A machine learning-based on-demand sweat glucose reporting platform.

Diabetes is a chronic endocrine disease that occurs due to an imbalance in glucose levels and altering carbohydrate metabolism. It is a leading cause of morbidity, resulting in a reduced quality of life even in developed societies, primarily affected by a sedentary lifestyle and often leading to mortality. Keeping track of blood glucose levels noninvasively has been made possible due to diverse breakthroughs in wearable sensor technology coupled with holistic digital healthcare. Efficient glucose management has been revolutionized by the development of continuous glucose monitoring sensors and wearable, non/minimally invasive devices that measure glucose concentration by exploiting different physical principles, e.g., glucose oxidase, fluorescence, or skin dielectric properties, and provide real-time measurements every 1-5 min. This paper presents a highly novel and completely non-invasive sweat sensor platform technology that can measure and report glucose concentrations from passively expressed human eccrine sweat using electrochemical impedance spectroscopy and affinity capture probe functionalized sensor surfaces. The sensor samples 1-5 µL of sweat from the wearer every 1-5 min and reports sweat glucose from a machine learning algorithm that samples the analytical reference values from the electrochemical sweat sensor. These values are then converted to continuous time-varying signals using the interpolation methodology. Supervised machine learning, the decision tree regression algorithm, shows the goodness of fit R2 of 0.94 was achieved with an RMSE value of 0.1 mg/dL. The output of the model was tested on three human subject datasets. The results were able to capture the glucose progression trend correctly. Sweet sensor platform technology demonstrates a dynamic response over the physiological sweat glucose range of 1-4 mg/dL measured from 3 human subjects. The technology described in the manuscript shows promise for real-time biomarkers such as glucose reporting from passively expressed human eccrine sweat.

Temporal profiling of cytokines in passively expressed sweat for detection of infection using wearable device.

This work presents the viability of passive eccrine sweat as a functional biofluid toward tracking the human body's inflammatory response. Cytokines are biomarkers that orchestrate the manifestation and progression of an infection/inflammatory event. Hence, noninvasive, real-time monitoring of cytokines can be pivotal in assessing the progression of infection/inflammatory event, which may be feasible through monitoring of host immune markers in eccrine sweat. This work is the first experimental proof demonstrating the ability to detect inflammation/infection such as fever, FLU directly from passively expressed sweat in human subjects using a wearable "SWEATSENSER" device. The developed SWEATSENSER device demonstrates stable, real-time monitoring of inflammatory cytokines in passive sweat. An accuracy of >90% and specificity >95% was achieved using SWEATSENSER for a panel of cytokines (interleukin-6, interleukin-8, interleukin-10, and tumor necrosis factor-α) over an analytical range of 0.2-200 pg mL-1. The SWEATSENSER demonstrated a correlation of Pearson's r > 0.98 for the study biomarkers in a cohort of 26 subjects when correlated with standard reference method. Comparable IL-8 levels (2-15 pg mL-1) between systemic circulation (serum) and eccrine sweat through clinical studies in a cohort of 15 subjects, and the ability to distinguish healthy and sick (infection) cohort using inflammatory cytokines in sweat provides pioneering evidence of the SWEATSENSER technology for noninvasive tracking of host immune response biomarkers. Such a wearable device can offer significant strides in improving prognosis and provide personalized therapeutic treatment for several inflammatory/infectious diseases.

Tracking metabolic responses based on macronutrient consumption: A comprehensive study to continuously monitor and quantify dual markers (cortisol and glucose) in human sweat using WATCH sensor.

Wearable Awareness Through Continuous Hidrosis (WATCH) sensor is a sweat based monitoring platform that tracks cortisol and glucose for the purpose of understanding metabolic responses related to macronutrient consumption. In this research article, we have demonstrated the ability of tracking these two biomarkers in passive human sweat over a workday period (8 h) for 10 human subjects in conjunction with their macronutrient consumption. The validation of the WATCH sensor performance was carried out via standard reference methods such as Luminex and ELISA This is a first demonstration of a passive sweat sensing technology that can detect interrelated dual metabolites, cortisol, and glucose, on a single sensing platform. The significance of detecting the two biomarkers simultaneously is that capturing the body's metabolic and endocrinal responses to dietary triggers can lead to improved lifestyle management. For sweat cortisol, we achieved a detection limit of 1 ng/ml (range ∼1-12.5 ng/ml) with Pearson's "r" of 0.897 in reference studies and 0.868 in WATCH studies. Similarly, for sweat glucose, we achieved a detection limit of 1 mg/dl (range ∼ 1-11 mg/dl) with Pearson's "r" of 0.968 in reference studies and 0.947 in WATCH studies, respectively. The statistical robustness of the WATCH sensor was established through the Bland-Altman analysis, whereby the sweat cortisol and sweat glucose levels are comparable to the standard reference method. The probability distribution (t-test), power analysis (power 0.82-0.87), α = 0.05. Mean absolute relative difference (MARD) outcome of Ë·5.10-5.15% further confirmed the statistical robustness of the sweat sensing WATCH device output.

A Rapid Response Electrochemical Biosensor for Detecting Thc In Saliva.

Marijuana is listed as a Schedule I substance under the American Controlled Substances Act of 1970. As more U.S. states and countries beyond the U.S. seek legalization, demands grow for identifying individuals driving under the influence (DUI) of marijuana. Currently no roadside DUI test exists for determining marijuana impairment, thus the merit lies in detecting the primary and the most sought psychoactive compound tetrahydrocannabinol (THC) in marijuana. Salivary THC levels are correlated to blood THC levels making it a non-invasive medium for rapid THC testing. Affinity biosensing is leveraged for THC biomarker detection through the chemical reaction between target THC and THC specific antibody to a measure signal output related to the concentration of the targeted biomarker. Here, we propose a novel, rapid, electrochemical biosensor for the detection of THC in saliva as a marijuana roadside DUI test with a lower detection limit of 100 pg/ml and a dynamic range of 100 pg/ml - 100 ng/ml in human saliva. The developed biosensor is the first of its kind to utilize affinity-based detection through impedimetric measurements with a rapid detection time of less than a minute. Fourier transform infrared spectroscopy analysis confirmed the successful immobilization of the THC immobilization assay on the biosensing platform. Zeta potential studies provided information regarding the stability and the electrochemical behavior of THC immunoassay in varying salivary pH buffers. We have demonstrated stable, dose dependent biosensing in varying salivary pH's. A binary classification system demonstrating a high general performance (AUC = 0.95) was employed to predict the presence of THC in human saliva. The biosensor on integration with low-power electronics and a portable saliva swab serves as a roadside DUI hand-held platform for rapid identification of THC in saliva samples obtained from human subjects.

AWARE: A Wearable Awareness with Real-time Exposure, for monitoring alcohol consumption impact through ethyl glucuronide detection.

Here we demonstrate for the first time a dynamic monitoring of the ethanol metabolite ethyl glucuronide (EtG) for a more robust evaluation of alcohol consumption, compared to conventional methods. A wearable biosensor device capable of reporting EtG levels in sweat continuously via low power impedance spectroscopy is reported. The custom hardware was compared against a conventional benchtop potentiostat, and demonstrated comparable results in the application of EtG detection in low volume sweat. The device successfully differentiated three distinct EtG concentrations correlating to simulated drinking scenarios estimated to be 1, 2, and 3 standard U.S. drinks consumed over a duration of 60 min, with p < 0.0001. This device has the potential to enable moderate drinkers to engage in guided decision-making, based on objective data, to address the needs of alcohol-sensitive populations. The device also will serve as a tool for researchers to better understand and characterize the relationship between sweat EtG and consumed alcohol.

A Four-Channel Electrical Impedance Spectroscopy Module for Cortisol Biosensing in Sweat-Based Wearable Applications.

A four-channel electrochemical impedance spectroscopy (EIS) analyzer module has been demonstrated on flexible chemi-impedance sensors fabricated with gold electrodes for wearable applications. The module can perform time division multiplexed (TDM) impedance measurements on four sensors at 1 kHz. In this work, we characterize the system for the detection of cortisol in an ultralow volume (1-3 µL) of perspired human sweat, sensor performance, and effects during continuous cortisol dosing and with pH and temperature variations expected on the surface of the skin that would be representative of use conditions as seen by a wearable device. Detection of cortisol was shown for concentrations of 1 pg/mL to 200 ng/mL in both synthetic and perspired human sweat, and output response reported as a change in impedance with varying cortisol concentrations. Continuous dose testing was performed to demonstrate the stability of the sensors over prolonged periods of operation for cortisol concentrations within the physiologically relevant range of 10-200 ng/mL reported in human sweat. Temperature and pH effects testing was performed for pH range 4-8 and in a temperature chamber for the clinical range reported on the surface of human skin: 25-40 °C. The cortisol sensor demonstrated stability of operation with 7.58% variability under these conditions.