INTERNET OF MEDICAL THINGS (IoMT)-BASED HEART RATE AND BODY TEMPERATURE MONITORING SYSTEM

Abstract

Research has been carried out on a heart rate and body temperature monitoring system based on the Internet of Medical Things (IoMT). This study aims to create a system for monitoring heart rate and body temperature remotely in real-time with measurement results displayed on a web server. This research includes several methods such as developing research concepts based on literature studies, system design consisting of hardware and software design, sensor calibration, web server creation, system testing, and direct data retrieval. The hardware manufacturing stage uses several components such as a pulse heart sensor to detect heart rate, DS18B20 sensor to detect body temperature, Arduino Uno microcontroller, Xbee end device, Xbee coordinator, and raspberry pi as a server computer. Then for the use of software on this system, it consists of Arduino Integrated Development Environment (IDE) to run Arduino Uno hardware, XCTU to provide configuration on Xbee, Python to run Raspberry Pi and Django as a framework for building web servers and MySQL as data storage center measurement results. Heart rate monitoring is done by placing a sensor on one of the fingers, and body temperature is done by placing the sensor in the axilla. The output from the sensor in the form of analog data is converted by the Arduino Uno microcontroller into digital data and then sent to the Raspberry Pi module via Xbee. The raspberry pi has processed data is then stored in the database and then displayed on the webserver. The sensor calibration results show that the pulse heart sensor's error rate is 0.41%, and the DS18B20 temperature sensor is 1.09%. After calibration of the sensor, data was collected on the three respondents' heart rate and body temperature. The measurement results show that the system can store each respondent's heart rate and body temperature data in the database and display the measurement results on the webserver in real-time. Based on these results indicate that the system that has been made can work well.

[Retracted] Edge‐Enabled Heart Rate Estimation from Multisensor PPG Signals

“…Heart rate (HR) estimation has been embedded into numerous portable physiological monitoring terminals, such as Internet of Medical Things (IoMT) devices [ 1 ], body area network (BAN) devices [ 2 ], wearable devices [ 3 ], remote video devices [ 4 ], and even smartphones [ 5 , 6 ]. Because of the technological advance of high-performance PPG optical sensors over the years, the PPG technique is employed by more and more IoMT health and wearable devices to monitor our body status.…”

“…Edge computing, as an emerging computing paradigm, provides an innovative opportunity for the synchronized computing of multisensor PPG signals in the proximity of the edge networks. Advancements in edge computing have the desired computing capacities for the rapid development of Internet of Tings (IoT) [1], Internet of Vehicles (IoV) [7,8], Satellite-Terrestrial Networks [9], reconfgurable wireless communications [10], and video streaming processing [11][12][13][14], especially in IoMT. Te explosive proliferation of IoMT generates massive amounts of time-series data, such as PPG signals.…”

“…Consequently, there are several challenges and difculties to be solved in this paper. (1) Te BAs are an inevitable phenomenon for an adult and is a map of the CSA. Due to the presence of the BAs, it increases the probability that an undesired PPG signal is selected.…”

Water Level Monitoring System in Water Utility Company Open Channels Based on Internet of Things

“…IoT connects things through the internet and supports human work and encourages the formation of the industrial revolution 4.0 concepts [7,8]. IoT can also be applied to identify, track, and monitor remotely [9]. Currently, a WSN system has been developed that supports fast measurements and accurate results built through the integration of IoT with sensors [7].…”