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Title: Accuracy of algorithm to non-invasively predict core body temperature using the kenzen wearable device
Authors: Moyen, Nicole E.
Bapat, Rohit C.
Tan, Beverly 
Hunt, Lindsey A.
Jay, Ollie
Mündel, Toby
Keywords: Extended Kalman filter
Heart rate
Heat illness
Heat injury
Heat stress
Machine learning
Issue Date: 13-Dec-2021
Publisher: MDPI
Citation: Moyen, Nicole E., Bapat, Rohit C., Tan, Beverly, Hunt, Lindsey A., Jay, Ollie, Mündel, Toby (2021-12-13). Accuracy of algorithm to non-invasively predict core body temperature using the kenzen wearable device. International Journal of Environmental Research and Public Health 18 (24) : 13126. ScholarBank@NUS Repository.
Rights: Attribution 4.0 International
Abstract: With climate change increasing global temperatures, more workers are exposed to hotter ambient temperatures that exacerbate risk for heat injury and illness. Continuously monitoring core body temperature (TC ) can help workers avoid reaching unsafe TC . However, continuous TC measurements are currently cost-prohibitive or invasive for daily use. Here, we show that Kenzen’s wearable device can accurately predict TC compared to gold standard TC measurements (rectal probe or gastrointestinal pill). Data from four different studies (n = 52 trials; 27 unique subjects; >4000 min data) were used to develop and validate Kenzen’s machine learning TC algorithm, which uses subject’s real-time physiological data combined with baseline anthropometric data. We show Kenzen’s TC algorithm meets pre-established accuracy criteria compared to gold standard TC: mean absolute error = 0.25? C, root mean squared error = 0.30? C, Pearson r correlation = 0.94, standard error of the measurement = 0.18? C, and mean bias = 0.07? C. Overall, the Kenzen TC algorithm is accurate for a wide range of TC, environmental temperatures (13–43? C), light to vigorous heart rate zones, and both biological sexes. To our knowledge, this is the first study demonstrating a wearable device can accurately predict TC in real-time, thus offering workers protection from heat injuries and illnesses. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Source Title: International Journal of Environmental Research and Public Health
ISSN: 1661-7827
DOI: 10.3390/ijerph182413126
Rights: Attribution 4.0 International
Appears in Collections:Staff Publications

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