A Smart System for the Contactless Measurement of Energy Expenditure.

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).

Comparative study of a novel portable indirect calorimeter to a reference breath-by-breath instrument and its use in telemedicine settings.

BACKGROUND & AIMS: Resting Energy Expenditure (REE) quantitatively describes the calories used to support body function (e.g. breathing, blood circulation, etc.) at resting condition. Assessment of the REE is essential for successful weight management and the understanding of metabolic health. REE is typically determined via indirect calorimetry. Current biomedical indirect calorimetry technologies, utilizing assessment of oxygen consumption (VO2) and carbon dioxide production (VCO2) rates (which are typically in the form factor of a metabolic cart) are bulky and require on-site calibration and/or trained professionals to operate. We introduce a novel wearable medical device with FDA clearance to determine REE accurately, portable, and user-friendly format, which can be used both by health professionals in a clinical environment and by the patient at home. Previously, we have reported the validation of Breezing Med (also named as Breezing Pro™) through Douglas Bag Method, a gold standard for gas exchange measurement, and excellent agreement has been found between the two methods for the determination of REE, VO2, and VCO2 rates (Mora et al., 2020). Now we present the validation of Breezing Med against Medical Graphics (MGC) CPX Ultima™, a FDA 510 k cleared metabolic cart, which principle is based on breath-by-breath analysis. In addition, we present Breezing Med as a tool for daily measurement of metabolic rate by the lay person at home. METHODS: A) The validation study was executed via parallel measurement of 20 healthy participants under resting conditions using both the Breezing Med and the MGC Ultima CPX™ (10 min test). B) Breezing Med measurements were carried out by six subjects at home during stay-at-home order due to COVID-19 for 30 days. RESULTS: A) The resulting measurements from both devices was compared with correlation slope's and R-squared coefficients close to 1. B) Results were recorded and analyzed for variability. The pilot study demonstrated the advantage of Breezing Med device to be easy-to-use at home by lay people, which make the valuable device for telemedicine applications related to weight management from home. CONCLUSIONS: This result shows that the MGC Ultima CPX™ and Breezing Med are substantially equivalent for REE measurement; and an advantage of this device for metabolic assessment under the current COVID-19 pandemic situation, for people with impaired physical mobility, and for those who lives in rural areas or face impediments that limit physical access to care.

A novel vertical flow assay for point of care measurement of iron from whole blood.

Disorders in iron metabolism are endemic globally, affecting more than several hundred million individuals and often resulting in increased rates of mortality or general deterioration of quality of life. To both prevent and monitor treatment of iron related disorders, we present a point of care medical device which leverages a simple smartphone camera to measure total iron concentration from a finger-prick sample. The system consists of a smartphone and an in-house developed app, a 3D printed sensing chamber and a vertical flow membrane-based sensor strip designed to accommodate 50 µl of whole blood, filter out the cellular components and carry out a colorimetric chelation reaction producing a colour change which is detected by our smartphone device. The app's accuracy and precision were assessed via comparison of the mobile app's RGB output to a reference imaging software, ImageJ for the same colorimetric sensing strip. Correlation plots resulted in slopes of 0.99 and coefficient of determination (R2 = 0.99). The device was determined to have a signal to noise ratio >40 and a mean bias of 2% which both indicate high analytical accuracy and precision (in terms of RGB measurement). The smartphone device's iron concentration readout was then studied using an extensively validated laboratory developed test (LDT) for iron detection, which is an optimized spectrophotometry-based technique (this is considered the gold standard for iron quantification among LDTs). In comparison of the smartphone-based technique with the gold standard LDT, a calibration slope of 0.0004 au µg-1 dL-1, a correlation plot with slope of 1.09 and coefficient of determination (R2) of 0.96 and a mean bias of 5.3%, our device can accurately measure iron levels in blood. With detection times of five minutes, fingerpick sample and sensor cost less than 10 cents, the device shows great promise in being developed as the first ever commercial device for iron quantification in blood.

A system for contact free energy expenditure assessment under free-living conditions: monitoring metabolism for weight loss using carbon dioxide emission.

Weight disorders are strikingly prevalent globally and can contribute to a wide array of potentially fatal diseases spanning from type II diabetes to coronary heart disease. These disorders have a common cause: poor calorie balance. Since energy expenditure (EE) (kcal d-1) constitutes one half of the calorie balance equation (the other half being food intake), its measurement could be of great value to those suffering from weight disorders. A technique for contact free assessment of EE is presented, which only relies on CO2concentration monitoring within a sealed office space, and assessment of carbon dioxide production rate (VCO2). Twenty healthy subjects were tested in a cross-sectional study to evaluate the performance of the aforementioned technique in measuring both resting EE (REE) and exercise EE using the proposed system (the 'SmartPad') and a U.S. Food and Drug Administration (FDA) cleared gold standard reference instrument for EE measurement. For VCO2and EE measurements, the method showed a correlation slope of 1.00 and 1.03 with regression coefficients of 0.99 and 0.99, respectively, and Bland-Altman plots with a mean bias = -0.232% with respect to the reference instrument. Furthermore, two subjects were also tested as part of a proof-of-concept longitudinal study where EE patterns were simultaneously tracked with body weight, sleep, stress, and step counts using a smartwatch over the course of a month, to determine correlation between the aforementioned parameters and EE. Analysis revealed moderately high correlation coefficients (Pearson'sr) for stress (raverage= 0.609) and body weight (raverage= 0.597) for the two subjects. The new SmartPad method was demonstrated to be a promising technique for EE measurement under free-living conditions.

An Unobstructive Sensing Method for Indoor Air Quality Optimization and Metabolic Assessment within Vehicles.

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.

Total Iron Measurement in Human Serum With a Novel Smartphone-Based Assay.

Background: Abnormally low or high blood iron levels are common health conditions worldwide and can seriously affect an individual's overall well-being. A low-cost point-of-care technology that measures blood iron markers with a goal of both preventing and treating iron-related disorders represents a significant advancement in medical care delivery systems. Methods: A novel assay equipped with an accurate, storable, and robust dry sensor strip, as well as a smartphone mount and (iPhone) app is used to measure total iron in human serum. The sensor strip has a vertical flow design and is based on an optimized chemical reaction. The reaction strips iron ions from blood-transport proteins, reduces Fe(III) to Fe(II), and chelates Fe(II) with ferene, with the change indicated by a blue color on the strip. The smartphone mount is robust and controls the light source of the color reading App, which is calibrated to obtain output iron concentration results. The real serum samples are then used to assess iron concentrations from the new assay, and validated through intra-laboratory and inter-laboratory experiments. The intra-laboratory validation uses an optimized iron detection assay with multi-well plate spectrophotometry. The inter-laboratory validation method is performed in a commercial testing facility (LabCorp). Results: The novel assay with the dry sensor strip and smartphone mount, and App is seen to be sensitive to iron detection with a dynamic range of 50 - [Formula: see text]/dL, sensitivity of 0.00049 a.u/[Formula: see text]/dL, coefficient of variation (CV) of 10.5%, and an estimated detection limit of [Formula: see text]/dL These analytical specifications are useful for predicting iron deficiency and overloads. The optimized reference method has a sensitivity of 0.00093 a.u/[Formula: see text]/dL and CV of 2.2%. The correlation of serum iron concentrations (N = 20) between the optimized reference method and the novel assay renders a slope of 0.95, and a regression coefficient of 0.98, suggesting that the new assay is accurate. Last, a spectrophotometric study of the iron detection reaction kinetics is seen to reveal the reaction order for iron and chelating agent. Conclusion: The new assay is able to provide accurate results in intra- and inter- laboraty validations, and has promising features of both mobility and low-cost manufacturing suitable for global healthcare settings.

A Handheld, Colorimetric Optoelectronic Dynamics Analyzer for Measuring Total Ammonia of Biological Samples.

This paper introduces a wireless, solid-state, portable, and automated device capable of measuring the total ammonia [ammonia (NH3) and ammonium (NH4+)] levels of fluids, including biological samples. This device reliably measures the total ammonia of biological samples (e.g., urine) faster than the current ammonia quantification techniques. Medical professionals typically estimate NH4+ levels using error-prone indirect measurement techniques (i.e., urine anion gap), which are time-consuming and are seldom suitable for periodic measurements. Several instantaneous measurements of total ammonia levels in a patient urine could be utilized as an early warning for both acid-base and/or potassium disturbances. Given the device's operation mechanism, it is able to quantify the total ammonia concentration within a biological sample in only 5 s and can simultaneously transmit data to other devices via Bluetooth. The analytical operation demonstrated high sensitivity, high specificity, fast reversibility, rapid response time, and has enabled the accurate determination of total ammonia concentration in urine samples produced by subjects who had consumed diets of variable protein compositions.

Assessing metabolic rate and indoor air quality with passive environmental sensors.

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.