Open Access
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
Author(s) -
Pali Madhavi,
Jagannath Badrinath,
Lin KaiChun,
Sankhala Devangsingh,
Upasham Sayali,
Muthukumar Sriram,
Prasad Shalini
Publication year - 2021
Publication title -
bioengineering and translational medicine
Language(s) - English
Resource type - Journals
ISSN - 2380-6761
DOI - 10.1002/btm2.10241
Subject(s) - sweat , wearable computer , medicine , reference range , power consumption , computer science , endocrinology , power (physics) , embedded system , physics , quantum mechanics
Abstract W earable A wareness T hrough C ontinuous H idrosis (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 ˷5.10–5.15% further confirmed the statistical robustness of the sweat sensing WATCH device output.