Citations

Ketones, which are key biomarkers of fat oxidation, are relevant for metabolic health maintenance and disease development, making continuous monitoring essential. In this study, we introduce a novel colorimetric sensor designed for potential continuous acetone detection in biological fluids. The sensor features a polydimethylsiloxane (PDMS) shell that encapsulates a sensitive and specific liquid-core acetone-sensing probe. The microsphere sensors were characterized by evaluating their size, PDMS shell thickness, colorimetric response, and sensitivity under realistic conditions, including 100% relative humidity (RH) and CO2 interference. The microsphere size and sensor sensitivity can be controlled by modifying the fabrication parameters. Critically, the sensor showed high selectivity for acetone detection, with negligible interference from CO2 concentrations up to 4%. In addition, the sensor displayed good reproducibility (CV < 5%) and stability under realistic storage conditions (over two weeks at 4 °C). Finally, the accuracy of the microsphere sensor was validated against a gold standard gas chromatography-mass spectrometry (GC-MS) method using simulated and real breath samples from healthy individuals and type 1 diabetes patients. The correlation between the microsphere sensor and GC-MS produced a linear fit with a slope of 0.948 and an adjusted R-squared value of 0.954. Therefore, the liquid-core microsphere-based sensor is a promising platform for acetone body fluid analysis.

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.

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.

This work evaluates the use of a new flow meter to assess exhalation rate. A mobile indirect calorimeter (MIC) was designed and used to measure resting metabolic rate (RMR), which relies on the measure of O2 consumption rate (VO2) and CO2 production rate (VCO2). The device was produced from a commercially available and well-established indirect calorimeter and implemented with a new flow meter for the purpose of this study. VO2 and VCO2 were assessed by measuring exhalation rates using the new flow meter and O2 and CO2 concentrations in breath using the original colorimetric sensors of the indirect calorimeter. The new flow meter was based on a thermal flow meter (TFM) affixed to an orifice with a diameter of 6.8 mm used as a passage for exhaled breath from 16 subjects. The results were compared with a metabolic cart (Medical Graphics), which was connected in series to the modified device. We found that 69% of the results had more than a 10% difference between the modified MIC device and the reference instrument, suggesting that the sensitivity of the thermal flow meter changed over time, which precluded its use as a flow meter for breath flow rate measurement.

Abstract The present work introduces the use of environmental sensors to assess indoor air quality (IAQ) in combination with human biometrics. The sensor array included temperature, relative humidity, carbon dioxide, and noise monitors. The array was used in a classroom as well as in a vehicle cabin to assess the carbon dioxide production rate of individuals in a closed ventilation environment. Analysis of carbon dioxide production allowed for the quantification of the average metabolic rate of the group of individuals in the classroom, and for one individual in the vehicle cabin. These results yielded a mere 5% difference from the values assessed using commercial metabolic rate instruments, and averaged values from epidemiological studies. The results presented in this work verify the feasibility of determining an individual’s metabolic rate using passive environmental sensors; these same sensors are able to provide a metric of IAQ that helps characterize the safety of the environment in which the individual is present.