Exercise, Speaking and Breathing at Rest: a Comparison of Aerosol Mass Emission
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ABSTRACT:
ORGANISM(S): Homo sapiens (human)
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PROVIDER: S-BSST691 | biostudies-other |
REPOSITORIES: biostudies-other
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Project description: Not available
| S-BSST754 | biostudies-other
Project description:BackgroundThe coronavirus disease-19 (COVID-19) pandemic led to the prohibition of group-based exercise and the cancellation of sporting events. Evaluation of respiratory aerosol emissions is necessary to quantify exercise-related transmission risk and inform mitigation strategies.MethodsAerosol mass emission rates are calculated from concurrent aerosol and ventilation data, enabling absolute comparison. An aerodynamic particle sizer (0.54-20 μm diameter) samples exhalate from within a cardiopulmonary exercise testing mask, at rest, while speaking and during cycle ergometer-based exercise. Exercise challenge testing is performed to replicate typical gym-based exercise and very vigorous exercise, as determined by a preceding maximally exhaustive exercise test.ResultsWe present data from 25 healthy participants (13 males, 12 females; 36.4 years). The size of aerosol particles generated at rest and during exercise is similar (unimodal ~0.57-0.71 µm), whereas vocalization also generated aerosol particles of larger size (i.e. was bimodal ~0.69 and ~1.74 µm). The aerosol mass emission rate during speaking (0.092 ng s-1; minute ventilation (VE) 15.1 L min-1) and vigorous exercise (0.207 ng s-1, p = 0.726; VE 62.6 L min-1) is similar, but lower than during very vigorous exercise (0.682 ng s-1, p < 0.001; VE 113.6 L min-1).ConclusionsVocalisation drives greater aerosol mass emission rates, compared to breathing at rest. Aerosol mass emission rates in exercise rise with intensity. Aerosol mass emission rates during vigorous exercise are no different from speaking at a conversational level. Mitigation strategies for airborne pathogens for non-exercise-based social interactions incorporating vocalisation, may be suitable for the majority of exercise settings. However, the use of facemasks when exercising may be less effective, given the smaller size of particles produced.
| S-EPMC9053213 | biostudies-literature
Project description:Since the outbreak of the COVID-19 pandemic, singing activities for children and young people have been strictly regulated with far-reaching consequences for music education in schools and ensemble and choir singing in some places. This is also due to the fact, that there has been no reliable data available on aerosol emissions from adolescents speaking, singing, and shouting. By utilizing a laser particle counter in cleanroom conditions we show, that adolescents emit fewer aerosol particles during singing than what has been known so far for adults. In our data, the emission rates ranged from 16 P/s to 267 P/s for speaking, 141 P/s to 1240 P/s for singing, and 683 P/s to 4332 P/s for shouting. The data advocate an adaptation of existing risk management strategies and rules of conduct for groups of singing adolescents, like gatherings in an educational context, e.g. singing lessons or choir rehearsals.
| S-EPMC7875408 | biostudies-literature
Project description: Not available
| S-BSST671 | biostudies-other
Project description:Many airborne pathogens such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are transmitted indoors via aerosol particles. During exercise, pulmonary ventilation can increase over 10-fold, and therefore, exercisers will exhale a greater volume of aerosol-containing air. However, we currently do not know how exercise affects the concentration of aerosol particles in exhaled air and the overall emission of aerosol particles. Consequently, we developed a method to measure in parallel the concentration of aerosol particles in expired air, pulmonary ventilation, and aerosol particle emission at rest and during a graded exercise test to exhaustion. We used this method to test eight women and eight men in a descriptive study. We found that the aerosol particle concentration in expired air increased significantly from 56 ± 53 particles/liter at rest to 633 ± 422 particles/liter at maximal intensity. Aerosol particle emission per subject increased significantly by a factor of 132 from 580 ± 489 particles/min at rest to a super emission of 76,200 ± 48,000 particles/min during maximal exercise. There were no sex differences in aerosol particle emission, but endurance-training subjects emitted significantly more aerosol particles during maximal exercise than untrained subjects. Overall, aerosol particle emission increased moderately up to an exercise intensity of ∼2 W/kg and exponentially thereafter. Together, these data might partly explain superspreader events especially during high-intensity group exercise indoors and suggest that strong infection prevention measures are needed especially during exercise at an intensity that exceeds ∼2 W/kg. Investigations of influencing factors like airway and whole-body hydration status during exercise on aerosol particle generation are needed.
| S-EPMC9295808 | biostudies-literature
Project description:Pathogens such as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), influenza, and rhinoviruses are transmitted by airborne aerosol respiratory particles that are exhaled by infectious subjects. We have previously reported that the emission of aerosol particles increases on average 132-fold from rest to maximal endurance exercise. The aims of this study are to first measure aerosol particle emission during an isokinetic resistance exercise at 80% of the maximal voluntary contraction until exhaustion, second to compare aerosol particle emission during a typical spinning class session versus a three-set resistance training session. Finally, we then used this data to calculate the risk of infection during endurance and resistance exercise sessions with different mitigation strategies. During a set of isokinetic resistance exercise, aerosol particle emission increased 10-fold from 5,400 ± 1,200 particles/min at rest to 59,000 ± 69,900 particles/min during a set of resistance exercise. We found that aerosol particle emission per minute is on average 4.9-times lower during a resistance training session than during a spinning class. Using this data, we determined that the simulated infection risk increase during an endurance exercise session was sixfold higher than during a resistance exercise session when assuming one infected participant in the class. Collectively, this data helps to select mitigation measures for indoor resistance and endurance exercise classes at times where the risk of aerosol-transmitted infectious disease with severe outcomes is high.
| S-EPMC9992860 | biostudies-literature
Project description:In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress. Data from healthy volunteers (n = 15) for cine and real-time free-breathing CMR at rest and under exercise stress were analyzed retrospectively. Exercise stress was performed using an ergometer in the supine position. Segmentations of two deep learning methods, a commercially available technique (comDL) and an openly available network (nnU-Net), were compared to a reference model created via the manual correction of segmentations obtained with comDL. Segmentations of left ventricular endocardium (LV), left ventricular myocardium (MYO), and right ventricle (RV) are compared for both end-systolic and end-diastolic phases and analyzed with Dice's coefficient. The volumetric analysis includes the cardiac function parameters LV end-diastolic volume (EDV), LV end-systolic volume (ESV), and LV ejection fraction (EF), evaluated with respect to both absolute and relative differences. For cine CMR, nnU-Net and comDL achieve Dice's coefficients above 0.95 for LV and 0.9 for MYO, and RV. For real-time CMR, the accuracy of nnU-Net exceeds that of comDL overall. For real-time CMR at rest, nnU-Net achieves Dice's coefficients of 0.94 for LV, 0.89 for MYO, and 0.90 for RV and the mean absolute differences between nnU-Net and the reference are 2.9 mL for EDV, 3.5 mL for ESV, and 2.6% for EF. For real-time CMR under exercise stress, nnU-Net achieves Dice's coefficients of 0.92 for LV, 0.85 for MYO, and 0.83 for RV and the mean absolute differences between nnU-Net and reference are 11.4 mL for EDV, 2.9 mL for ESV, and 3.6% for EF. Deep learning methods designed or trained for cine CMR segmentation can perform well on real-time CMR. For real-time free-breathing CMR at rest, the performance of deep learning methods is comparable to inter-observer variability in cine CMR and is usable for fully automatic segmentation. For real-time CMR under exercise stress, the performance of nnU-Net could promise a higher degree of automation in the future.
| S-EPMC10866998 | biostudies-literature
Project description:The aim of this study is to compare the accuracy of Airgo™, a non-invasive wearable device that records breath, with respect to a gold standard. In 21 healthy subjects (10 males, 11 females), four parameters were recorded for four min at rest and in different positions simultaneously by Airgo™ and SensorMedics 2900 metabolic cart. Then, a cardio-pulmonary exercise test was performed using the Erg 800S cycle ergometer in order to test Airgo™'s accuracy during physical effort. The results reveal that the relative error median percentage of respiratory rate was of 0% for all positions at rest and for different exercise intensities, with interquartile ranges between 3.5 (standing position) and 22.4 (low-intensity exercise) breaths per minute. During exercise, normalized amplitude and ventilation relative error medians highlighted the presence of an error proportional to the volume to be estimated. For increasing intensity levels of exercise, Airgo™'s estimate tended to underestimate the values of the gold standard instrument. In conclusion, the Airgo™ device provides good accuracy and precision in the estimate of respiratory rate (especially at rest), an acceptable estimate of tidal volume and minute ventilation at rest and an underestimation for increasing volumes.
| S-EPMC7412454 | biostudies-literature
Project description:Musculoskeletal loss in actual or simulated microgravity occurs at a high rate. Bed rest studies are a reliable ground-based spaceflight analogue that allow for direct comparison of intervention and control participants. The aim of this review was to investigate the impact of exercise compared to no intervention on bone mineral density (BMD) and muscle cross-sectional area (muscle CSA) in bed rest studies relative to other terrestrial models. Eligible bed rest studies with healthy participants had an intervention arm with an exercise countermeasure and a control arm. A search strategy was implemented for MEDLINE. After screening, eight studies were identified for inclusion. Interventions included resistive exercise (RE), resistive vibration exercise (RVE), flywheel resistive exercise, treadmill exercise with lower body negative pressure (LBNP) and a zero-gravity locomotion simulator (ZLS). Lower limb skeletal sites had the most significant BMD losses, particularly at the hip which reduced in density by 4.59% (p?<?0.05) and the tibial epiphysis by 6% (p?<?0.05). Exercise attenuated bone loss at the hip and distal tibia compared to controls (p?<?0.05). Muscle CSA changes indicated that the calf and quadriceps were most affected by bed rest. Exercise interventions significantly attenuated loss of muscle mass. ZLS, LBNP treadmill and RE significantly attenuated bone and muscle loss at the hip compared to baseline and controls. Despite exercise intervention, high rates of bone loss were still observed. Future studies should consider adding bisphosphonates and pharmacological/nutrition-based interventions for consideration of longer-duration missions. These findings correlate to terrestrial bed rest settings, for example, stroke or spinal-injury patients.
| S-EPMC6506471 | biostudies-literature
Project description:Delivery of medications to preterm neonates receiving non-invasive ventilation (NIV) represents one of the most challenging scenarios for aerosol medicine. This challenge is highlighted by the undersized anatomy and the complex (patho)physiological characteristics of the lungs in such infants. Key physiological restraints include low lung volumes, low compliance, and irregular respiratory rates, which significantly reduce lung deposition. Such factors are inherent to premature birth and thus can be regarded to as the intrinsic factors that affect lung deposition. However, there are a number of extrinsic factors that also impact lung deposition: such factors include the choice of aerosol generator and its configuration within the ventilation circuit, the drug formulation, the aerosol particle size distribution, the choice of NIV type, and the patient interface between the delivery system and the patient. Together, these extrinsic factors provide an opportunity to optimize the lung deposition of therapeutic aerosols and, ultimately, the efficacy of the therapy.In this review, we first provide a comprehensive characterization of both the intrinsic and extrinsic factors affecting lung deposition in premature infants, followed by a revision of the clinical attempts to deliver therapeutic aerosols to premature neonates during NIV, which are almost exclusively related to the non-invasive delivery of surfactant aerosols. In this review, we provide clues to the interpretation of existing experimental and clinical data on neonatal aerosol delivery and we also describe a frame of measurable variables and available tools, including in vitro and in vivo models, that should be considered when developing a drug for inhalation in this important but under-served patient population.
| S-EPMC7908012 | biostudies-literature