TBscreen: A passive cough classifier for tuberculosis screening with a controlled dataset.

Recent respiratory disease screening studies suggest promising performance of cough classifiers, but potential biases in model training and dataset quality preclude robust conclusions. To examine tuberculosis (TB) cough diagnostic features, we enrolled subjects with pulmonary TB (N = 149) and controls with other respiratory illnesses (N = 46) in Nairobi. We collected a dataset with 33,000 passive coughs and 1600 forced coughs in a controlled setting with similar demographics. We trained a ResNet18-based cough classifier using images of passive cough scalogram as input and obtained a fivefold cross-validation sensitivity of 0.70 (±0.11 SD). The smartphone-based model had better performance in subjects with higher bacterial load {receiver operating characteristic-area under the curve (ROC-AUC): 0.87 [95% confidence interval (CI): 0.87 to 0.88], P < 0.001} or lung cavities [ROC-AUC: 0.89 (95% CI: 0.88 to 0.89), P < 0.001]. Overall, our data suggest that passive cough features distinguish TB from non-TB subjects and are associated with bacterial burden and disease severity.

Blood glucose variance measured by continuous glucose monitors across the menstrual cycle.

Past studies on how blood glucose levels vary across the menstrual cycle have largely shown inconsistent results based on limited blood draws. In this study, 49 individuals wore a Dexcom G6 continuous glucose monitor and a Fitbit Sense smartwatch while measuring their menstrual hormones and self-reporting characteristics of their menstrual cycles daily. The average duration of participation was 79.3 ± 21.2 days, leading to a total of 149 cycles and 554 phases in our dataset. We use periodic restricted cubic splines to evaluate the relationship between blood glucose and the menstrual cycle, after which we assess phase-based changes in daily median glucose level and associated physiological parameters using mixed-effects models. Results indicate that daily median glucose levels increase and decrease in a biphasic pattern, with maximum levels occurring during the luteal phase and minimum levels occurring during the late-follicular phase. These trends are robust to adjustments for participant characteristics (e.g., age, BMI, weight) and self-reported menstrual experiences (e.g., food cravings, bloating, fatigue). We identify negative associations between each of daily estrogen level, step count, and low degrees of fatigue with higher median glucose levels. Conversely, we find positive associations between higher food cravings and higher median glucose levels. This study suggests that blood glucose could be an important parameter for understanding menstrual health, prompting further investigation into how the menstrual cycle influences glucose fluctuation.

Smartphone camera oximetry in an induced hypoxemia study.

Hypoxemia, a medical condition that occurs when the blood is not carrying enough oxygen to adequately supply the tissues, is a leading indicator for dangerous complications of respiratory diseases like asthma, COPD, and COVID-19. While purpose-built pulse oximeters can provide accurate blood-oxygen saturation (SpO2) readings that allow for diagnosis of hypoxemia, enabling this capability in unmodified smartphone cameras via a software update could give more people access to important information about their health. Towards this goal, we performed the first clinical development validation on a smartphone camera-based SpO2 sensing system using a varied fraction of inspired oxygen (FiO2) protocol, creating a clinically relevant validation dataset for solely smartphone-based contact PPG methods on a wider range of SpO2 values (70-100%) than prior studies (85-100%). We built a deep learning model using this data to demonstrate an overall MAE = 5.00% SpO2 while identifying positive cases of low SpO2 < 90% with 81% sensitivity and 79% specificity. We also provide the data in open-source format, so that others may build on this work.

O-pH: Optical pH Monitor to Measure Dental Biofilm Acidity and Assist in Enamel Health Monitoring.

OBJECTIVE: Bacteria in the dental biofilm produceacid after consumption of carbohydrates which if left unmonitored leads to caries formation. We present O-pH, a device that can measure dental biofilm acidity and provide quantitative feedback to assist in oral health monitoring. METHOD: O-pH utilizes a ratiometric pH sensing method by capturing fluorescence of Sodium Fluorescein, an FDA approved chemical dye. The device was calibrated to a lab pH meter using buffered fluorescein solution with a correlation coefficient of 0.97. The calibration was further verified in vitro on additional buffered solution, artificial, and extracted teeth. An in vivo study on 30 pediatric subjects was performed to measure pH before (rest pH) and after (drop pH) a sugar rinse, and the resultant difference in pH (diff pH) was calculated. The study enrolled subjects with low (Post-Cleaning) and heavy (Pre-Cleaning) biofilm load, having both unhealthy/healthy surfaces. Further, we modified point-based O-pH to an image-based device using a multimode-scanning fiber endoscope (mm-SFE) and tested in vivo on one subject. RESULTS AND CONCLUSION: We found significant difference between Post-Cleaning and Pre-Cleaning group using drop pH and diff pH. Additionally, in Pre-Cleaning group, the rest and drop pH is lower at the caries surfaces compared to healthy surfaces. Similar trend was not noticed in the Post-Cleaning group. mm-SFE pH scope recorded image-based pH heatmap of a subject with an average diff pH of 1.5. SIGNIFICANCE: This work builds an optical pH prototype and presents a pioneering study for non-invasively measuring pH of dental biofilm clinically.

Passively sensing SARS-CoV-2 RNA in public transit buses.

Affordably tracking the transmission of respiratory infectious diseases in urban transport infrastructures can inform individuals about potential exposure to diseases and guide public policymakers to prepare timely responses based on geographical transmission in different areas in the city. Towards that end, we designed and tested a method to detect SARS-CoV-2 RNA in the air filters of public buses, revealing that air filters could be used as passive fabric sensors for the detection of viral presence. We placed and retrieved filters in the existing HVAC systems of public buses to test for the presence of trapped SARS-CoV-2 RNA using phenol-chloroform extraction and RT-qPCR. SARS-CoV-2 RNA was detected in 14% (5/37) of public bus filters tested in Seattle, Washington, from August 2020 to March 2021. These results indicate that this sensing system is feasible and that, if scaled, this method could provide a unique lens into the geographically relevant transmission of SARS-CoV-2 through public transit rider vectors, pooling samples of riders over time in a passive manner without installing any additional systems on transit vehicles.

Using Health Concept Surveying to Elicit Usable Evidence: Case Studies of a Novel Evaluation Methodology.

BACKGROUND: Developers, designers, and researchers use rapid prototyping methods to project the adoption and acceptability of their health intervention technology (HIT) before the technology becomes mature enough to be deployed. Although these methods are useful for gathering feedback that advances the development of HITs, they rarely provide usable evidence that can contribute to our broader understanding of HITs. OBJECTIVE: In this research, we aim to develop and demonstrate a variation of vignette testing that supports developers and designers in evaluating early-stage HIT designs while generating usable evidence for the broader research community. METHODS: We proposed a method called health concept surveying for untangling the causal relationships that people develop around conceptual HITs. In health concept surveying, investigators gather reactions to design concepts through a scenario-based survey instrument. As the investigator manipulates characteristics related to their HIT, the survey instrument also measures proximal cognitive factors according to a health behavior change model to project how HIT design decisions may affect the adoption and acceptability of an HIT. Responses to the survey instrument were analyzed using path analysis to untangle the causal effects of these factors on the outcome variables. RESULTS: We demonstrated health concept surveying in 3 case studies of sensor-based health-screening apps. Our first study (N=54) showed that a wait time incentive could influence more people to go see a dermatologist after a positive test for skin cancer. Our second study (N=54), evaluating a similar application design, showed that although visual explanations of algorithmic decisions could increase participant trust in negative test results, the trust would not have been enough to affect people's decision-making. Our third study (N=263) showed that people might prioritize test specificity or sensitivity depending on the nature of the medical condition. CONCLUSIONS: Beyond the findings from our 3 case studies, our research uses the framing of the Health Belief Model to elicit and understand the intrinsic and extrinsic factors that may affect the adoption and acceptability of an HIT without having to build a working prototype. We have made our survey instrument publicly available so that others can leverage it for their own investigations.

Optical pH measurement system using a single fluorescent dye for assessing susceptibility to dental caries (Erratum).

The erratum corrects a grant number listed in Acknowledgments section of the original article.

Multi-Channel Facial Photoplethysmography Sensing.

Motivated by the need for continuous cardiovascular monitoring, we present a system for performing photoplethysmography sensing at multiple facial locations. As a proof-of-concept, our system incorporates an optical sensor array into a wearable face mask form factor for application in a surgical hemodynamic monitoring use case. Here we demonstrate that our design can accurately detect pulse timing by validating estimated heart rate against ground truth electrocardiogram recordings. In an experiment across 10 experimental subjects, our system achieves an error standard deviation of 2.84 beats per minute. This system shows promise for performing non-invasive, continuous pulse waveform recording from multiple locations on the face.

Optical pH measurement system using a single fluorescent dye for assessing susceptibility to dental caries.

Sugar-rich diets and poor dental hygiene promote the formation of a biofilm (plaque) that strongly adheres to the dental enamel surface and fosters the evolution of aciduric bacteria. The acid contributes to demineralization of the exterior tooth enamel, which accelerates after the pH drops below a critical value (∼5.5) for extended time periods resulting in the need for restorative procedures. Preventative techniques to alert the dentist and caries-susceptible patients regarding vulnerability to dental decay require a clinical measure of plaque activity. Therefore, there is a need to evaluate the acid production capability of plaque deposits in the pits and fissures of occlusal and interproximal regions. A ratiometric fluorescence pH-sensing device has been developed using an FDA-approved dye and LED excitation. Fluorescein spectral profiles were collected using a spectrometer and analyzed with a spectral unmixing algorithm for calibration over the pH range of 4.5 to 7. An in vivo pilot study on human subjects was performed using a sucrose rinse to accelerate bacterial metabolism and to measure the time-dependent drop in pH. The optical system is relatively immune to confounding factors such as photobleaching, dye concentration, and variation in excitation intensity associated with earlier dye-based pH measurement techniques.

Noninvasive hemoglobin measurement using unmodified smartphone camera and white flash.

We show that a mobile phone can measure hemoglobin levels using the built-in RGB camera and white LED without modification. Prior work has demonstrated that a smartphone using the built-in RGB camera with the aid of visible and IR lights can achieve a Pearson correlation results between 0.69-0.82 and an RMSE value between 1.26-1.56 g/dL. Our system builds upon the prior work and demonstrates that with only the built-in white LED, the estimation of hemoglobin level has a Pearson correlation of 0.62 with an RMSE of 1.27 g/dL. This extension work demonstrates that it is feasible to measure hemoglobin without using an IR source.