response (HCVR). We reviewed clinical, video-electroencephalography, and respiratory (belts, airflow, pulse oximeter, and HCVR) data of epilepsy patients. Mean, SD, and coefficient of variation (CV) of interbreath interval (IBI) were calculated. Primary outcomes were: (1) nadir of capillary oxygen saturation (SpO2 ) and (2) duration of oxygen desaturation. Poincaré plots of IBI were created. Covariates were evaluated in univariate models, then, based on Akaike information criteria (AIC), multivariate regression models were created. Of 66 GCS recorded in 131 subjects, 30 had interpretable respiratory data. In the multivariate model with the lowest AIC value, duration of epilepsy was a significant predictor of duration of oxygen desaturation. Duration of tonic phase and CV of IBI during the third postictal minute correlated with SpO2 nadir, whereas CV of IBI during non-rapid eye movement sleep had a negative correlation. Poincaré plots showed that long-term variability was significantly greater in subjects with ≥200 s of postictal oxygen desaturation after GCS compared to those with <200 s desaturation. Finally, HCVR slope showed a negative correlation with measures of respiratory variability. These results indicate that interictal respiratory variability predicts severity of postictal oxygen desaturation, suggesting its utility as a potential biomarker. They also suggest that interictal respiratory control may be abnormal in some patients with epilepsy.

The protective effect of inhaled corticosteroid on lung inflammation and breathing pattern complexity in a rat model of asthma

Asthma is a heterogeneous disease in which the complexity of the breathing pattern reduces as the severity of the disease increases. Since the pathophysiological basis of reduced breathing pattern complexity in asthma is unclear, in this study, we investigated the effect of reducing inflammation using an inhaled corticosteroid (fluticasone propionate) on the breathing pattern of a rat model of asthma. Detrended fluctuation analysis, sample entropy, and cross-sample entropy analysis of both inter-breath interval and respiratory volume time series showed that early treatment with inhaled corticosteroids not only diminishes lung inflammation and airway hyper-responsiveness, but also has a protective effect against the reduction of breathing pattern complexity due to asthma. However, late treatment had a partial effect on asthma-induced respiratory pattern changes. Since inflammation is a key factor in shifting breathing dynamics away from normal fluctuations, these findings further emphasize the importance of early treatment of asthma with corticosteroids.

Cue rates and surfacing characteristics of sei whales (Balaenoptera borealis) in the Falkland Islands

The cue rate (CR: blows per whale per hour), surfacing characteristics and swim speeds of sei whales (Balaenoptera borealis) were quantified fromfocal follows carried out at Berkeley Sound (East Falkland) between January and May 2017 and off the west coast of West Falkland betweenFebruary and April 2018. In Berkeley Sound, focal follows were conducted from Cape Pembroke lighthouse and from a small boat. In West Falklandall focal follows were conducted from a yacht. Thirty-seven focal follows of sei whale individuals or groups (2–5 individuals) were analysed toproduce CRs ranging from 21.99 to 46.73, with a mean of 31.46 (SD = 5.12). There was no significant difference in the CRs observed from shorevs. boat platforms or between the two study areas. Maximum submergence times exceeding 13min were recorded from both individuals and groups.The durations of 51 whale surfacing events had a mean of 6.4s (SD = 1.7). The average swim speed during boat-based sei whale focal follows was5.7kmh−1. The inter-breath intervals (IBIs) recorded from 13 solitary individuals ranged from 77.2 to 180.1s, with an overall mean of 118.6s (SD= 137.6). A combined approach incorporating IBI parameters and sequence pattern was used to classify 270 IBIs into surface dives (mean = 37.2s),intermediate dives (mean = 113.7s) and true dives (mean = 332.6s). Individuals showed marked variation in dive pattern, with some exhibitingclear cycles of true dives interspersed with surface bouts while others routinely took intermediate-duration dives interspersed by single surfacings.Sei whales in Berkeley Sound exhibited a higher proportion of surface dives than whales in West Falkland, and those surface dives were of lowermean and median IBI. Individual sei whales had surface bouts comprising a mean of 3.8 blows and a mean IBI of 33.4s. These are the firstquantifiable data on surfacing-dive patterns and CRs for sei whales in the Falkland Islands and across the wider range of the species. The data haveconservation and management relevance, including addressing availability bias for line transect and cue count abundance estimates, incorporationinto vessel strike modelling, and understanding foraging behaviour.

Changes in Forcecardiography Heartbeat Morphology Induced by Cardio-Respiratory Interactions

The cardiac function is influenced by respiration. In particular, various parameters such as cardiac time intervals and the stroke volume are modulated by respiratory activity. It has long been recognized that cardio-respiratory interactions modify the morphology of cardio-mechanical signals, e.g., phonocardiogram, seismocardiogram (SCG), and ballistocardiogram. Forcecardiography (FCG) records the weak forces induced on the chest wall by the mechanical activity of the heart and lungs and relies on specific force sensors that are capable of monitoring respiration, infrasonic cardiac vibrations, and heart sounds, all simultaneously from a single site on the chest. This study addressed the changes in FCG heartbeat morphology caused by respiration. Two respiratory-modulated parameters were considered, namely the left ventricular ejection time (LVET) and a morphological similarity index (MSi) between heartbeats. The time trends of these parameters were extracted from FCG signals and further analyzed to evaluate their consistency within the respiratory cycle in order to assess their relationship with the breathing activity. The respiratory acts were localized in the time trends of the LVET and MSi and compared with a reference respiratory signal by computing the sensitivity and positive predictive value (PPV). In addition, the agreement between the inter-breath intervals estimated from the LVET and MSi and those estimated from the reference respiratory signal was assessed via linear regression and Bland-Altman analyses. The results of this study clearly showed a tight relationship between the respiratory activity and the considered respiratory-modulated parameters. Both the LVET and MSi exhibited cyclic time trends that remarkably matched the reference respiratory signal. In addition, they achieved a very high sensitivity and PPV (LVET: 94.7% and 95.7%, respectively; MSi: 99.3% and 95.3%, respectively). The linear regression analysis reported almost unit slopes for both the LVET (R2 = 0.86) and MSi (R2 = 0.97); the Bland-Altman analysis reported a non-significant bias for both the LVET and MSi as well as limits of agreement of ±1.68 s and ±0.771 s, respectively. In summary, the results obtained were substantially in line with previous findings on SCG signals, adding to the evidence that FCG and SCG signals share a similar information content.

Respiratory-Induced Amplitude Modulation of Forcecardiography Signals.

Forcecardiography (FCG) is a novel technique that records the weak forces induced on the chest wall by cardio-respiratory activity, by using specific force sensors. FCG sensors feature a wide frequency band, which allows us to capture respiration, heart wall motion, heart valves opening and closing (similar to the Seismocardiogram, SCG) and heart sounds, all simultaneously from a single contact point on the chest. As a result, the raw FCG sensors signals exhibit a large component related to the respiratory activity, referred to as a Forcerespirogram (FRG), with a much smaller, superimposed component related to the cardiac activity (the actual FCG) that contains both infrasonic vibrations, referred to as LF-FCG and HF-FCG, and heart sounds. Although respiration can be readily monitored by extracting the very low-frequency component of the raw FCG signal (FRG), it has been observed that the respiratory activity also influences other FCG components, particularly causing amplitude modulations (AM). This preliminary study aimed to assess the consistency of the amplitude modulations of the LF-FCG and HF-FCG signals within the respiratory cycle. A retrospective analysis was performed on the FCG signals acquired in a previous study on six healthy subjects at rest, during quiet breathing. To this aim, the AM of LF-FCG and HF-FCG were first extracted via a linear envelope (LE) operation, consisting of rectification followed by low-pass filtering; then, the inspiratory peaks were located both in the LE of LF-FCG and HF-FCG, and in the reference respiratory signal (FRG). Finally, the inter-breath intervals were extracted from the obtained inspiratory peaks, and further analyzed via statistical analyses. The AM of HF-FCG exhibited higher consistency within the respiratory cycle, as compared to the LF-FCG. Indeed, the inspiratory peaks were recognized with a sensitivity and positive predictive value (PPV) in excess of 99% in the LE of HF-FCG, and with a sensitivity and PPV of 96.7% and 92.6%, respectively, in the LE of LF-FCG. In addition, the inter-breath intervals estimated from the HF-FCG scored a higher R2 value (0.95 vs. 0.86) and lower limits of agreement (± 0.710 s vs. ±1.34 s) as compared to LF-FCG, by considering those extracted from the FRG as the reference. The obtained results are consistent with those observed in previous studies on SCG. A possible explanation of these results was discussed. However, the preliminary results obtained in this study must be confirmed on a larger cohort of subjects and in different experimental conditions.

Respiratory pattern complexity in newly-diagnosed asthmatic patients

BackgroundThe intensity of respiratory symptoms and expiratory airflow limitations in asthma fluctuate over time. Some studies have reported variable complexity of the respiratory patterns in asthmatic patients. Thus, we conducted a novel study to assess the correlation between asthma severity and breathing pattern dynamics in newly-diagnosed asthmatic patients. MethodsA total of 20 newly-diagnosed asthmatic patients (7 male, 13 female) and 20 healthy cases (11 male, 9 female) were included. The respiratory patterns of all participants and the asthma severity for asthmatic patients were measured using a spirometer (before and after a bronchodilator exposure) and airflow recorder, respectively. The peak-to-peak intervals and the amplitude of peaks were considered as the inter-breath interval (IBI) and lung volume (LV) series. The Detrended Fluctuation Analysis (DFA), Sample Entropy (SampEn), Multi-scale Entropy (MSE), short-term (SD1) and long-term (SD2) variability, and IBI and LV Cross-Sample Entropy of the respiratory pattern dynamics were calculated using MATLAB (Mathwork, USA). ResultsAsthma patients showed notable increase in the average of sample entropy in both IBI and LV parameters (p = 0.025 and p = 0.018, respectively) and also decreased synchronization between IBI and LV (p = 0.042). The multi-scale sample entropy of both IBI and LV was significantly higher in asthmatic patients (p < 0.05). Furthermore, SD1 and SD2 were higher in the patients with asthma (p < 0.05). Significant correlations were detected between spirometric (forced expiratory flow (FEF) change, pre FEF, pre forced expiratory volume in one second (FEV1) / forced vital capacity (FVC), FVC change) and respiratory pattern (mean-IBI, mean-LV, mean-respiratory rate (RR), coefficient of variation (CV)-IBI, CV-LV, cross-sample entropy) parameters (p < 0.05). Furthermore, we identified a negative correlation between CV of IBI and asthma severity (r = −0.52, p = 0.021). ConclusionHere, we took a novel approach and observed increased irregularity (more complexity) in the breathing pattern of patients newly-diagnosed with asthma. Remarkable correlations were detected between breathing complexity markers and spirometric indices along with disease severity in asthmatic patients. Thus, our data suggests respiratory pattern indices could be utilized as an indicator of asthma and its severity. However, more clinical data are required to support this conclusion.

New method to measure interbreath intervals in infants for the assessment of apnoea and respiration

BackgroundRespiratory disorders, including apnoea, are common in preterm infants due to their immature respiratory control compared with term-born infants. However, our inability to accurately measure respiratory rate in hospitalised infants...

A Novel Broadband Forcecardiography Sensor for Simultaneous Monitoring of Respiration, Infrasonic Cardiac Vibrations and Heart Sounds.

The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High-Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients.

Paternal preconception exposure to chronic morphine alters respiratory pattern in response to morphine in male offspring

The clinical use of opioids is restricted by its deleterious impacts on respiratory system. Gaining a better understanding of an individual’s susceptibility to adverse opioid effects is important to recognize patients at risk. Ancestral drug addiction has been shown to be associated with alterations in drug responsiveness in the progenies. In the current study, we sought to evaluate the effects of preconception paternal morphine consumption on respiratory parameters in response to acute morphine in male offspring during adulthood, using plethysmography technique. Male Wistar rats administered 10 days of increasing doses of morphine in the period of adolescence. Thereafter, following a 30-day abstinence time, adult males copulated with naïve females. The adult male offspring were examined for breathing response to morphine.Our results indicated that sires who introduce chronic morphine during adolescence leads to increase irregularity of respiratory pattern and asynchronization between inter-breath interval (IBI) and respiratory volume (RV) time series in male offspring. These findings provide evidence that chronic morphine use by parents even before pregnancy can affect respiratory pattern and response to morphine in the offspring.

PPG-Based Respiratory Rate Monitoring Using Hybrid Vote-Aggregate Fusion Technique.

In this work, we present a low-complexity photoplethysmography-based respiratory rate monitoring (PPG-RRM) algorithm that achieves high accuracy through a novel fusion method. The proposed technique extracts three respiratory-induced variation signals, namely the maximum slope, the amplitude, and the frequency, from the PPG signal. The variation signals undergo time domain peak detection to identify the inter-breath intervals and produce three different instantaneous respiratory rate (IRR) estimates. The IRR estimates are combined through a hybrid vote-aggregate fusion scheme to generate the final RR estimate. We utilize the publicly available Capnobase data-sets [1] that contain both PPG and capnography signals to evaluate our RR monitoring algorithm. Compared to the reference capnography IRR, the proposed PPG-RRM algorithm achieves a mean absolute error (MAE) of 1.44 breaths per minute (bpm), a mean error (ME) of 0.70±2.54 bpm, a root mean square error (RMSE) of 2.63 bpm, and a Pearson correlation coefficient r = 0.95, p < .001.

Predicting apneic events in preterm infants using cardio-respiratory and movement features

Background and objectivePreterm neonates are prone to episodes of apnea, bradycardia and hypoxia (ABH) that can lead to neurological morbidities or even death. There is broad interest in developing methods for real-time prediction of ABH events to inform interventions that prevent or reduce their incidence and severity. Using advances in machine learning methods, this study develops an algorithm to predict ABH events. MethodsFollowing previous studies showing that respiratory instabilities are closely associated with bouts of movement, we present a modeling framework that can predict ABH events using both movement and cardio-respiratory features derived from routine clinical recordings. In 10 preterm infants, movement onsets and durations were estimated with a wavelet-based algorithm that quantified artifactual distortions of the photoplethysmogram signal. For prediction, cardio-respiratory features were created from time-delayed correlations of inter-beat and inter-breath intervals with past values; movement features were derived from time-delayed correlations with inter-breath intervals. Gaussian Mixture Models and Logistic Regression were used to develop predictive models of apneic events. Performance of the models was evaluated with ROC curves. ResultsPerformance of the prediction framework (mean AUC) was 0.77 ± 0.04 for 66 ABH events on training data from 7 infants. When grouped by the severity of the associated bradycardia during the ABH event, the framework was able to predict 83% and 75% of the most severe episodes in the 7-infant training set and 3-infant test set, respectively. Notably, inclusion of movement features significantly improved the predictions compared with modeling with only cardio-respiratory signals. ConclusionsOur findings suggest that recordings of movement provide important information for predicting ABH events in preterm infants, and can inform preemptive interventions designed to reduce the incidence and severity of ABH events.

Respiration Monitoring via Forcecardiography Sensors

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R2 = 0.98) vs. 0.98, 0.11 s (R2 = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.