Body Temperature Data Research Articles

Small Scale Aerial Monitoring for Human Body Temperature Measurement Using Rotary Wing Drone

In Indonesia, the COVID-19 pandemic has had an impact on a variety of sectors. Using all available technology for disaster mitigation is critical for pandemic prevention and control. Recent studies have uncovered the advantage of Unmanned Aerial Vehicle (UAV) or drones, particularly those with rotary wings, in dealing with the pandemic. Much effort has been devoted to developing a rotary-wing drone system as a flying platform for aerial monitoring. However, several factors must be considered when visually observing a specific region, i.e., the area's size, topographic contours, locations of special interest inside the area, approach points to the area, and the observation timeframe. Since fever is a common symptom of COVID-19, human body temperature monitoring is highlighted for fever screening, with the objective of minimizing people with high body temperatures going to the crowd. A major challenge is creating a system that can provide accurate body temperature data, which is critical for fighting the pandemic. The purpose of this paper is to present a rotary wing drone application for aerial human body temperature measurements. The paper also proposed an alternative solution based on using a portable, low-cost, Forward-looking Infrared (FLIR) thermal imaging camera. The FLIR thermal camera is incorporated into the drone's electronic system. Furthermore, thermal image data are transmitted into the ground station via a radio telemetry transceiver to allow flexible surveillance by the operator. Indoor and outdoor experiments reveal that the system has been effectively installed and provide data collection for further research. The results show that the system can be used for small-scale area aerial monitoring.

Continuous body temperature as a window into adolescent development

Continuous body temperature is a rich source of information on hormonal status, biological rhythms, and metabolism, all of which undergo stereotyped change across adolescence. Due to the direct actions of these dynamic systems on body temperature regulation, continuous temperature may be uniquely suited to monitoring adolescent development and the impacts of exogenous reproductive hormones or peptides (e.g., hormonal contraception, puberty blockers, gender affirming hormone treatment). This mini-review outlines how traditional methods for monitoring the timing and tempo of puberty may be augmented by markers derived from continuous body temperature. These features may provide greater temporal precision, scalability, and reduce reliance on self-report, particularly in females. Continuous body temperature data can now be gathered with ease across a variety of wearable form factors, providing the opportunity to develop tools that aid in individual, parental, clinical, and researcher awareness and education.

IOT Based Real Time Tele-healthcare System

Tele-healthcare is need of the hour to bridge the vast healthcare gap in developing country like India. Being the second most populous country, quality healthcare facility is not easily accessible in the rural outskirts of India. In this research work the proposed system has acquired ECG, heart rate, SpO2 and body temperature data for better diagnosis and prognosis. The proposed system has been tested on the different patients belonging to different age groups and the result obtained on the health monitoring dashboard is found to be satisfactory. It also provides enhanced accessibility as multiple healthcare professionals can collaborate on the patient's data. This paper concludes with real time audio/ video connectivity, scope of interest of which is very effective and applicable in healthcare world

Light Deep Models for Cognitive Computing in Intelligent Transportation Systems

The paper proposes light convolutional neural network (CNN) models for the use of cognitive networking in an intelligent transportation system (ITS). There are two CNN models, one with 1D convolution and connectors, and the other with a tree-like structure. The 1D CNN model is deployed to process 1D temporal data such as the driver’s body temperature and electrocardiogram (ECG) data to measure emotion, while the deep tree CNN model is used to process image data obtained from car camera sensors. As the driver’s cognitive state can frequently change depending on the situation and location of the car, different edge controllers should handle the car sensors’ data within a short period of time. The tree-based deep learning model that can be branched and processed independently in the edge devices can be executed with less computation. This reduces the load and the time of the execution of the model. The light 1D CNN model has less learnable parameters, and hence can be executed in real-time. The cognitive state of a driver is measured by the facial emotion, body temperature, and ECG signal of the driver. The proposed is tested using a publicly available facial emotion database, and the accuracy and the information density are around 94-96% and 4.4, respectively.

Dairy Cow Thermal Balance Model During Heat Stress: Part 1. Model Development

Highlights Equations for a modified steady-state thermal balance model solved with a spreadsheet are described. The modified model describes heat exchange between lactating cows and the surrounding environment. New relations were used for tissue insulation, sweat rate, longwave radiation, and convective heat exchange. A companion paper compares model results to published body temperatures, respiration rates, and skin temperatures. Abstract. Dairy cow heat stress impacts cow well-being, reduces milk yield, and leads to economic losses. Understanding heat stress mechanics supports ongoing and future efforts to mitigate heat stress. The purpose of this project was to modify a steady-state heat transfer model developed by McGovern and Bruce (2000) by incorporating work by Berman (2005), McArthur (1987), Turnpenny et al. (2000a,b), Thompson et al. (2014), Gwadera et al. (2017), two new empirical relations for tissue insulation and sweat rate, and a new solution method that allowed for overlapping changes in heat exchange. The modified model describes heat exchange between a lactating cow and the environment through respiration, convection, sweating, and shortwave and longwave radiation. This article describes the process-based model equations, compares results from the two new empirical relations used to published work, and presents the inputs and results for a cow on pasture in sunlight. The modified model, which can be solved with a spreadsheet, provides insight into factors and processes that affect lactating cow heat exchange. A companion paper compares the modified model results with published average measured body temperatures, respiration rates, and skin temperatures and unpublished body temperature data for cows on pasture in the sunshine. Keywords: Body temperature, Dairy, Heat stress, Lactating cow, Respiration rate, Thermal balance model.

Distribution of the follicular and luteal phase lengths and their age-dependent changes in Japanese women: A large population study.

The current definition of menstrual cycle length in a Japanese woman is different from those of WHO definition, and the original data are outdated. We aimed to calculate the distribution of follicular and luteal phases length in modern Japanese women with various menstrual cycles. This study determined the lengths of the follicular and luteal phases of Japanese women using basal body temperature data collected via a smartphone application from 2015 to 2019, and the data were analyzed using the Sensiplan method. Over 9 million temperature readings from more than 80 000 participants were analyzed. The mean duration of the low-temperature (follicular) phase averaged 17.1 days and was shorter among participants aged 40-49 years. The mean duration of the high-temperature (luteal) phase was 11.8 days. The variance and maximum-minimum difference of the length of the low temperature period were significant in women under 35 years old than women aged more than 35 years. The shortening of the follicular phase in women aged 40-49 years implied a relationship with the rapid decline of ovarian reserve in these women, and the age 35 years old was turning point of ovulatory function.

Measurement of body temperature in the oral cavity with a temperature sensor integrated with a powered toothbrush

This paper presents a method for collecting core body temperature data via a temperature sensor integrated into a powered toothbrush. The purpose is to facilitate the collection of temperature data without any extended effort from the user. Twelve participants use a powered toothbrush with a temperature sensor mounted on the brush head twice daily for two months. The obtained values are compared with those from a conventional fever thermometer approved for intraoral use. The results show that the temperature sensor–integrated powered toothbrush can measure the core body temperature and provide values comparable to those provided by a traditional oral thermometer. The use of the device can facilitate disease monitoring, fertility control, and security solutions for the elderly.

Determining the different phases of torpor from skin- or body temperature data in heterotherms

Technological innovations have made heat-sensitive data-loggers smaller, more efficient and less expensive, which has led to a growing body of literature that measures the skin- or body temperatures of small animals in their natural environments. Studies of this type on heterothermic endotherms have prompted much debate regarding how to best define ‘torpor’ expressions from skin- or body temperature data alone. We propose a new quantitative method for defining torpor ‘entries’, ‘arousals’ and ‘stable torpor periods’ whilst comparing the results to ‘torpor bout’ durations identified using only the torpor cut-off method. By decomposing a torpor bout into ‘entries’, ‘stable torpor periods’, and ‘active arousals’, we avoid biases introduced by using strict threshold temperature values for the onset of torpor, thereby allowing better insight into individual use of torpor. We present our method as an easy-to-use function written in R-code, offering an un-biased and consistent methodology to be applied on skin- or body temperature measurements across datasets and research groups. When testing the function on a large dataset of skin temperature data collected on three bat species in Norway (Plecotus auritus: Nind = 39; Eptesicus nilssonii: Nind = 11; Myotis brandtii: Nind = 10), we identified 461 complete torpor bouts across species. More than 40% of the torpor bouts (Nbouts = 192) did not contain stable torpor periods, because the bats aroused before they had reached a stable skin temperature level. Furthermore, only considering ‘torpid’ and ‘euthermic’ temperature values by applying strict cut-off thresholds led to potentially large underestimations of torpor bout durations compared to our quantitative determination of the onset and termination of each torpor bout. We highlight the importance of differentiating between torpor phases, especially for active arousals that can be very energetically expensive and may alter our evaluation of the actual energetic savings gained by an individual employing torpor.

Prototype of Body Temperature and Oxygen Saturation Monitoring System Using DS18B20 and MAX30100 Sensors based on IOT

After people died from infections during the COVID-19 epidemic, this attracted a lot of attention. COVID-19 causes symptoms such as fever, headache, sore throat, shortness of breath, and others. Many deaths are asymptomatic, which makes the problem even bigger. Therefore, real-time system monitoring is needed. Monitoring will be carried out about measuring body temperature and oxygen saturation in patients. Monitoring body temperature is necessary because it can detect symptoms of COVID-19 in patients earlier. The concept of the Internet of Things (IoT) is to enable devices to send and receive data over an internet network. The monitoring system to be built uses NodeMCU ESP8266, DS18B20 sensor, and MAX30100 sensor. Data communication is used in the exchange of information using WiFi. Applications made using MIT App Inventor are used to view body temperature and oxygen saturation data. This system is expected to reduce the number of deaths due to COVID-19. DS18B20 sensor has a sensor accuracy of 99,73% and an average error of 0,27%. MAX30100 sensor has an accuracy rate of 99,18% and an average error of 0,82%. Delay test results show an average of 155,57 ms, and packet loss test results show an average of 0%. The result of a system that has been tested said that both sensors can read well.

Cooling Kinetic Characteristics of Temperature Difference between Cadaver Temperature and Ambient Temperature.

To study the cooling reaction kinetic characteristics of the temperature difference between cadaver temperature and ambient temperature (hereinafter referred to as "cadaver temperature difference") according to the reaction kinetics method. Thirty rabbits were randomly divided into 5 groups with 6 rabbits in each group. The rabbits were injected with 10% potassium chloride solution intravenously. After death, the rabbits were placed at 5 ℃, 10 ℃, 15 ℃, 20 ℃ and 25 ℃ environment condition, respectively, and the rectal temperature was measured every minute for 20 hours. The measured cadaver temperature was subtracted from ambient temperature, and the cadaver temperature difference data was calculated using the reaction kinetics formula. The linear regression equation was fitted for analysis, and the experimental results were applied to the temperature difference data of human body after death for verification. Under different environmental conditions, the linear coefficient determination of temperature difference -ln(C/C0) in rabbits was 0.99, showing a good linear relationship with time t. The application of human body temperature data after death was consistent with the results of animal experiments. Under stable conditions, the temperature difference cooling process after death in rabbits is a first-order kinetic response. The method can also be used to study the temperature difference in human body after death.

Endothelial SIRT-1 has a critical role in the maintenance of capillarization in brown adipose tissue

Brown adipose tissue (BAT) has critical roles in thermogenesis and systemic metabolism. Capillary rarefaction was reported to develop in BAT with dietary obesity, and previous studies showed that suppression of vascular endothelial growth factor A (VEGF-A) reduced capillary density in BAT, promoting the functional decline of this organ. Capillarization is regulated through the balance between angiogenesis and vasculogenesis on the one hand and apoptosis of endothelial cells (ECs) on the other; however, the role of EC apoptosis in BAT remained to be explored. In studies testing the role of boysenberry polyphenols (BoyP) in BAT, we found that BoyP decreased EC apoptosis, enhanced capillarization in BAT, and ameliorated dietary BAT dysfunction, which was associated with the upregulation of nicotinamide adenine dinucleotide-dependent protein deacetylase sirtuin 1 (SIRT-1) in ECs. Our studies suggest that EC SIRT-1 would be one of the potential targets of BoyP that contributes to BAT capillarization and function.

Heartbeat and Body Temperature Monitoring System Based on Artificial Neural Networks

Heartbeat and body temperature are vital sign parameters for paramedics in strengthening the diagnosis of a disease. Medical staff generally use an electrocardiogram and thermometer to check the heart rate and body temperature. These tools are still manual and require concentration to get accurate values. This examination system is less useful because it requires a long time to collect data, increasing the burden on medical personnel and rising operational costs. To improve health services optimally, the authors propose the manufacture of heart rate and body temperature monitoring devices for the elderly based on wireless using the Artificial Neural Network (ANN) method. The proposed method can assist medical personnel in diagnosing heart attacks with three conditions (normal, low risk, and high risk). This study aims to assist medical staff in monitoring patients 'health conditions and diagnosing patients' heart disease in real time. This system uses PPG HRM-2511E sensor to detect heart rate and a DS18B20 sensor to detect body temperature. The data detection process uses a raspberry pi, and the decision-making system uses the ANN method. The results of testing the success rate of detecting the heartbeat of 97.90%, and the body temperature of 99.51%. The heart rate and body temperature data processing using ANN went as expected.

A Three-Way Correlation Study for Body Temperature, Glucose and Blood Pressure Using the Collected Biomarker Data of 245 Days Based on GH-Method: Math-Physical Medicine (No. 461)

The author conducted multiple studies regarding the influences of ambient temperatures on his glucoses, including cold weather’s negative influences on fasting plasma glucose (FPG) and hot weather’s positive influences on postprandial plasma glucose (PPG). As a result, he incorporated ambient temperature or weather temperature as one of the ~20 influential factors of glucose formation in his AI-based glucose prediction model. In his presentation at one of the European medical conferences in 2018, one medical doctor in the audience inquired whether his research work was conducted regarding the inter-relationship between body temperature and glucose. Not until 10/1/2020 did the author start to measure his body temperature on a daily basis. As of 6/2/2021, he collected a sufficient amount of his own body temperature data for a period of 8+ months or precisely 245 days. This report covers the triple inter-relationship existing between body temperature versus glucose, body temperature versus blood pressure (BP), and glucose versus BP using simple statistical correlation coefficient calculations.

A Cost Efficient Contactless IoT based Body Temperature Detection System

In the recent outbreak of Covid-19 pandemic, various methods has been adopted to prevent and control the wide spread of pandemic. One of the commonly used method is by detecting the body temperature. This is to isolate those obtained higher body temperature who are possibly infected with the virus. Body temperature detection device is commonly deployed at the entrance of merchants for this purpose. However if one person is detected in one merchant with higher body temperature, this information is not bundled with his/her identity information. Therefore his/her entranced to other merchants are not linked and warned, and causing a possible spread of pandemic if other customers who appeared in the same premises are not being notified. In this work, an IoT based body temperature detection system is developed. In this system, the body temperature data is obtained and sent to the internet cloud together with the identity information of that person. This allow easy tracking of the potential virus infected person. The collected data can be further analysed using online analysis tool. Furthermore, the identity information is obtained using QR code which eliminate the ordinary procedure of writing personal data into logbook. The QR code method is contactless and able to avoid the infection of virus through the contact of pen and logbook. This system is developed with low-cost material and is affordable for small merchants.

Penerapan Algoritma Fuzzy Logic Pada Sistem Pengukur Suhu Tubuh Manusia dan Hand Sanitizer Berbasis Arduino Uno R3 dengan Menggunakan Sensor Proximity

Maintaining health is very important for life, especially during the current Covid-19 pandemic. One of the protocols imposed by the government for people who are active in public spaces or open facilities is to check body temperature and hand sanitizer. In this research, a design for measuring body temperature and automatic hand sanitizer based on Arduino Uno is made which has a reminder alarm if the body temperature is NORMAL if the temperature is 35.8°C – 37.5°C and NOT NORMAL if the temperature is above 37.5°C. Where this tool will work after the hand is brought near to measure the temperature and at the same time issue hand sanitizer using the proximity sensor. Body temperature data is also displayed on the 16x2 (cm) LCD on the device. For data collection techniques, this research was carried out by means of observation and literature in accordance with the problems being studied.

Diagnosis of abnormal body temperature based on deep neural network

INTRODUCTION: A method for diagnosing abnormal body temperature based on deep neural network is proposed. OBJECTIVES: To improve the diagnostic accuracy, reduce the false alarm rate, and improve the diagnostic level of abnormal body temperature. METHODS: According to the weight of the temperature sensor node itself and its neighbor nodes, the network trust relationship is established, and the node trust value is output through the combination of decision-making. Use trust value and double threshold to identify and remove malicious nodes, and optimize the network structure. The optimized temperature sensor network is used to collect human body temperature data. RESULTS: A deep neural network is used to construct a diagnosis model of abnormal body temperature, so as to realize the diagnosis of abnormal body temperature. CONCLUSION: The experimental results show that the method in this paper has high diagnostic accuracy, low false positive rate and high diagnostic efficiency, and can improve the diagnostic level of abnormal body temperature.

Female mice exhibit less overall variance, with a higher proportion of structured variance, than males at multiple timescales of continuous body temperature and locomotive activity records

Despite recent work demonstrating that female rodents and humans do not show greater variance in behavior and physiology than males due to ovulatory cycles, many researchers still default to using males in their investigations. Although government funding agencies now require inclusion of female subjects where applicable, the erroneous belief that the study of males reduces overall data variance continues to result in male subject bias. Recently, we reported the first direct experimental refutation of this belief by examining continuous body temperature and locomotor activity in male and female mice. These findings revealed that males exceeded female variance within and across individuals over time, showing greater variance within a day than females do across an entire estrous cycle. However, the possibility remains that male variance within a day is impacted by ultradian rhythms, analogous to the influence of infradian estrous cycles on female variance, and both sexes show predictable, structured variance across the day. If structures underlying variance can be predicted, then the variance can be statistically accounted for, reducing experimental error and increasing precision of measurements. Here we assess these continuous body temperature and activity data for the contributions of structured and unstructured variance to overall variance within and across individuals at ultradian, circadian, and infradian timescales. In no instance do females exceed male variance, and in most instances male variance exceeds female variance. Additionally, more female variance is accounted for by temporal structure. In conclusion, even when estrous cycles are not controlled for, females show less variability than males, and this advantage can be further capitalized upon by inclusion of known temporal patterns to control for previously unknown but structured sources of variance.

The protective role of wallowing against heat stress in gestating and lactating sows housed outdoors

The objective of this study was to describe the physiological response of gestating and lactating sows to naturally-occurring environmental conditions, and to identify factors that may contribute to or prevent heat stress, while being kept outdoors in Québec, Canada during the summer. Six groups of 4 Yorkshire-Landrace sows lived in outdoor pens equipped with a wallow, shade structure, farrowing huts and access to a pasture from July to September 2018. Between week 15 of gestation and week 3 of lactation (inclusive), we recorded the location of each sow 5 days/week during 5 daily 15-min observation periods, and additionally measured the sow's respiratory rate and mud cover at the end of each observation period. Simultaneously, we collected sow body temperature data with vaginal temperature loggers 24 h/d on week 15 of gestation and week 2 of lactation, and monitored environmental conditions with temperature and humidity loggers to calculate the temperature humidity index (THI). Sows had significantly higher and more variable body temperatures during lactation compared to gestation (P ≤ 0.0001), and when THI was analysed as a continuous variable, it was positively associated with sow body temperature during the night in lactation. During gestation, neither respiratory rate nor body temperature were associated with high or low levels of THI (P = 0.15 and 0.79, respectively) or mud cover (P = 0.29 and 0.94, respectively). However, in lactation, respiratory rate was higher when, simultaneously, THI exceeded 74 and mud cover was low (P = 0.006), while a THI higher than 74 and a low mud cover had independent effects on body temperature (P = 0.012 and 0.004, respectively). In lactation, sows that spent an entire observation period in the farrowing hut also had a higher respiratory rate than sows that left the hut at least once (P = 0.009). In summary, lactating sows were more likely to show increases in respiratory rate and body temperature in warmer conditions than gestating sows, and our findings also suggest that time in the farrowing hut may be a risk factor for heat stress. However, mud cover may limit these physiological consequences when sows have access to a wallow.

P-631 Day Length Predicts Ovulatory Shifts in Women’s Reproductive Function

Abstract Study question Is there a relationship between day length and ovulation rate in women of reproductive age? Summary answer Analysis showed that increasing day length is associated with higher ovulation rate in women of reproductive age in both Sweden and the United States (US). What is known already Historically, winter months have been characterised by threatening survival conditions, such as reduced food availability and lower temperatures. Day length, or photoperiod, provides a reliable indication of upcoming seasonal changes, which promotes season-specific adaptations to behaviours and reproductive systems in mammals. To avoid the survival threats the winter months present, mammals with long gestation periods typically exhibit increased breeding as photoperiods increase. As humans also possess long gestation periods, it may be that humans similarly adapt to increasing photoperiods by exhibiting seasonal shifts in reproductive functioning. Study design, size, duration This retrospective analysis of basal body temperature (BBT) data from the Natural Cycles contraceptive app included approximately 115,000 Natural Cycles users’ data, amounting to approximately 1.3 million cycles from May 2014 - January 2021. BBT was used to confirm ovulation, the rate of which was calculated and compared to the number of hours daylight users experienced based on the geographical location in which they had registered for the app. Participants/materials, setting, methods We exclude cycles with missing data for any of the studied variables leaving ∼180k Swedish and ∼150K US cycles. The Meteostat library supplied the temperature on the start date of each user cycle. The Suntime library was used to determine the number of hours of daylight users were exposed to on the start date of each cycle, which used the geographic coordinates of the users’ reported country of residence. Main results and the role of chance Menstrual Cycle data from approximately 115 thousand Natural Cycles app users aged between 18-62 from two geographic groups, Sweden and the US. Data from cycles during and immediately following the event of a miscarriage, pregnancy, or instance of taking an emergency contraceptive, as well as the two cycles immediately following a completed pregnancy. Using a generalised logistic mixed-effects model, implementation via GPBoost, user-specific variation in ovulation rate as a function of location-specific day length was assessed while controlling for age, cycle length, body mass index (BMI), daily temperature, and education level. We find that day length is significantly correlated with higher ovulation (p < 0.01) in both the US and Swedish cohort. Limitations, reasons for caution Ovulation rate and day length may have emerged as a function a several underlying mechanisms, including the optimisation of conditions for childbirth, the optimisation of conditions for conception and early embryonic development, or a decrease in ovulation during the darker, winter months as a result of investment in immune function. Wider implications of the findings Photoperiod may be an important regulator of human reproductive activity, providing some preliminary evidence of seasonal changes to women’s ovulatory functioning. Furthermore, birth rate as a measurement of seasonal reproductive patterns in humans may not be as stable or accurate a measure for contemporary analyses of women’s reproductive functioning. Trial registration number 000000

Design of a portable low-power wearable heart rate and blood oxygen monitoring system

<p>Heart rate, blood oxygen and body temperature are all important physiological information of human body, and designing a small and portable system measurement device will have a large social and clinical economic benefit. An attempt was made to design a portable monitoring device with STM32F103C8T6 as the controller. The heart rate, blood oxygen and body temperature data are collected by MAX30102 and GYMCU90615 modules and the data are sent to an Android smart phone via Bluetooth module for analysis and display, realizing an Android-based heart rate, blood oxygen and body temperature monitoring system. The system has been tested and verified to be stable and reliable.</p>