Body temperature predicting Patch-Type telemedicine system

Woo, Seung Han; Din, Zia Mohy Ud; Lee, Jang Woo; Jung, Eui Sung; Seong, Ki Woong; Lim, Hyung Gyu; Bae, Tae Wuk; Lee, Jyung Hyun; Won, Chul Ho; Cho, Jin Ho

doi:10.1587/elex.6.1161

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…However, the equipment highly professional was not suitable for continuous monitoring and long term. Lately, Woo et al [38] have used a patch-type device that put on the skin over the clavicle measured humidity and skin temperature from which they predicted the body temperature. With an algorithm, they studied the relationship between perspiration rate and skin temperature to predict the body temperature; the error committed makes the method unreliable.…”

Section: Core Body Temperature Wireless Monitoringmentioning

confidence: 99%

"Development Plan for the Project: Integrated System for Patient Localization, Tracking and Monitoring in an Indoor Environment"

Bibbò

2022

OAJBS

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Currently, the health care problem for older people is becoming of considerable size and involves the whole civilized world. The number of people in need of assistance is constantly growing due to life extension, and the social cost is becoming unsustainable. Technological evolution and IT development can help contain spending by providing efficient health services and improving the quality of life. This article highlights methodological and technical aspects to support the development of an integrated system for locating and monitoring people in their homes or nursing homes. This system complements the home care service by avoiding hospitalization in health facilities with more significant financial burdens.

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Section: Core Body Temperature Wireless Monitoringmentioning

confidence: 99%

"Development Plan for the Project: Integrated System for Patient Localization, Tracking and Monitoring in an Indoor Environment"

Bibbò

2022

OAJBS

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“…The prediction of CBT through chest measurement requires professional equipments for longer-term and continuous monitoring in natural habitats or daily environment. While, the prediction ST with and without external parameters i.e (humadity) was performed with a patch-type device (PTD) attached over the clavicle point of skin [15]. Although the relationship between perspiration rate and ST was also focused to monitor and measure the temperature but the applied PTD was not feasible for long-term use as the monitoring error was 15% larger than the commercial device.…”

Section: Emotional Statesmentioning

confidence: 99%

Design of a contactless body temperature measurement system using Arduino

Rahimoon

Abdullah

Taib

2020

IJEECS

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<span lang="EN-US">The recent advances in electronics and microelectronics devices allow the development of newly low-cost monitoring tools used by peoples for health preventive purposes. Sensors used in medical equipments convert various forms of human body vital signs into electrical signals. Therefore, the healthcare monitoring systems considering non-invasive and wearable sensors with integrated communication mediums allow an efficient solution to live a comfortable home life. This paper presents the remote monitoring of human body temperature (HBT) wirelessly by means of Arduino controller with different sensors and open source internet connection. The proposed monitoring system uses an internet network via wireless fieldity (wifi) connection to be linked with online portal on smart phone or computer. The proposed system is comprised of an Arduino controller, LM-35 (S1), MLX-90614 (S2) temperature sensors and ESP-wifi shield module. The obtained result has shown that real time temperature monitoring data can be transferred to authentic observer by utilizing internet of things (IoT) applications. The findings from this research indicates that the difference of average temperature in between Sensor S1 and S2 is about 15 <sup>0</sup>C</span>

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“…Lately, Woo et al proposed a patch-type device that attaches to the skin over the clavicle for measuring skin temperature and humidity and thus to predict the body temperature [15]. The researchers studied the relationship between perspiration rate and skin temperature and used the data to estimate the body temperature.…”

Section: Introductionmentioning

confidence: 99%

Development of a Wireless Health Monitoring System for Measuring Core Body Temperature from the Back of the Body

Wei

Park

Lee

2019

Journal of Healthcare Engineering

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In this paper, a user-friendly and low-cost wireless health monitoring system that measures skin temperature from the back of the body for monitoring the core body temperature is proposed. To measure skin temperature accurately, a semiconductor-based microtemperature sensor with a maximum accuracy of ±0.3°C was chosen and controlled by a high-performance/low-power consumption Acorn-Reduced Instruction Set Computing Machine (ARM) architecture microcontroller to build the temperature measuring device. Relying on a 2.4 GHz multichannel Gaussian frequency shift keying (GFSK) RF communication technology, up to 100 proposed temperature measuring devices can transmit the data to one receiver at the same time. The shell of the proposed wireless temperature-measuring device was manufactured via a 3D printer, and the device was assembled to conduct the performance tests and in vivo experiments. The performance test was conducted with a K-type temperature sensor in a temperature chamber to observe temperature measurement performance. The results showed an error value between two devices was less than 0.1°C from 25 to 40°C. For the in vivo experiments, the device was attached on the back of 10 younger male subjects to measure skin temperature to investigate the relationship with ear temperature. According to the experimental results, an algorithm based on the curve-fitting method was implemented in the proposed device to estimate the core body temperature by the measured skin temperature value. The algorithm was established as a linear model and set as a quadratic formula with an interpolant and with each coefficient for the equation set with 95% confidence bounds. For evaluating the goodness of fit, the sum of squares due to error (SSE), R-square, adjusted R-square, and root mean square error (RMSE) values were 33.0874, 0.0212, 0.0117, and 0.3998, respectively. As the experimental results have shown, the mean value for an error between ear temperature and estimated core body temperature is about ±0.19°C, and the mean bias is 0.05 ± 0.14°C when the subjects are in steady status.

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Body temperature predicting Patch-Type telemedicine system

Cited by 3 publications

References 7 publications

"Development Plan for the Project: Integrated System for Patient Localization, Tracking and Monitoring in an Indoor Environment"

"Development Plan for the Project: Integrated System for Patient Localization, Tracking and Monitoring in an Indoor Environment"

Design of a contactless body temperature measurement system using Arduino

Development of a Wireless Health Monitoring System for Measuring Core Body Temperature from the Back of the Body

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