Gauging Ambient Environmental Carbon Dioxide Concentration Solely Using Biometric Observations: A Machine Learning Approach
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Jan 30, 2024
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Abstract
Respiration is vital for human function. Inhaling specific gases can have specific physiological and cognitive impacts. Using a suite of sensors, we can collect detailed information on a range of both physiological and environmental factors. This study builds on previous research exploring how particulate matter affects physiological and cognitive responses, now expanded to include CO2. We tracked the biometric variables of a cyclist, analyzing 329 specific variables. Simultaneously, an electric vehicle following the cyclist measured CO2 and other environmental factors. After data collection, we used machine learning models to decipher the interactions between the human body and its surroundings. We found that biometric data alone could be used to accurately estimate the amount of CO2 inhaled, achieving a good level of precision (r2=0.98) when comparing the estimated CO2 based on biometrics and the actual observed CO2 levels. In addition, we developed a ranking system to identify the biometric variables that most significantly predict environmental CO2 inhalation.
Keywords:
Machine learning, biometric, particulate matter, cognitive, CO2
Article Details
How to Cite
RUWALI, Shisir et al.
Gauging Ambient Environmental Carbon Dioxide Concentration Solely Using Biometric Observations: A Machine Learning Approach.
Medical Research Archives, [S.l.], v. 12, n. 1, jan. 2024.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/4890>. Date accessed: 23 nov. 2024.
doi: https://doi.org/10.18103/mra.v12i1.4890.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
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