scholarly journals Accuracy of Algorithm to Non-Invasively Predict Core Body Temperature Using the Kenzen Wearable Device

2021 ◽  
Vol 18 (24) ◽  
pp. 13126
Author(s):  
Nicole E. Moyen ◽  
Rohit C. Bapat ◽  
Beverly Tan ◽  
Lindsey A. Hunt ◽  
Ollie Jay ◽  
...  
Keyword(s):  
Body Temperature ◽  
Real Time ◽  
Gold Standard ◽  
Mean Squared Error ◽  
Core Body Temperature ◽  
Absolute Error ◽  
Wearable Device ◽  
Physiological Data ◽  
Wide Range ◽  
Core Body

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.

scholarly journals Using implantable biosensors and wearable scanners to monitor dairy cattle's core body temperature in real-time

2020 ◽  
Vol 174 ◽  
pp. 105453
Author(s):  
Hanwook Chung ◽  
Jingjie Li ◽  
Younghyun Kim ◽  
Jennifer M.C. Van Os ◽  
Sabrina H. Brounts ◽  
...  
Keyword(s):  
Body Temperature ◽  
Real Time ◽  
Core Body Temperature ◽  
Implantable Biosensors ◽  
Core Body

A Real-Time Case Study in Driver Science: Physiological Strain and Related Variables

2015 ◽  
Vol 10 (8) ◽  
pp. 1058-1060 ◽  
Author(s):  
Edward S. Potkanowicz
Keyword(s):  
Body Temperature ◽  
Real Time ◽  
Core Body Temperature ◽  
Time Data ◽  
Physiological Strain ◽  
Physiological Strain Index ◽  
Probe System ◽  
Future Work ◽  
Core Body

This case study was conducted as an attempt to quantify racecar-driver core body temperature and heart rate (HR) in real time on a minute-by-minute basis and to expand the volume of work in the area of driver science. Three drivers were observed during a 15-lap, 25-min maximal event. Each driver competed in the closed-wheel, closed-cockpit sports-car category. Data on core body temperature and HR were collected continuously using the HQ Inc. ingestible core probe system and HR monitoring. Driver 1 pre- and postrace core temperatures were 37.80°C and 38.79°C, respectively. Driver 2 pre- and postrace core temperatures were 37.41°C and 37.99°C. Driver 1 pre- and postrace HRs were 102 and 161 beats/min. Driver 2 pre- and postrace HRs were 94.3 and 142 beats/min. Driver 1’s physiological strain index (PSI) at the start was 3.51. Driver 2’s PSI at the start was 3.10. Driver 1 finished with a PSI of 7.04 and driver 2 with a PSI of 3.67. Results show that drivers are continuously challenged minute by minute. In addition, before getting into their cars, the drivers already experience physiological and thermal challenges. The data suggest that drivers are getting hot quickly. In longer events, this represents the potential for severe heat injury. Investigating whether the HRs observed are indicative of work or evidence of a thermoregulatory-associated challenge is a direction for future work. The findings support the value of real-time data collection and offer strong evidence for the expansion of research on driver-athletes.

scholarly journals Novel Analytic Methods Needed for Real-Time Continuous Core Body Temperature Data

2016 ◽  
Vol 39 (1) ◽  
pp. 95-111 ◽  
Author(s):  
Vicki Hertzberg ◽  
Valerie Mac ◽  
Lisa Elon ◽  
Nathan Mutic ◽  
Abby Mutic ◽  
...  
Keyword(s):  
Data Analysis ◽  
Body Temperature ◽  
Real Time ◽  
Time Course ◽  
Core Body Temperature ◽  
Heat Exposure ◽  
Threshold Limit Value ◽  
Limit Value ◽  
Novel Approach ◽  
Core Body

Affordable measurement of core body temperature (Tc) in a continuous, real-time fashion is now possible. With this advance comes a new data analysis paradigm for occupational epidemiology. We characterize issues arising after obtaining Tc data over 188 workdays for 83 participating farmworkers, a population vulnerable to effects of rising temperatures due to climate change. We describe a novel approach to these data using smoothing and functional data analysis. This approach highlights different data aspects compared with describing Tc at a single time point or summaries of the time course into an indicator function (e.g., did Tc ever exceed 38 °C, the threshold limit value for occupational heat exposure). Participants working in ferneries had significantly higher Tc at some point during the workday compared with those working in nurseries, despite a shorter workday for fernery participants. Our results typify the challenges and opportunities in analyzing Big Data streams from real-time physiologic monitoring.

scholarly journals Perinatal Infection: A Major Contributor to Efficacy of Cooling in Newborns Following Birth Asphyxia

2021 ◽  
Vol 22 (2) ◽  
pp. 707
Author(s):  
Jibrin Danladi ◽  
Hemmen Sabir
Keyword(s):  
Gene Expression ◽  
Heat Shock ◽  
Body Temperature ◽  
Therapeutic Hypothermia ◽  
Cold Shock ◽  
Core Body Temperature ◽  
Cold Shock Protein ◽  
Perinatal Infection ◽  
Wide Range ◽  
Core Body

Neonatal encephalopathy (NE) is a global burden, as more than 90% of NE occurs in low- and middle-income countries (LMICs). Perinatal infection seems to limit the neuroprotective efficacy of therapeutic hypothermia. Efforts made to use therapeutic hypothermia in LMICs treating NE has led to increased neonatal mortality rates. The heat shock and cold shock protein responses are essential for survival against a wide range of stressors during which organisms raise their core body temperature and temporarily subject themselves to thermal and cold stress in the face of infection. The characteristic increase and decrease in core body temperature activates and utilizes elements of the heat shock and cold shock response pathways to modify cytokine and chemokine gene expression, cellular signaling, and immune cell mobilization to sites of inflammation, infection, and injury. Hypothermia stimulates microglia to secret cold-inducible RNA-binding protein (CIRP), which triggers NF-κB, controlling multiple inflammatory pathways, including nod-like receptor family pyrin domain containing 3 (NLRP3) inflammasomes and cyclooxygenase-2 (COX-2) signaling. Brain responses through changes in heat shock protein and cold shock protein transcription and gene-expression following fever range and hyperthermia may be new promising potential therapeutic targets.

Circadian Rhythm Estimation by Core Body Temperature Filtered with Simultaneously Recorded Physiological Data

1997 ◽  
Vol 36 (04/05) ◽  
pp. 306-310 ◽  
Author(s):  
T. Nakano ◽  
E. Koyama ◽  
T. Imai ◽  
H. Hagiwara
Keyword(s):  
Heart Rate ◽  
Circadian Rhythm ◽  
Body Temperature ◽  
Core Body Temperature ◽  
Field Measurements ◽  
Physical Activities ◽  
Temperature Data ◽  
Physiological Data ◽  
Heart Rate Data ◽  
Core Body

Abstract.In field measurements, monitoring of core body temperature is influenced by physical activities; therefore, the estimation of circadian rhythm from the data may not be exact. The purpose of this study is to design a core body temperature filter in order to reduce artifacts induced by physical activities using simultaneously recorded physiological data such as heart rate data.The effects of physical activities on core body temperature and heart rate are assessed through three experiments. Based on the above knowledge, a core body temperature filter was designed. The filter removes part of rectal temperature data as artifact when heart rate rises above a predetermined threshold. As a result, most of the spike-like noise was removed and the filtered temperature data showed sinusoidal variation more than the unfiltered data. The mesor of the estimated rhythm significantly decreased. This filtering method can provide more precise information about circadian rhythm, especially in field measurements.

scholarly journals Individualized estimation of human core body temperature using noninvasive measurements

2018 ◽  
Vol 124 (6) ◽  
pp. 1387-1402 ◽  
Author(s):  
Srinivas Laxminarayan ◽  
Vineet Rakesh ◽  
Tatsuya Oyama ◽  
Josh B. Kazman ◽  
Ran Yanovich ◽  
...  
Keyword(s):  
Physical Activity ◽  
Body Temperature ◽  
Real Time ◽  
Environmental Variables ◽  
Injury Risk ◽  
Core Body Temperature ◽  
Model Parameters ◽  
Heat Injury ◽  
Noninvasive Measurements ◽  
Core Body

A rising core body temperature (Tc) during strenuous physical activity is a leading indicator of heat-injury risk. Hence, a system that can estimate Tc in real time and provide early warning of an impending temperature rise may enable proactive interventions to reduce the risk of heat injuries. However, real-time field assessment of Tc requires impractical invasive technologies. To address this problem, we developed a mathematical model that describes the relationships between Tc and noninvasive measurements of an individual’s physical activity, heart rate, and skin temperature, and two environmental variables (ambient temperature and relative humidity). A Kalman filter adapts the model parameters to each individual and provides real-time personalized Tc estimates. Using data from three distinct studies, comprising 166 subjects who performed treadmill and cycle ergometer tasks under different experimental conditions, we assessed model performance via the root mean squared error (RMSE). The individualized model yielded an overall average RMSE of 0.33 (SD = 0.18)°C, allowing us to reach the same conclusions in each study as those obtained using the Tc measurements. Furthermore, for 22 unique subjects whose Tc exceeded 38.5°C, a potential lower Tc limit of clinical relevance, the average RMSE decreased to 0.25 (SD = 0.20)°C. Importantly, these results remained robust in the presence of simulated real-world operational conditions, yielding no more than 16% worse RMSEs when measurements were missing (40%) or laden with added noise. Hence, the individualized model provides a practical means to develop an early warning system for reducing heat-injury risk. NEW & NOTEWORTHY A model that uses an individual’s noninvasive measurements and environmental variables can continually “learn” the individual’s heat-stress response by automatically adapting the model parameters on the fly to provide real-time individualized core body temperature estimates. This individualized model can replace impractical invasive sensors, serving as a practical and effective surrogate for core temperature monitoring.

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