Introduction and Objective: The amount and rate of CO2 produced versus O2 consumed, called respiratory quotient (RQ), indicates the type and quantity of metabolic substrate utilized by the body and may be used as a marker of blood glucose estimation. We developed a hand-held device (Breath-AI V3) that measured end tidal breath CO2 along with a finger pulse sensor that captured heart rate and derived oxygen consumption, and built algorithms to explore its potential to estimate blood sugar levels.Methods: The study was conducted in randomly selected 3066 adult male and female subjects residing in urban slums of Pune city who participated in the Pollution Awareness and Wellness Assessment Initiative-2 health screening and awareness study. Breath-AI V3 was used to obtain end tidal CO2 and the pulse sensor recorded heart rate, breath humidity and temperature. Each subject held the Breath-AI V3 device close to the nose for 40-60 seconds, while keeping the middle finger of the hand on the pulse sensor. Blood glucose was measured using the Glucometer device. An AI algorithm was developed based on ETCO2, exhalation time, Heart rate, breath rate to estimate blood glucose levels and was compared with values from Glucometer.Results: Are represented in figureConclusion: The breath-AI device demonstrated good tracking and trending of glucose levels compared to the glucometer and shows potential to develop this device as a cost effective and environment friendly noninvasive glucose monitoring approach.
S. Zambad: Board Member; Thincr Technologies India Private Limited, Virtual Sense Global Technologies Private Limited. S. Salvi: None. M. Barne: None. J.V. Rajendran: None. P. Harkut: None. S. Madas: None. V. Das: None. A. Sable: None. M. Dhawale: None. P. Dudhbhate: Employee; Virtual Sense Global Technologies Pvt Ltd. A. Shaikh: None. A. Gaikwad: None. S. Kale: None. G. Rajvaidya: Employee; Virtual Sense Global Technology Pvt Ltd.
Corporate Social Responsibility Grant from JB Pharmaceuticals and Chemicals Ltd., Mumbai, India.
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