Gauging Ambient Environmental Carbon Dioxide Concentration Solely Using Biometric Observations: A Machine Learning Approach

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Shisir Ruwali Bharana Ashen Fernando Shawhin Talebi Lakitha Wijeratne John Waczak Vinu Sooriyaarachchi Prabuddha Hathurusinghe David J. Lary John Sadler Tatiana Lary Matthew Lary Adam Aker


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

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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: <>. Date accessed: 03 mar. 2024. doi:
Research Articles


[1] NHLBI, “How the lungs work,” 2022. health/lungs, Last accessed on 2023-05-11.

[2] WHO, “Air pollution,” 2023. air pollution#tab=tab_1, Last accessed on 2023-05-11.

[3] M. Kampa and E. Castanas, “Human health effects of air pollution,” Environmental Pollution, vol. 151, no. 2, pp. 362–367, 2008.

[4] J. R. Balmes, J. M. Fine, and D. Sheppard, “Symptomatic bronchoconstriction after short-term inhalation of sulfur dioxide1, 2,” Am Rev Respir Dis, vol. 136, no. 11171121, pp. 10–1164, 1987.

[5] N. Uysal and R. M. Schapira, “Effects of ozone on lung function and lung diseases,” Current opinion in pulmonary medicine, vol. 9, no. 2, pp. 144–150, 2003.

[6] J. Kagawa, “Evaluation of biological significance of nitrogen oxides exposure,” The Tokai journal of experimental and clinical medicine, vol. 10, no. 4, pp. 348–353, 1985.

[7] D. G. Badman and E. R. Jaff´e, “Blood and air pollution; state of knowledge and research needs,” Otolaryngology–Head and Neck Surgery, vol. 114, no. 2, pp. 205–208, 1996.

[8] K. Ewan and R. Pamphlett, “Increased inorganic mercury in spinal motor neurons following chelating agents.,” Neurotoxicology, vol. 17, no. 2, pp. 343–349, 1996.

[9] M. Loghman-Adham, “Renal effects of environmental and occupational lead exposure.,” Environmental health perspectives, vol. 105, no. 9, pp. 928–939, 1997.

[10] D. B. Menzel, “The toxicity of air pollution in experimental animals and humans: the role of oxidative stress,” Toxicology letters, vol. 72, no. 1-3, pp. 269–277, 1994.

[11] S. Talebi, D. J. Lary, L. O. H. Wijeratne, B. Fernando, T. Lary, M. Lary, J. Sadler, A. Sridhar, J. Waczak, A. Aker, and Y. Zhang, “Decoding physical and cognitive impacts of particulate matter concentrations at ultra-fine scales,” Sensors, vol. 22, no. 11, 2022.

[12] L. Kajt´ar and L. Herczeg, “Influence of carbon-dioxide concentration on human well-being and intensity of mental work,” QJ Hung. Meteorol. Serv, vol. 116, no. 2, pp. 145–169, 2012.

[13] U. Satish, M. J. Mendell, K. Shekhar, T. Hotchi, D. Sullivan, S. Streufert, and W. J. Fisk, “Is co2 an indoor pollutant? direct effects of low-to-moderate co2 concentrations on human decision-making performance,” Environmental health perspectives, vol. 120, no. 12, pp. 1671– 1677, 2012.

[14] X. Zhang, P. Wargocki, and Z. Lian, “Physiological responses during exposure to carbon dioxide and bioeffluents at levels typically occurring indoors,” Indoor air, vol. 27, no. 1, pp. 65–77, 2017.

[15] P. H. Sechzer, L. D. Egbert, H. W. Linde, D. Y. Cooper, R. D. Dripps, and H. L. Price, “Effect of co2 inhalation on arterial pressure, ecg and plasma catecholamines and 17-oh corticosteroids in normal man,” Journal of Applied Physiology, vol. 15, no. 3, pp. 454–458, 1960. PMID: 14444401.

[16] LI-COR, “Introduction to the instruments,” 2023., Last accessed on 2023-08-20

[17] Cognionics, “Products,” 2023. products, Last accessed on 2023-08-20.

[18] Cognionics, “Cgx aim physiological monitors,” 2023., Last accessed on 2023-08-26.

[19] Tobii, “Tobii pro glasses 2,” 2023. discontinued/tobii-pro-glasses-2,
Last accessed on 2023-08-27.

[20] M. Soufineyestani, D. Dowling, and A. Khan, “Electroencephalography (eeg) technology applications and available devices,” Applied Sciences, vol. 10, no. 21, 2020.

[21] J. N. Acharya, A. J. Hani, J. Cheek, P. Thirumala, and T. N. Tsuchida, “American clinical neurophysiology society guideline 2: guidelines for standard electrode position nomenclature,” The Neurodiagnostic Journal, vol. 56, no. 4, pp. 245–252, 2016.

[22] P. Virtanen, R. Gommers, T. E. Oliphant, M. Haberland, T. Reddy, D. Cournapeau, E. Burovski, P. Peterson, W. Weckesser, J. Bright, S. J. van der Walt, M. Brett, J. Wilson, K. J. Millman, N. Mayorov, A. R. J. Nelson, E. Jones, R. Kern, E. Larson, C. J. Carey, I˙. Polat, Y. Feng, E. W. Moore, J. VanderPlas, D. Laxalde, J. Perktold, R. Cimrman, I. Henriksen, E. A. Quintero, C. R. Harris, A. M. Archibald, A. H. Ribeiro, F. Pedregosa, P. van Mulbregt, and SciPy 1.0 Contributors, “SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,” Nature Methods, vol. 17, pp. 261–272, 2020.

[23] John Hopkins Medicine, “Electrocardiogram,” 2023. https://www. electrocardiogram, Last accessed on 2023-08-26.

[24] W. B. Albert and T. S. T. Tullis, “Chapter 8 - measuring emotion,” in Measuring the User Experience (Third Edition) (W. B. Albert and T. S. T. Tullis, eds.), Interactive Technologies, pp. 195–216, Morgan Kaufmann, third edition ed., 2023.

[25] A. Jubran, “Pulse oximetry,” Critical care, vol. 3, pp. 1–7, 1999.

[26] L. Breiman, “Random forests,” Machine learning, vol. 45, pp. 5–32, 2001.

[27] F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay, “Scikit-learn: Machine learning in Python,” Journal of Machine Learning Research, vol. 12, pp. 2825–2830, 2011.

[28] S. M. Lundberg and S.-I. Lee, “A unified approach to interpreting model predictions,” in Advances in Neural Information Processing Systems (I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, eds.), vol. 30, Curran Associates, Inc., 2017.

[29] S. M. Lundberg, G. Erion, H. Chen, A. DeGrave, J. M. Prutkin, B. Nair, R. Katz, J. Himmelfarb, N. Bansal, and S.-I. Lee, “From local explanations to global understanding with explainable ai for trees,” Nature Machine Intelligence, vol. 2, no. 1, pp. 2522–5839, 2020.

[30] T. pandas development team, “pandas-dev/pandas: Pandas,” Feb. 2020.

[31] Wes McKinney, “Data Structures for Statistical Computing in Python,” in Proceedings of the 9th Python in Science Conference (St´efan van der Walt and Jarrod Millman, eds.), pp. 56 – 61, 2010.

[32] S. D. Goldinger and M. H. Papesh, “Pupil dilation reflects the creation and retrieval of memories,” Current directions in psychological science, vol. 21, no. 2, pp. 90–95, 2012.

[33] P. van der Wel and H. Van Steenbergen, “Pupil dilation as an index of effort in cognitive control tasks: A review,” Psychonomic bulletin & review, vol. 25, pp. 2005–2015, 2018.

[34] R. W. Bullard, “Effects of carbon dioxide inhalation on sweating,” Journal of applied physiology, vol. 19, no. 1, pp. 137–141, 1964.

[35] K. H. Jawabri and S. Sharma, Physiology, Cerebral Cortex Functions. Treasure Island (FL): StatPearls Publishing, 2023.

[36] X. Jiang, G.-B. Bian, and Z. Tian, “Removal of artifacts from eeg signals: a review,” Sensors, vol. 19, no. 5, p. 987, 2019.