The tracheal flow field shapes particle transport into the lower airways and thus influences both the spread of inhaled pathogens and the effectiveness of aerosol-based therapies. Identifying how different inhalation routes modify the flow field is therefore crucial for understanding lower-airway disease transmission and for guiding targeted drug delivery. To gain a detailed understanding of the influence of the inhalation route on the flow structures in the human trachea, the flow field in the trachea is investigated in vitro in a non-compliant, refractive-index matched silicone model of the human respiratory tract. The investigations comprise steady inhalation, and oscillatory flow to simulate calm breathing. A realistic breathing pattern is approximated by a sinusoidal waveform for two Reynolds numbers of $Re_{Tr} = [400, 1200]$, based on the bulk velocity at maximum volume flux and the hydraulic diameter of the trachea and two Womersley numbers of $Wo = [3, 4.5]$, representing the oscillation time scales. To capture the inherently three-dimensional and asymmetric nature of the flow field, 3D particle-tracking velocimetry measurements are performed using the Shake-The-Box algori
Inhalation injuries present a challenge in clinical diagnosis and grading due to Conventional grading methods such as the Abbreviated Injury Score (AIS) being subjective and lacking robust correlation with clinical parameters like mechanical ventilation duration and patient mortality. This study introduces a novel deep learning-based diagnosis assistant tool for grading inhalation injuries using bronchoscopy images to overcome subjective variability and enhance consistency in severity assessment. Our approach leverages data augmentation techniques, including graphic transformations, Contrastive Unpaired Translation (CUT), and CycleGAN, to address the scarcity of medical imaging data. We evaluate the classification performance of two deep learning models, GoogLeNet and Vision Transformer (ViT), across a dataset significantly expanded through these augmentation methods. The results demonstrate GoogLeNet combined with CUT as the most effective configuration for grading inhalation injuries through bronchoscopy images and achieves a classification accuracy of 97.8%. The histograms and frequency analysis evaluations reveal variations caused by the augmentation CUT with distribution chang
The air flows in the proximal and distal portions of the human lungs are interconnected: the lower Reynolds number in the deeper generations causes a progressive flow regularization, while mass conservation requires flow rate oscillations to propagate through the airway bifurcations. To explain how these two competing effects shape the flow state in the deeper generations, we have performed the first high-fidelity numerical simulations of the air flow in a lung model including 23 successive bifurcations of a single planar airway. Turbulence modelling or assumptions on flow regimes are not required. The chosen flow rate is stationary (steady on average), and representative of the peak inspiratory flow reached by adult patients breathing through therapeutical inhalers. As expected, advection becomes progressively less important after each bifurcation, until a time-dependent Stokes regime governed solely by viscous diffusion is established in the smallest generations. However, fluctuations in this regime are relatively fast and large with respect to the mean flow, which is in contrast with the commonly agreed picture that only the breathing frequency is relevant at the scale of the al
Inhalation directs air through a defined pathway, initiating from nostrils, moving through the main nasal cavity, past the pharynx and trachea, and culminating in the lungs. Inhaled particles, of a range of sizes, are ferried by this incoming air but are filtered and trapped by upper airway structures to protect the delicate lower respiratory system. From an energetics perspective, the airflow physics along this convoluted tract is characterized by turbulence. The system approaches a critical stationary state over the time scales during which particles enter the airway and deposit. This stasis can be conjectured to correspond with the emergence of criticality in the complex flow domain. For such systemic criticality (i.e., sensitivity to perturbations), inhaled particle deposition impacted by the surrounding flow processes can act as signature avalanche-like events. Based on the principles of organized criticality, we have explored the emergence of power law trends in particle deposition levels at the nasopharynx, a key initial infection site for airborne pathogens. These trends are derived from numerical data from five anatomic airway geometries for 15-85 L/min inhalation rates, m
Shear cell tests have been conducted on twenty different lactose powders, most of which commercially available for oral or inhalation purposes, spanning a wide range of particle sizes, particle morphologies, production processes. The aims of the investigation were: i) to verify the reliability of the technique in evaluating and classifying the flowability of powders; ii) to understand the connection between the flowability of a powder and the morphological properties of its particles; iii) to find a general mathematical relationship able to predict the yield locus shape given the particle size, shape and consolidation state of a lactose powder. These aspects and their limitations are detailed in the manuscript together with other interesting findings on the stick-slip behavior observed in most of the lactose powders examined.
N,N,N-Trimethyl chitosan (TMC), a biocompatible and biodegradable derivative of chitosan, is currently used as a permeation enhancer to increase the translocation of drugs to the bloodstream in the lungs. This article discusses the effect of TMC on a mimetic pulmonary surfactant, Curosurf, a low-viscosity lipid formulation administered to preterm infants with acute respiratory distress syndrome. Curosurf exhibits a strong interaction with TMC, resulting in the formation of aggregates at electrostatic charge stoichiometry. At nanoscale, Curosurf undergoes a profound reorganization of its lipid vesicles in terms of size and lamellarity. The initial micron-sized vesicles (average size 4.8 microns) give way to a froth-like network of unilamellar vesicles about 300 nm in size. Under such conditions, neutralization of the cationic charges by pulmonary surfactant may inhibit TMC permeation enhancer capacity, especially as electrostatic charge complexation is found at low TMC content. The permeation properties of pulmonary surfactant-neutralized TMC should then be evaluated for its applicability as a permeation enhancer for inhalation in the alveolar region.
Surgical masks have played a crucial role in healthcare facilities to protect against respiratory and infectious diseases, particularly during the COVID-19 pandemic. However, the synthetic fibers, mainly made of polypropylene, used in their production may adversely affect the environment and human health. Recent studies have confirmed the presence of microplastics and fibers in human lungs and have related these synthetic particles with the occurrence of pulmonary ground glass nodules. Using a piston system to simulate human breathing, this study investigates the role of surgical masks as a direct source of inhalation of microplastics. Results reveal the release of particles of sizes ranging from nanometers (300 nm) to millimeters (~2 mm) during normal breathing conditions, raising concerns about the potential health risks. Notably, large visible particles (> 1 mm) were observed to be ejected from masks with limited wear after only a few breathing cycles. Given the widespread use of masks by healthcare workers and the potential future need for mask usage by the general population during seasonal infectious diseases or new pandemics, developing face masks using safe materials for
The seemingly simple process of inhalation relies on a complex interplay between muscular contraction in the thorax, elasto-capillary interactions in individual lung branches, propagation of air between different connected branches, and overall air flow into the lungs. These processes occur over considerably different length and time scales; consequently, linking them to the biomechanical properties of the lungs, and quantifying how they together control the spatiotemporal features of inhalation, remains a challenge. We address this challenge by developing a computational model of the lungs as a hierarchical, branched network of connected liquid-lined flexible cylinders coupled to a viscoelastic thoracic cavity. Each branch opens at a rate and a pressure that is determined by input biomechanical parameters, enabling us to test the influence of changes in the mechanical properties of lung tissues and secretions on inhalation dynamics. By summing the dynamics of all the branches, we quantify the evolution of overall lung pressure and volume during inhalation, reproducing the shape of measured breathing curves. Using this model, we demonstrate how changes in lung muscle contraction, m
In this research, we presented the method of inhalation therapy with noble gas micro-doses and results of clinical studies in hospital of Russian Academy of Sciences (RAS). We have designed a device that allows dosed injection of noble gas with a volume of about 2-4 ml with peroxide vapors into the nasal cavity. After testing on the authors of the project and obtaining a positive impact of xenon and krypton, a study was conducted on a group of conditionally healthy volunteers in the amount of 20 people. We have noted a positive effect from 18 people. And also, in this article we briefly described the methods and devices that are used for inhalation therapy with mixtures of noble gases with oxygen. Keywords: noble gases, oxygen, inhalation therapy, device, respiratory apparatus, aerosols, COVID-19 pneumonia.
During a rapid inhalation, such as a sniff, the flow in the airways accelerates and decays quickly. The consequences for flow development and convective trans- port of an inhaled gas were investigated in a subject geometry extending from the nose to the bronchi. The progress of flow transition and the advance of an inhaled non-absorbed gas were determined using highly resolved simulations of a sniff 0.5 s long, 1 litre per second peak flow, 364 ml inhaled volume. In the nose, the distribution of airflow evolved through three phases: (i) an initial transient of about 50 ms, roughly the filling time for a nasal volume, (ii) quasi-equilibrium over the majority of the inhalation, and (iii) a terminating phase. Flow transition commenced in the supraglottic region within 20ms, resulting in large- amplitude fluctuations persisting throughout the inhalation; in the nose, fluctuations that arose nearer peak flow were of much reduced intensity and diminished in the flow decay phase. Measures of gas concentration showed non-uniform build-up and wash-out of the inhaled gas in the nose. At the carina, the form of the temporal concentration profile reflected both shear dispersion and airway fill
Objective: To quantify the effect of inhaled 5% carbon-dioxide/95% oxygen on EEG recordings from patients in non-convulsive status epilepticus (NCSE). Methods: Five children of mixed aetiology in NCSE were given high flow of inhaled carbogen (5% carbon dioxide/95% oxygen) using a face mask for maximum 120s. EEG was recorded concurrently in all patients. The effects of inhaled carbogen on patient EEG recordings were investigated using band-power, functional connectivity and graph theory measures. Carbogen effect was quantified by measuring effect size (Cohen's d) between "before", "during" and "after" carbogen delivery states. Results: Carbogen's apparent effect on EEG band-power and network metrics across all patients for "before-during" and "before-after" inhalation comparisons was inconsistent across the five patients. Conclusion: The changes in different measures suggest a potentially non-homogeneous effect of carbogen on the patients' EEG. Different aetiology and duration of the inhalation may underlie these non-homogeneous effects. Tuning the carbogen parameters (such as ratio between CO2 and O2, duration of inhalation) on a personalised basis may improve seizure suppression i
Studies of flow through the human airway have shown that inhalation time (IT) and secondary flow structures can play important roles in particle deposition. However, the effects of varying IT in conjunction with respiratory rate (RR) on airway flow remain unknown. Using 3D numerical simulations of oscillatory flow through an idealized airway model consisting of a mouth inlet, glottis, trachea and symmetric double bifurcation at trachea Reynolds number ($Re$) of 4,200, we investigated how varying the ratio of IT to breathing time (BT) from 25% to 50% and RR from 10 breaths per minute (bpm) corresponding to Womersley number ($Wo$) of 2.37 to 1,000 bpm ($Wo$=23.7) impacts airway flow characteristics. Irrespective of IT/BT, axial flow during inhalation at tracheal cross-sections was non-uniform for $Wo$=2.37 as compared to centrally concentrated distribution for $Wo$=23.7. For a given $Wo$ and IT/BT, both axial and secondary (lateral) flow components unevenly split between left and right branches of a bifurcation. Irrespective of $Wo$, IT/BT and airway generation, lateral dispersion was stronger than axial flow streaming. Despite left-right symmetry of the lower airway in our model, th
The purpose of research was to check up the influence of decrease of nonequality of ventilating (after bronchodilator (berotec) inhalation (BI)) on the magnitude of dynamic compliance of lungs (Cdyn) at asthma patients with ventilating infringements. Methods and materials: 20 patients (with 2 and 3 degrees of ventilating infringements (VC<73%, FEV1<51%, MVV<56%), without restrictive disease of lungs, suffering from bronchial asthma were studied before and after BI by plotting volume, rate flow, against the transpulmonare pressure. About the change of nonequality of ventilating we consider by the change after BI of Cdyn, Cdyn at once after flow interruption (Cdyn1), tissue resistance at inhalation (Rti in) and exhalation (Rti ex), parameters of ventilating and general parameters of respiratory mechanics. Results: the parameters of ventilating were improved (P < 0,05). General parameters of respiratory mechanics also improved. Rti in and Rti ex are made 0,48+0,16; 1,05+0,25 kPa/l/s before BI and decreased 0,09+0,04; 0,28+0,09 kPa/l/s after BI (P < 0,05; P < 0,05). But Cdyn and Cdyn1 are not changed after BI. Conclusions: 1. The decrease of ventilation nonequality an
Before aerosols can be sensed, sampling technologies must capture the particulate matter of interest. To that end, for systems deployed in open environments where the location of the aerosol is unknown, extending the reach of the sampler could lessen the precision required in sensor placement or reduce the number of sensors required for full spatial coverage. Inspired by the sensitivity of the canine olfactory system, this paper presents a rudimentary sampler that mimics the air flow of a dog's nose. The design consists of speed-controlled inhalation jets, as well as exhalation jets that are angled down and to the side. We tested this design on volatile organic compounds (VOC) in a small number of scenarios to validate the concept and understand how the system behaves. We show that in preliminary testing this dog-nose setup provides improvements over passive and solely inhalation sensing.
Background: Cystic fibrosis (CF) airway mucus exhibits reduced mucin sialylation, increasing viscosity and impairing mucociliary clearance (MCC). NEU1 inhibition has been proposed to restore MCC, but its quantitative pharmacokinetic and rheological effects, particularly with inhaled delivery, remain uncharacterized. Objective: To develop an integrated pharmacokinetic/pharmacodynamic (PK/PD) and biophysical model to assess the efficacy of an inhaled NEU1 inhibitor. Methods: Empirical and preclinical NEU1 inhibition data were combined with inhalation PK/PD modeling and a biophysical viscosity framework linking mucin sialylation and extracellular DNA. Synthetic cohort simulations (N = 200) were reconciled with empirical PK benchmarks using Latin hypercube parameter sampling. Cross-validation, hold-out testing, and causal inference methods (inverse probability of treatment weighting and targeted maximum likelihood estimation) quantified predicted effects on lung function (delta FEV1). Results: With reconciled parameters (F_dep = 0.12; k_abs = 0.21 per hour; k_muc = 0.24 per hour), epithelial lining fluid drug levels reached a peak concentration of 7.5 micromolar (95 percent CI: 6 to 10
The patterns of inhalation and exhalation contain important physiological signals that can be used to anticipate human behavior, health trends, and vital parameters. Human activity recognition (HAR) is fundamentally connected to these vital signs, providing deeper insights into well-being and enabling real-time health monitoring. This work presents i-Mask, a novel HAR approach that leverages exhaled breath patterns captured using a custom-developed mask equipped with integrated sensors. Data collected from volunteers wearing the mask undergoes noise filtering, time-series decomposition, and labeling to train predictive models. Our experimental results validate the effectiveness of the approach, achieving over 95\% accuracy and highlighting its potential in healthcare and fitness applications.
Could the microdroplets formed by viscoelastic stretching and break-up of mucosal liquids in the upper respiratory tract (URT), when inhaled further downwind, explain the brisk pace at which deep lung infections emerge following onset of initial infection at the URT? While it is well-established that particulates inhaled from outside can possibly penetrate to the lower airway only if they are < 5 microns, the fate of particulates (many > 5-microns in diameter) sheared away from the intra-URT mucosa during inhalation remains an open question. These particulates predominantly originate at the nasopharynx, oropharynx, and laryngeal chamber with the vocal folds. To resolve the posed question, this study considers a CT-based 3D anatomical airway reconstruction and isolates the tract from the laryngeal vocal fold region, mapping the entire tracheal cavity and concluding at generation 2 of the tracheobronchial tree. Through the delineated geometry, airflow simulation is conducted using the LES scheme to replicate relaxed inhalation at 15 L/min. Against the ambient air flux, numerical experiments have been performed to monitor the transport of liquid particulates with diameters 1-30
Objective: The accurate segmentation of capnograms during cardiopulmonary resuscitation (CPR) is essential for effective patient monitoring and advanced airway management. This study aims to develop a robust algorithm using a U-net architecture to segment capnograms into inhalation and non-inhalation phases, and to demonstrate its superiority over state-of-the-art (SoA) methods in the presence of CPR-induced artifacts. Materials and methods: A total of 24354 segments of one minute extracted from 1587 patients were used to train and evaluate the model. The proposed U-net architecture was tested using patient-wise 10-fold cross-validation. A set of five features was extracted for clustering analysis to evaluate the algorithm performance across different signal characteristics and contexts. The evaluation metrics included segmentation-level and ventilation-level metrics, including ventilation rate and end-tidal-CO$_2$ values. Results: The proposed U-net based algorithm achieved an F1-score of 98% for segmentation and 96% for ventilation detection, outperforming existing SoA methods by 4 points. The root mean square error for end-tidal-CO$_2$ and ventilation rate were 1.9 mmHg and 1.1
Asthma is a chronic respiratory condition that affects millions of people worldwide. While this condition can be managed by administering controller medications through handheld inhalers, clinical studies have shown low adherence to the correct inhaler usage technique. Consequently, many patients may not receive the full benefit of their medication. Automated classification of inhaler sounds has recently been studied to assess medication adherence. However, the existing classification models were typically trained using data from specific inhaler types, and their ability to generalize to sounds from different inhalers remains unexplored. In this study, we adapted the wav2vec 2.0 self-supervised learning model for inhaler sound classification by pre-training and fine-tuning this model on inhaler sounds. The proposed model shows a balanced accuracy of 98% on a dataset collected using a dry powder inhaler and smartwatch device. The results also demonstrate that re-finetuning this model on minimal data from a target inhaler is a promising approach to adapting a generic inhaler sound classification model to a different inhaler device and audio capture hardware. This is the first study i
The rapid development of Internet of Things (IoT) technology has significantly impacted various market sectors. According to Li et al. (2024), an estimated 75 billion devices will be on the market in 2025. The healthcare industry is a target to improve patient care and ease healthcare provider burdens. Chronic respiratory disease is likely to benefit from their inclusion, with 545 million people worldwide recorded to suffer from patients using these devices to track their dosage. At the same time, healthcare providers can improve medication administration and monitor respiratory health (Soriano et al., 2020). While IoT medical devices offer numerous benefits, they also have security vulnerabilities that can expose patient data to cyberattacks. It's crucial to prioritize security measures in developing and deploying IoT medical devices, especially in personalized health monitoring systems for individuals with respiratory conditions. Efforts are underway to assess the security risks associated with intelligent inhalers and respiratory medical devices by understanding usability behavior and technological elements to identify and address vulnerabilities effectively. This work analyses