Optical Monitoring of Breathing Patterns and Tissue Oxygenation: A Potential Application in COVID-19 Screening and Monitoring.

The worldwide outbreak of the novel Coronavirus (COVID-19) has highlighted the need for a screening and monitoring system for infectious respiratory diseases in the acute and chronic phase. The purpose of this study was to examine the feasibility of using a wearable near-infrared spectroscopy (NIRS) sensor to collect respiratory signals and distinguish between normal and simulated pathological breathing. Twenty-one healthy adults participated in an experiment that examined five separate breathing conditions. Respiratory signals were collected with a continuous-wave NIRS sensor (PortaLite, Artinis Medical Systems) affixed over the sternal manubrium. Following a three-minute baseline, participants began five minutes of imposed difficult breathing using a respiratory trainer. After a five minute recovery period, participants began five minutes of imposed rapid and shallow breathing. The study concluded with five additional minutes of regular breathing. NIRS signals were analyzed using a machine learning model to distinguish between normal and simulated pathological breathing. Three features: breathing interval, breathing depth, and O2Hb signal amplitude were extracted from the NIRS data and, when used together, resulted in a weighted average accuracy of 0.87. This study demonstrated that a wearable NIRS sensor can monitor respiratory patterns continuously and non-invasively and we identified three respiratory features that can distinguish between normal and simulated pathological breathing.

Review of the efficacy of infrared thermography for screening infectious diseases with applications to COVID-19.

Purpose: The recent coronavirus disease 2019 (COVID-19) pandemic, which spread across the globe in a very short period of time, revealed that the transmission control of disease is a crucial step to prevent an outbreak and effective screening for viral infectious diseases is necessary. Since the severe acute respiratory syndrome (SARS) outbreak in 2003, infrared thermography (IRT) has been considered a gold standard method for screening febrile individuals at the time of pandemics. The objective of this review is to evaluate the efficacy of IRT for screening infectious diseases with specific applications to COVID-19. Approach: A literature review was performed in Google Scholar, PubMed, and ScienceDirect to search for studies evaluating IRT screening from 2002 to present using relevant keywords. Additional literature searches were done to evaluate IRT in comparison to traditional core body temperature measurements and assess the benefits of measuring additional vital signs for infectious disease screening. Results: Studies have reported on the unreliability of IRT due to poor sensitivity and specificity in detecting true core body temperature and its inability to identify asymptomatic carriers. Airport mass screening using IRT was conducted during occurrences of SARS, Dengue, Swine Flu, and Ebola with reported sensitivities as low as zero. Other studies reported that screening other vital signs such as heart and respiratory rates can lead to more robust methods for early infection detection. Conclusions: Studies evaluating IRT showed varied results in its efficacy for screening infectious diseases. This suggests the need to assess additional physiological parameters to increase the sensitivity and specificity of non-invasive biosensors.

The Role of Human–Machine Interactive Devices for Post-COVID-19 Innovative Sustainable Tourism in Ho Chi Minh City, Vietnam

In this research article, we aim to study the proposed role of human–machine interactive (HMI) technologies, including both artificial intelligence (AI) and virtual reality (VR)-enabled applications, for the post-COVID-19 revival of the already depleted tourism industry in Vietnam’s major tourist destination and business hub of Ho Chi Minh City. The researchers aim to gather practical knowledge regarding tourists’intentions for such service enhancements, which may drive the sector to adopt a better conclusive growth pattern in post-COVID-19 times. In this study, we attempt to focus on travelers who look for paramount safety with the assurance of empathetic, personalized care in post-COVID-19 times. In the current study, the authors employ structural equation modeling to evaluate the intentions of tourists both structurally and empirically for destination tourism with data collected from tourists with previous exposure to various kinds of these devices. The study shows that human–machine interactive devices are integrating AI and VR and have a significant effect on overall service quality, leading to tourist satisfaction and loyalty. The use of such social interactive gadgets within tourism and mostly in hospitality services requires an organization to make a commitment to futuristic technologies, along with building value by enriching service quality expectations among fearful tourists. This research shows that tourists mainly focus on the use of such HMI devices from the perspective of technology acceptance factors, qualitative value-enhancing service and trustworthy information-sharing mechanisms. The concept of the tour bubble framework is also discussed in detail. The analysis of this discussion gives us a more profound understanding of the novel opportunities which various administrative agencies may benefit from to position these devices better in smart, sustainable destination tourism strategies for the future so that, collectively, service 5.0 with HMI devices can possibly bring back tourism from being disintegrated. Such service applications are the new social innovations leading to sustainable service and a sophisticated experience for all tourists.

A fluid mechanics explanation of the effectiveness of common materials for respiratory masks.

OBJECTIVES: Face masks are an important component of personal protection equipment employed in preventing the spread of diseases such as COVID-19. As the supply of mass-produced masks has decreased, the use of homemade masks has become more prevalent. It is important to quantify the effectiveness of different types of materials to provide useful information, which should be considered for homemade masks. METHODS: Filtration effects of different types of common materials were studied by measuring the aerosol droplet concentrations in the upstream and downstream regions. Flow-field characteristics of surrounding regions of tested materials were investigated using a laser-diagnostics technique, i.e., particle image velocimetry. The pressure difference across the tested materials was measured. RESULTS: Measured aerosol concentrations indicated a breakup of large-size particles into smaller particles. Tested materials had higher filtration efficiency for large particles. Single-layer materials were less efficient, but they had a low pressure-drop. Multilayer materials could produce greater filtering efficiency with an increased pressure drop, which is an indicator of comfort level and breathability. The obtained flow-fields indicated a flow disruption downstream of the tested materials as the velocity magnitude noticeably decreased. CONCLUSIONS: The obtained results provide an insight into flow-field characteristics and filtration efficiency of different types of household materials commonly used for homemade masks. This study allows comparison with mass-produced masks under consistent test conditions while employing several well-established techniques.