Breathing Rate Research Articles

The Effect of Breathing Exercises on Respiratory Condition After Coronary Artery Bypass Surgery

Background: Respiratory complications are prevalent in coronary artery bypass graft (CABG) surgery. Breathing exercises are efficient and cost-effective techniques to eliminate this problem. Objectives: This study investigated the effect of simultaneous breathing exercises on patients' respiratory condition after CABG surgery. Methods: In a randomized controlled clinical trial, 52 CABG candidates were allocated to two intervention and control groups. The control group received routine breathing exercises (incentive spirometry and vibration). Besides routine exercises, the intervention group performed exercises such as pursed-lip breathing, diaphragmatic breathing, incentive spirometry, and effective coughing for three days after the surgery. The incidence of atelectasis, oxygen saturation, lung auscultation, and the patients' satisfaction with the respiratory function was measured and recorded before and after the surgery in both groups. The collected data were analyzed in SPSS v. 22 at a significance level of < 0.05. Results: The patients' mean age was 60.9 ± 9.5 years, and 26 (51%) were male. There was no significant difference between the patients in underlying parameters. None of the patients in the two groups had atelectasis before the surgery. However, four days after the surgery, 40% of the patients in the control group and 23% of those in the intervention group suffered from atelectasis complications. The visual analog scale (VAS) score increased after surgery in the intervention group, although the difference was insignificant. Moreover, the arterial oxygen saturation percentage and breathing rate increased in the intervention group. No significant difference was observed between the two groups regarding crackles at different hours after surgery, although they were relatively less in the intervention group. Conclusions: Breathing exercises, especially combined breathing exercises, improve respiratory function after open heart surgery.

Assessment of physiological responses and milk production in Jersey crossbred cows at different stratum of THI inside the cow barn

Environmental heat stress is one of the restrictive factors for optimum production of dairy cows. Present study was conducted to assess alteration in cardinal physiological responses, heat tolerance indices and milk yield in Jersey crossbred cows at three levels of thermal humidity index (THI), viz. THI-1 (<72), THI-2 (72-80) and THI-3 (>80). THI levels significantly influenced rectal temperature (RT) and respiration rate (RR), but not the pulse rate. With increase in THI level 1 to 3, the RT and RR increased significantly by 0.75°F and 10.70 counts/min during morning and 0.92°F and 12.5 counts/min during afternoon, respectively. The respective enhancement between THI-2 to THI-3 was 0.48°F and 7.06/min in morning and 0.58°F and 7.45/min in afternoon. Among the cardinal physiologicalresponses, breathing rate was the most diurnal variable parameter and it increased by 22-29% from 8:00 am to 2:00 pm with enhancement of stress levels fromTHI-1 to THI-3. Measures of heat tolerance indices revealed that cows were comfortable at THI-1 and discomfort levels were prominent at THI > 80. Low yielders (<10 kg/day) resisted natural heat stress by oriented decline in daily milk yield (DMY) and sustained DMY even at THI >80. In case of high yielders (>10 kg/day) increase in THI level 1 to 2, DMY did not drop significantly; in contrast, with increase of THI-2 to THI-3, the DMY declined. It was concluded that enhanced breathing rate was the most prominent bio-indicator of natural heat stress in Jersey crossbred cows and at THI>80 production decline due to natural heat stress was nonsignificant in low yielders, whereas highly significant in high yielders (more than 21%). It was recommended that atTHI >80, inside of cow shed needs immediate amelioration measures to diminish production losses and high yielders (>10 kg/day) warrant more attention than low yielders during heat stress.

The effects of mechanical versus bag-valve ventilation on gas exchange during cardiopulmonary resuscitation in emergency department patients: A randomized controlled trial (CPR-VENT)

IntroductionEffective ventilation is crucial for successful cardiopulmonary resuscitation (CPR). Previous studies indicate that higher arterial oxygen levels (PaO2) during CPR increase the chances of successful resuscitation. However, the advantages of mechanical ventilators over bag-valve ventilation for achieving optimal PaO2 during CPR remain uncertain. MethodWe conducted a randomized trial involving non-traumatic adult cardiac arrest patients who received CPR in the ED. After intubation, patients were randomly assigned to ventilate with a mechanical ventilator (MV) or bag valve ventilation (BV). In MV group, ventilation settings were: breath rate 10/minute, tidal volume 6–7 ml/kg, inspiratory time 1 second, positive end-expiratory pressure 0 cm water, inspiratory oxygen fraction (FiO2) 100%. The primary outcome was to compare the difference in PaO2 from arterial blood gases (ABG) obtained 4–10 minutes later during CPR between both groups. ResultsSixty patients were randomized (30 in each group). The study population consisted of: 57% male, median age 62 years, 37% received bystander CPR, and 20% had an initial shockable rhythm. Median time from arrest to intubation was 24 minutes. The median PaO2 was not significantly different in the BV compared to MV [36.5 mmHg (14.0–70.0) vs. 29.0 mmHg (15.0–70.0), P = 0.879]. Other ABG parameters and rates of return of spontaneous circulation and survival were not different. ConclusionsIn ED patients with refractory cardiac arrest, arterial oxygen levels during CPR were comparable between patients ventilated with MV and BV. Mechanical ventilation is at least feasible and safe during CPR in intubated cardiac arrest patients.

Comprehensive evaluation of the pharmacological and toxicological effects of γ-valerolactone as compared to γ-hydroxybutyric acid: Insights from in vivo and in silico models

Γ-valerolactone (GVL), marketed online as “Tranquilli-G” and “excellent Valium”, is used as a legal substitute for γ-hydroxybutyric acid (GHB); however, until now, GVL has only been connected to one Drug-Facilitated Sexual Assault (DFSA) case. Moreover, the pharmaco-toxicological effects of GVL are poorly studied. The aim of this study was to investigate the 1) in vivo effects of gavage administration of GVL (100–3000 mg/kg) on neurological (myoclonia, convulsions), sensorimotor (visual, acoustic, and overall tactile) responses, righting reflex, thermoregulation, motor activity (bar, drag, and accelerod test) and cardiorespiratory changes (heart rate, breath rate, oxygen saturation, and pulse distension) in CD-1 male mice and the 2) in silico ADMET profile of GVL in comparison to GHB and the open active form γ-hydroxyvaleric acid (GHV). The present study demonstrates that GVL inhibits, in a dose-dependent manner, sensorimotor and motor responses and induces cardiorespiratory depression (at a dose of 3000 mg/kg) in mice. The determination of the ED50 in sensorimotor and motor responses revealed that GVL is about 4–5 times less potent than GHB. In silico prediction of ADMET profiles revealed toxicokinetic similarities between GHB and GHV, and differences with GVL. These results suggest that GVL could be used as a substitute for GHB and should be added to forensic toxicology screenings.

Nasal High-Flow (NHF) Improves Ventilation in Patients with Interstitial Lung Disease (ILD)-A Physiological Study.

Acute hypercapnic respiratory failure has a poor prognosis in patients with interstitial lung disease (ILD). Recent data demonstrated a positive effect of nasal high-flow (NHF) in patients with acute hypoxemic respiratory failure. Preliminary data also show benefits in several hypercapnic chronic lung diseases. The aim of this study was to characterize flow-dependent changes in mean airway pressure, breathing volumes, and breathing frequency and decreases in PCO2. Mean airway pressure was measured in the nasopharyngeal space. To evaluate breathing volumes, a polysomnographic device was used (16 patients). All subjects received 20, 30, 40, and 50 L/min and-to illustrate the effects-nCPAP and nBiPAP. Capillary blood gas analyses were performed in 25 hypercapnic ILD subjects before and 5 h after the use of NHF. Additionally, comfort and dyspnea during the use of NHF were surveyed. NHF resulted in a small flow-dependent increase in mean airway pressure. Tidal volume was unchanged and breathing rate decreased. The calculated minute volume decreased by 20 and 30 L/min NHF breathing. In spite of this fact, hypercapnia decreased at a flow rate of 24 L/min. Additionally, an improvement in dyspnea was observed. NHF leads to a reduction in paCO2. This is most likely achieved by a washout of the respiratory tract and a reduction in functional dead space. NHF enhances the effectiveness of breathing in ILD patients by the reduction in respiratory rate. In summary, NHF works as an effective ventilatory support device in hypercapnic ILD patients.

Shallow kinetics induced by a metronome (SKIM): A novel contactless respiratory motion management.

As an alternative to conventional compression amidst the COVID-19 pandemic, we developed a contactless motion management strategy. By increasing the patient's breathing rate to induce shallow breathing with the aid of a metronome, our hypothesis is that the motion magnitude of the target may be minimized without physical contact or compression. Fourteen lung stereotactic body radiation therapy (SBRT) patients treated under fast shallow-breathing (FSB) were selected for inclusion in this retrospective study. Our proposed method is called shallow kinetics induced by a metronome (SKIM). We induce FSB by setting the beats-per-minute (BPM) high (typically in the range of 50-60). This corresponded to a patient breathing rate of 25-30 (breathing) cycles per minute. The magnitude of target motion in 3D under SKIM was evaluated using 4DCT datasets. Comparison with free breathing (FB) 4DCT was also made for a subset for which FB data available. The overall effectiveness of SKIM was evaluated with 18 targets (14 patients). Direct comparison with FB was performed with 12 targets (10patients). The vector norm mean±SD value of motion magnitude under SKIM for 18 targets was 8.2±4.1mm. The mean±SD metronome BPM was 54.9±4.0 in this group. The vector norm means±SD values of target motion for FB and SKIM in the 12 target sub-group were 14.6±8.5mm and 9.3±3.7mm, respectively. The mean±SD metronome BPM for this sub-group was 56.3±2.5. Compared with FB, SKIM can significantly reduce respiratory motion magnitude of thoracic targets. The difference in maximum motion reduction in the overall vector norm, S-I, and A-P directions was significant (p=0.033, 0.042, 0.011). Our proposed method can be an excellent practical alternative to conventional compression due to its flexibility and ease of implementation.

Abstract P342: Acute Nasal Breathing Lowers Blood Pressure And Increases Parasympathetic Contributions To Heart Rate Variability In Young Adults

Introduction: Interest is growing in how breathing pace, pattern, and training (e.g., device-assisted or -resisted breathing) affect prognostic cardiovascular variables (e.g., blood pressure (BP)). Nasal breathing increases bronchodilation via airway epithelium nitric oxide production, increases diaphragmatic movement, and reduces accessory inspiratory muscle recruitment. Despite these changes, the effect of nasal compared with oral breathing (i.e., breathing route) on prognostic cardiovascular variables is unclear. Hypothesis: We hypothesized that nasal compared with oral breathing would acutely lower BP and improve heart rate variability (HRV) metrics. Methods: We tested 20 young healthy adults in this study (13 Female/7 Male; age: 18 [1] years, median [IQR]; body mass index: 23 ± 2 kg•m -2 , screening systolic / diastolic BP 116 ± 12 / 67 ± 7 mmHg mean ± SD). Participants self-selected their breathing rate during a five-minute ‘run-in’ period. Using a metronome, their breathing rate was fixed during two subsequent (random order) five-minute resting periods with nasal and oral breathing while we measured brachial BP and HRV metrics via ECG. We compared data between conditions using a Wilcoxon signed-rank paired test (data presented as median [IQR]) or using paired, two-tailed t-tests (data presented as mean ± SD). We set the significance to p <0.05. Results: Nasal breathing lowered mean (nasal: 84 ± 7 vs. oral: 86 ± 5 mmHg, p =0.006, Cohen’s d =0.70) and diastolic (nasal: 68 [8] vs. oral: 72 [5] mmHg, p <0.001, Rank-biserial correlation=0.89), but not systolic (nasal: 116 ± 11 vs. oral: 117 ± 9 mmHg, p =0.48, Cohen’s d =0.16) BP. Nasal breathing also raised the High-Frequency contribution to HRV (nasal: 59 ± 19 vs. oral: 52 ± 21 %, p =0.04, Cohen’s d =0.50) and lowered the Low-Frequency to High-Frequency ratio (nasal: 0.9 ± 0.8 vs. oral: 1.2 ± 0.9, p =0.04, Cohen’s d =0.49), suggesting a greater parasympathetic contribution to HRV. There were no differences between conditions for heart rate ( p= 0.90) or time-domain HRV metrics ( ps ≥0.07; e.g., the standard deviation of NN intervals). Conclusion: These data suggest that nasal compared with oral breathing acutely lowers mean and diastolic BP as well as potentially increases parasympathetic contributions to HRV.

Factors Associated with Sedentary Behavior and Physical Activity Among People Living in Saudi Arabia - A Cross-Sectional Study.

A poor physical activity and sedentary behavior is common among individuals which can be detrimental to one's health. Furthermore, sedentary behavior is associated with metabolic disorders. Therefore, this study explored factors associated with sedentary behavior and physical activity among individuals in capital region of Saudi Arabia. A cross-sectional web-based study was conducted over a period of 3 months in 2023 using prevalidated questionnaires, which address the sedentary behavior and physical activity and its factors. This study included among individuals aged from 19 to 50 years, living in Riyadh. Factors associated with outcome variables were identified using multiple linear regression analysis in SPSS. Of the 833 study participants, 569 (68.3%) and most were males aged between years 31-35 years old. Only 20.6% (n=172) of the activities that induced high levels of breathing or heart rate were vigorous-intensity activities among the respondents. The average number of sitting hours per day was 6.74 (SD=1.577). The regression model's findings showed a significant correlation between mean sitting time and education level (p=0.008), occupation (p=0.001), monthly income (p=0.029), and kind and status of physical activity (p=0.002). Similar to this, there was a significant correlation between age group (p=0.040) and physical activity status (p=0.001) and the amount of time spent engaging in vigorous-intensity activities at work on an average day. The findings of this study confirmed that Saudi adults living in the Riyadh region spent a significant amount of time sedentary, and the most common factors associated with sedentary behavior were education, employment, monthly income, physical activity status, type of physical activity, and reasons for not practicing physical activity. The findings of this study can be used by healthcare providers and those associated with policymaking to improve health outcomes in healthcare settings.

On the thermographic measurement of the respiratory rate

Abstract Respiration is a vital process for normal function at every level of organization of living beings. A simple and noncontact measurement of the respiratory rate certainly offers advantages in many situations compared to classical measurements, e.g., with a respiratory measurement belt. Thus, we started a study for thermographic detection of breathing rate. For this purpose, several subjects were filmed with an infrared (IR) camera and the recordings were subjected to pixel value analysis using MATLAB. By using different regions of interest (ROIs), the pixel values were averaged and mapped graphically. The resulting graphs generally show a periodic breathing process based on the temperature changes within the selected ROIs. To put this pixel value analysis into perspective, control measurements were taken with a BIOPAC-system using a respiratory measurement belt to measure abdominal/thoracic respiration. The two sets of measurements were compared by cross correlation and a moderately strong anti-correlation was demonstrated.

Heart rate modeling and prediction of construction workers based on physical activity using deep learning

Construction projects require long working hours where workers are subjected to intensive tasks such as hard manual labor, heavy weightlifting, and compulsive working postures. Among the physiological metrics, Heart Rate (HR) is reported to be a good indicator of physical stress and workload. HR forecasting models have been used in various areas including cardiopathy research, heart attack warning indicator, and early physical fatigue detection. However, there are no reported studies on HR modeling and forecasting in the construction field. Modeling and forecasting the HR of construction workers using construction field data is of paramount importance due to the direct relationship between activity level and HR. The objective of this study is to (1) analyze the effect of physiological factors including breathing rate, acceleration of torso movements, torso posture, and impulse load on the HR of construction workers, and (2) model and forecast one-minute ahead HR for construction workers based on their physical activity using deep learning algorithms. To this end, physiological metrics of five bridge maintenance workers performing several construction activities were collected. According to the Pearson correlation and entropy based mutual information analysis, time-lagged variables including acceleration of torso movements, torso posture, and impulse load have significant effect on the HR data. The results of deep learning models indicate that Long Short-Term Memory Network (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), and Bidirectional GRU (BiGRU) have similar predictive performance. However, LSTM had the best overall performance in HR prediction with Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) of 5.4, 7.34, and 5.77%, respectively. These models have the potential to facilitate the mitigation of cardiovascular strain and enable proactive prevention of accidents in the construction industry.

Sistem Screening Mandiri Covid-19 Berbasis Internet of Things (IoT)

The increasing need to perform Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) during the COVID-19 pandemic is time-consuming and costly. An IoT-based self-screening system of COVID-19, is expected to be a solution. In this study, instruments were created to monitor SpO2 and heart rate using the MAX30102 sensor, body temperature using the MLX90614 sensor, and breathing rate using a flex sensor as a COVID-19 detection parameter. The measured vital sign results are also transmitted to the website using the Wi-Fi module ESP32. The method used is a decision tree that has two classifications, indicated healthy and indicated COVID-19. Decision tree accuracy is 90% and recall is 100%. Temperature readings have a 98.68% accuracy, SpO2 readings and heartbeats are 98.74% and 98.64%, respectively, and breathing rate per minute readings are 100% accurate. This autonomous COVID-19 screening system can be used as an alternative solution for early detection of COVID-19.

A Computer Vision-Based Respiratory Rate Monitoring and Alarm System

Breathing rate is one of the most important vital signals for monitoring health status and reflecting conditions of dangerous diseases. Previous contactless breath monitoring methods were more convenient than contact methods, but they were not suitable for the actual sleeping environment because of the narrow field of vision (FoV). This study proposed a breathing rate monitoring strategy using a mono camera to track and detect sleep apnea phenomena. Breathing rates were first tracked among consecutive image frames. The human body area was then isolated and magnified using a deep neural network (DNN) model before applying the optical flow algorithm to extract and monitor the up and down changes caused by respiration. The most variated directions of the body feature’s motions were detected based on the Principal Component Analysis (PCA) method. Breathing rate was the number of times the signal amplitude peaks per minute. The comparison between predicted values and manually estimated was used for evaluating the accuracy of the method. The accuracy of our method in various light, position, and distance conditions is 2 breaths/minute (<10%) for children and less than 1 breath/minute (<5%) for adults. The study has two main contributions: (1) monitoring breathing rate at home gives comfortable feelings to patients and caregivers, expanding the potential of applying modern technology to clinics, (2) the study has solved the problem of tracking small movements in videos with relatively large FoV in real-time. Perspectively, we will be employed the method in a home-based respiratory rate monitoring system.

Flexible Fabric Temperature Sensor Based on Vo2/Pedot:Pss with High Performance

Long‐term effective temperature monitoring using a flexible wearable temperature sensor is critical for future health monitoring, noninvasive clinical biomonitoring, disease diagnosis, and so on. Thermistors have the merits of simple structure, ease of preparation and great sensitivity, but the preparation of thermistors with good flexibility is often at the expense of their sensitivity and requirement of high temperature. Herein, a flexible temperature sensor with stability and high sensitivity by spraying VO2/PEDOT:PSS composites on an SBS electrospinning substrate is reported. The sensor exhibits high thermal sensitivity (−2.712%/°C), high precision (85 mK), ultra‐fast response time (1 s) and recovery time (2.5 s), enabling accurate real‐time temperature detection and meeting the need for long‐term temperature monitoring and tracking. As a proof of concept, this sensor is applied to monitor human skin temperature, breathing rate, and temperature recognition, and as a temperature‐based input keyboard, demonstrating its tremendous potential to further develop personalized flexible sensors.

Regulation of vagally-evoked respiratory responses by the lateral parabrachial nucleus in the mouse

Vagal sensory inputs to the brainstem can alter breathing through the modulation of pontomedullary respiratory circuits. In this study, we set out to investigate the localised effects of modulating lateral parabrachial nucleus (LPB) activity on vagally-evoked changes in breathing pattern. In isoflurane-anaesthetised and instrumented mice, electrical stimulation of the vagus nerve (eVNS) produced stimulation frequency-dependent changes in diaphragm electromyograph (dEMG) activity with an evoked tachypnoea and apnoea at low and high stimulation frequencies, respectively. Muscimol microinjections into the LPB significantly attenuated eVNS-evoked respiratory rate responses. Notably, muscimol injections reaching the caudal LPB, previously unrecognised for respiratory modulation, potently modulated eVNS-evoked apnoea, whilst muscimol injections reaching the intermediate LPB selectively modulated the eVNS-evoked tachypnoea. The effects of muscimol on eVNS-evoked breathing rate changes occurred without altering basal eupneic breathing. These results highlight novel roles for the LPB in regulating vagally-evoked respiratory reflexes.

The psychophysiological reactivity to beaches vs. to green and urban environments: insights from a virtual reality experiment

Coastal environments effectively reduce perceived levels of stress. However, little is known about whether coastal environments influence physiological parameters of stress, whether these influences differ from those of urban and green environments, and whether these effects depend on the level of precedent stress. The current study exposed 164 participants (18-65y, 68% female) from the Flemish population to two 16-minute virtual reality exposures (i.e. beach vs. green or urban) via a randomized crossover design, during which the heart rate, high-frequency heart rate variability (HF-HRV), skin conductance responses (SCR), mean arterial pressure (MAP), breathing rate, and upper trapezius muscle tone were monitored. Self-reported measures of stress were also taken. General linear mixed models analyzed for each parameter whether the change over time differed per exposed environment and by the level of stress in the past week (from ‘low’ to ‘moderate’ levels), while controlling for study design and participant related covariates. Results show that beaches caused lower breathing rates than urban environments and lower SCR than green environments. The upper trapezius muscle tone showed complex patterns, and the heart rate, HF-HRV, and MAP did not react differently to the beach than to the urban and green environments. The individuals’ level of stress in the past week did not affect these differences much. Self-reported measures showed that, under moderate stress, beaches decreased the negative mood and perceived stress, whereas green environments did not and urban environments generally had more adverse effects on the negative mood, perceived stress, positive mood, and perceived quality for relaxation. This study demonstrates that beaches slow down breathing and reduce the sympathetic nervous system activity, and highlights the benefits of beaches for health and wellbeing. The results mark the importance of considering diverse physiological pathways of stress and the individuals’ precedent stress.

Role of high flow nasal therapy in Intensive Care Units

Introduction and purpose: High Flow Nasal Therapy is quite new respiratory support method, although recently it became more popular – especially during COVID-19 pandemic. Physiological mechanisms as well as main applications were observed and described in several randomized controlled trias and metaanalisys. The purpose of this review is to present fundamental studies and indicate applications of this method.
 Brief description of the state of knowladge: Breathing mixture with a maximum flow 60l/min needs to be heated and humidified to protect the airways from dryness. Optimal humidity improves mucocilary clearance, reduces inflammation of the airways and energy expenditure, especially in acute respiratory failure. High flow nasal therapy may imrpove the mechanics of breathing also by washout of nasopharyngeal dead space and generating positive airway pressure during exhalation, which keeps airways open and prevents the alveoli from collapsing. High flow therapy can be use in many different applications but at Intensive Care Unit the most important are: acute hypoxemia, during extubation or rest breaks from NIV. It is important to monitor the patient and predict the need for intubation on time. There are physiological states that we shoud focus on: respiratory rate, dyspnea or work of breathing, but it is good to know ROX index which can be helpful to assess the success of the therapy.
 Summary (conlcusions): High flow nasal therapy is a simple and safety respiratory support method that can be applicable at Intensive Care Units. It can lower the intubation numbers and help during NIV rest breaks. High flow nasal therapy is a very promising method for all patients with respiratory failure but it is important to monitor the patient and not delay the intubation.

Effective fall detection and post-fall breath rate tracking using a low-cost CW Doppler radar sensor

Existing low-cost Doppler radar-based fall detection systems encounter challenges due to false alarms and the absence of post-fall health tracking, significantly impacting their accuracy and overall compatibility for fall detection. This paper presents a cost-effective, robust solution for a fall detection system with the post-fall health tracking facility using a 3.18 GHz continuous-wave Doppler radar sensor. The experimental data acquisition is conducted in-house under the guidance of a healthcare expert, involving various activities such as standing, sitting, sleeping, running, walking, falling, sit-to-stand, and stand-to-sit transitions. We propose an algorithm comprising four hierarchical stages, each with specific objectives. Considering the complexity, the model is trained differently for each stage to optimize the classification accuracy. The system architecture is designed to minimize computational costs and power consumption through modular implementation in stages, utilizing low-power equipment and incorporating traditional machine-learning algorithms. Experimental results demonstrate a fall detection accuracy of 93.24% and breath rate measurement error of 2.26%, which is competitive with recent state-of-the-art approaches. Obtained results highlight the effectiveness of the proposed system in addressing the challenges of false alarms and post-fall health tracking while maintaining cost-efficiency and accuracy in fall detection.

Abstract P2002: Variability In The Relationship Between Heart Rate And Automatic Breathing Rate Throughout The Mouse Lifespan

Background: Autonomic neural surveillance maintains a symphonic relationship between heart and breathing rhythms. We have established how heart beat interval variability changes across mouse lifespan (6 months - 30 months) in the presence and absence of double autonomic blockade (Baltimore Longitudinal Study on Aging in Mice, BLSAM; Geroscience 2022, PMID: 35759167). Objective: To determine how the automatic breathing rate (BR) changes with age in the same BLSAM cohort, and whether the BR and Heart Rate (HR) track each other in the presence and absence of double autonomic blockade across the lifespan of individual mice. Methods: The BLSAM cohort consists of 58 mice in which HR and BR were assessed from the EKG (under light anesthesia) at 3-month intervals, beginning at 6 months of age until the end of life (30 months of age). EKG was recorded in the presence and absence double autonomic blockade (i.p injection of atropine, 0.5mg/kg, and propranolol, 1mg/kg). Data were analyzed via a mixed ANOVA. Results: The BR remained stable until approximately 21 months of age, and then became sharply reduced between 21 and 30 months of age (Fig. A). The pattern of HR change over the adult life span was similar to that of BR (Fig. B). Both HR and BR were significantly (p<0.05) reduced in the presence of double autonomic blockade (arrows in figs). The relative magnitude of BR reduction beyond 21 months of age was substantially greater than the relative reduction in HR over this age range, resulting in a marked increase in HR/BR Ratio (Fig. C), which was also significantly impacted by autonomic function. Conclusion: Thus, beginning at approximately the 70% of maximum mice lifespan, the harmony between heart rhythm and breathing rhythm gradually deteriorates.

Measuring Anatomical Distributions of Ventilation and Aerosol Deposition with PET-CT.

In disease, lung function and structure are heterogeneous, and aerosol transport and local deposition vary significantly among parts of the lung. Understanding such heterogeneity is relevant to aerosol medicine and for quantifying mucociliary clearance from different parts of the lung. In this chapter, we describe positron emission tomography (PET) imaging methods to quantitatively assess the deposition of aerosol and ventilation distribution within the lung. The anatomical information from computed tomography (CT) combined with the PET-deposition data allows estimates of airway surface concentration and peripheral tissue dosing in bronchoconstricted asthmatic subjects. A theoretical framework is formulated to quantify the effects of heterogeneous ventilation, uneven aerosol ventilation distribution in bifurcations, and varying escape from individual airways along a path of the airway tree. The framework is applied to imaging data from bronchoconstricted asthmatics to assess the contributions of these factors to the unevenness in lobar deposition. Results from this analysis show that the heterogeneity of ventilation contributes on average to more than one-third of the variability in interlobar deposition. Actual contribution of ventilation in individual lungs was variable and dependent on the breathing rate used by the subject during aerosol inhalation; the highest contribution was in patients breathing slowly. In subjects breathing faster, contribution of ventilation was reduced, with more expanded lobes showing lower deposition per unit ventilation than less expanded ones in these subjects. The lobar change in expansion measured from two static CT scans, which is commonly used as a surrogate for ventilation, did not correlate with aerosol deposition or with PET-measured ventilation. This suggests that dynamic information is needed to provide proper estimates of ventilation for asthmatic subjects. We hope that the enhanced understanding of the causes of heterogeneity in airway and tissue dosing using the tools presented here will help to optimize therapeutic effectiveness of inhalation therapy while minimizing toxicity.

Automatic Life Detection Based on Efficient Features of Ground-Penetrating Rescue Radar Signals.

Good feature engineering is a prerequisite for accurate classification, especially in challenging scenarios such as detecting the breathing of living persons trapped under building rubble using bioradar. Unlike monitoring patients' breathing through the air, the measuring conditions of a rescue bioradar are very complex. The ultimate goal of search and rescue is to determine the presence of a living person, which requires extracting representative features that can distinguish measurements with the presence of a person and without. To address this challenge, we conducted a bioradar test scenario under laboratory conditions and decomposed the radar signal into different range intervals to derive multiple virtual scenes from the real one. We then extracted physical and statistical quantitative features that represent a measurement, aiming to find those features that are robust to the complexity of rescue-radar measuring conditions, including different rubble sites, breathing rates, signal strengths, and short-duration disturbances. To this end, we utilized two methods, Analysis of Variance (ANOVA), and Minimum Redundancy Maximum Relevance (MRMR), to analyze the significance of the extracted features. We then trained the classification model using a linear kernel support vector machine (SVM). As the main result of this work, we identified an optimal feature set of four features based on the feature ranking and the improvement in the classification accuracy of the SVM model. These four features are related to four different physical quantities and independent from different rubble sites.