LES study on the impact of airway deformation on the airflow structures in the idealized mouth–throat model

Effects of face shield on an emitter during a cough process: A large-eddy simulation study

Face shield is a common personal protection equipment for pandemic. In the present work, three-dimensional computational fluid dynamic (CFD) method is used to simulate a cough jet from an emitter who wears a face shield. A realistic manikin model with a simplified mouth cavity is employed. A large eddy simulation with a dynamic structure subgrid scale model is applied to model the turbulence. An Eulerian-Lagrangian approach is adopted to model the two-phase flows, with which the droplets are represented by a cloud of particles. The droplet breakup, evaporation, dispersion, drag force, and wall impingement are considered in this model. An inlet velocity profile that is based on a variable mouth opening area is considered. Special attentions have been put the vortex structure and droplet re-distribution induced by the face shield. It is found that the multiple vortices are formed when the cough jet impinges on the face shield. Some droplets move backward and others move downward after the impinging. It is also found that a small modification of the face shield significantly modifies the flow field and droplet distribution. We conclude that face shield significantly reduces the risk factor in the front of the emitter, meanwhile the risk factor in the back of the emitter increases. When the receiver standing in front of the emitter is shorter than the emitter, the risk is still very high. More attentions should be paid on the design of the face field, clothes cleaning and floor cleaning of the emitters with face shields. Based on the predicted droplet trajectory, a conceptual model for droplet flux is proposed for the scenario with the face shield.

Body Acoustics for the Non-Invasive Diagnosis of Medical Conditions

In the past few decades, many non-invasive monitoring methods have been developed based on body acoustics to investigate a wide range of medical conditions, including cardiovascular diseases, respiratory problems, nervous system disorders, and gastrointestinal tract diseases. Recent advances in sensing technologies and computational resources have given a further boost to the interest in the development of acoustic-based diagnostic solutions. In these methods, the acoustic signals are usually recorded by acoustic sensors, such as microphones and accelerometers, and are analyzed using various signal processing, machine learning, and computational methods. This paper reviews the advances in these areas to shed light on the state-of-the-art, evaluate the major challenges, and discuss future directions. This review suggests that rigorous data analysis and physiological understandings can eventually convert these acoustic-based research investigations into novel health monitoring and point-of-care solutions.