Mora, Sabrina

Objectives: This study evaluates the efficacy of existing and new aerosol mitigation methods during nebulization (Neb) in combination with high-flow nasal cannula (HFNC) oxygen supplementation and non-invasive ventilation (NIV). Methods: We recorded fugitive aerosol particle concentrations over time and assessed the peak (P) and area (A) efficacy of active and passive mitigation methods, comparing them to a no-mitigation condition. Peak efficacy was measured by the reduction in maximum aerosol concentration, while area efficacy was quantified by the reduction of the area under the aerosol concentration–time curve. Results: For HFNC with Neb, we found that active mitigation using a mask with a biofilter and a fan (referred to as the aerosol barrier mask) significantly outperformed passive mitigation with a face mask. The peak and area efficacy for aerosol reduction were 99.0% and 96.4% for active mitigation and 35.9% and 7.6% for passive mitigation, respectively. For NIV with Neb, the active mitigation method, using a box with a biofilter and fan, also outperformed passive mitigation using only the box. The peak and area efficacy for aerosol reduction were 92.1% and 85.5% for active mitigation and 53.7.0% and 25.4% for passive mitigation, respectively. Conclusion: We concluded that active mitigation set up systems advantageous for effective reduction of airborne aerosols during aerosol generated procedures.

Ketones are well-known biomarkers of fat oxidation produced in the liver as a result of lipolysis. These biomarkers include acetoacetic acid and β-hydroxybutyric acid in the blood/urine and acetone in our breath and skin. Monitoring ketone production in the body is essential for people who use caloric intake deficit to reduce body weight or use ketogenic diets for wellness or therapeutic treatments. Current methods to monitor ketones include urine dipsticks, capillary blood monitors, and breath analyzers. However, these existing methods have certain disadvantages that preclude them from being used more widely. In this work, we introduce a novel acetone sensor device that can detect acetone levels in breath and overcome the drawbacks of existing sensing approaches. The critical element of the device is a robust sensor with the capability to measure acetone using a complementary metal oxide semiconductor (CMOS) chip and convenient data analysis from a red, green, and blue deconvolution imaging approach. The acetone sensor device demonstrated sensitivity of detection in the micromolar-concentration range, selectivity for detection of acetone in breath, and a lifetime stability of at least one month. The sensor device utility was probed with real tests on breath samples using an established blood ketone reference method.

Abstract In the initial stages of the COVID-19 pandemic, it became evident that singing carried a substantial risk of virus transmission. Consequently, new regulations were implemented to safeguard the population, and the adoption of singing masks emerged as a pivotal measure to curb the spread of COVID-19 during vocal performances. However, the discomfort and impediment to sensory expression caused by these masks posed significant challenges, particularly for individuals whose passions or professions revolved around singing. This study shows a novel solution to address these issues: the Aerosol Barrier System for Singing. The system features a transparent screen with an Impactor-Fan-Filter. The Impactor-Fan-Filter (IFF) is integrated into the transparent screen and strategically positioned within 1.5 feet of the singer's face. We demonstrated that the system effectively reduces the dispersion of aerosols generated during singing by over 99%. In addition, comparative sound analysis indicated that the system minimizes interference with sound waves, ensuring the preservation of sound quality. Furthermore, the transparent screen offers an unobstructed view of the singer, enhancing the overall performance experience. Our system adheres to several crucial criteria for an effective solution tailored to the needs of singers: it prioritizes safety and comfort, upholds sound quality, and facilitates an unrestricted view of the singer's entire face for the benefit of the audience, conductors, and ensemble members.

Energy Expenditure (EE) (kcal/day), a key element to guide obesity treatment, is measured from CO2 production, VCO2 (mL/min), and/or O2 consumption, VO2 (mL/min). Current technologies are limited due to the requirement of wearable facial accessories. A novel system, the Smart Pad, which measures EE via VCO2 from a room’s ambient CO2 concentration transients was evaluated. Resting EE (REE) and exercise VCO2 measurements were recorded using Smart Pad and a reference instrument to study measurement duration’s influence on accuracy. The Smart Pad displayed 90% accuracy (±1 SD) for 14–19 min of REE measurement and for 4.8–7.0 min of exercise, using known room’s air exchange rate. Additionally, the Smart Pad was validated measuring subjects with a wide range of body mass indexes (BMI = 18.8 to 31.4 kg/m2), successfully validating the system accuracy across REE’s measures of ~1200 to ~3000 kcal/day. Furthermore, high correlation between subjects’ VCO2 and λ for CO2 accumulation was observed (p < 0.00001, R = 0.785) in a 14.0 m3 sized room. This finding led to development of a new model for REE measurement from ambient CO2 without λ calibration using a reference instrument. The model correlated in nearly 100% agreement with reference instrument measures (y = 1.06x, R = 0.937) using an independent dataset (N = 56).

This work investigates the use of an intelligent and unobstructive sensing technique for maintaining vehicle cabin’s indoor air quality while simultaneously assessing the driver metabolic rate. CO2 accumulation patterns are of great interest because CO2 can have negative cognitive effects at higher concentrations and also since CO2 accumulation rate can potentially be used to determine a person’s metabolic rate. The management of the vehicle’s ventilation system was controlled by periodically alternating the air recirculation mode within the cabin, which was actuated based on the CO2 levels inside the vehicle’s cabin. The CO2 accumulation periods were used to assess the driver’s metabolic rate, using a model that considered the vehicle’s air exchange rate. In the process of the method optimization, it was found that the vehicle’s air exchange rate (λ [h−1]) depends on the vehicle speeds, following the relationship: λ = 0.060 × (speed) − 0.88 when driving faster than 17 MPH. An accuracy level of 95% was found between the new method to assess the driver’s metabolic rate (1620 ± 140 kcal/day) and the reference method of indirect calorimetry (1550 ± 150 kcal/day) for a total of N = 16 metabolic assessments at various vehicle speeds. The new sensing method represents a novel approach for unobstructive assessment of driver metabolic rate while maintaining indoor air quality within the vehicle cabin.