Internet of things–based vital sign monitoring system

Alamsyah, Alamsyah; Subito, Mery; Ikhlayel, Mohammad; Setijadi, Eko

doi:10.11591/ijece.v10i6.pp5891-5898

Cited by 12 publications

(8 citation statements)

References 24 publications

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“…The test results show the heart rate is at 70 bpm to 74 bpm with an error rate of 0.41%. The results obtained are by previous research conducted by Alamsyah, et al (2020), which states that a normal heart rate at rest is in the range of 60 bpm to 100 bpm [6]. Furthermore, the comparison of the temperature measurement results is shown in Figure 5.…”

Section: Figure 4 Comparison Graph Of Heart Rate Measurement Resultssupporting

confidence: 53%

“…Examination of vital signs includes checking heart rate, body temperature, respiration, and blood pressure [2][3][4][5]. Monitoring vital signs is the main priority that must be considered by medical personnel to carry out early prevention and reduce mortality [6]. The population in Indonesia continues to grow, but health care and monitoring remain a severe problem.…”

Section: Introductionmentioning

confidence: 99%

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

Laila

Arifin

Armynah

2022

IPR

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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.

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Section: Figure 4 Comparison Graph Of Heart Rate Measurement Resultssupporting

confidence: 53%

Section: Introductionmentioning

confidence: 99%

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

Laila

Arifin

Armynah

2022

IPR

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“…52 The application of Internet of Things (IoT) technology has increased considerably, especially in vital sign monitoring. 53 Raban et al 54 reported that health care facilities can use EMRs as reminders to check and remove medication patches. Accordingly, LTS IS can be further integrated with EMRs or EHRs and connected with a main LTC system through a data exchange interface for relevant applications.…”

Section: Discussion and Future Workmentioning

confidence: 99%

Daily Care Information System Requirements: Professional Service-Driven Service Blueprint Approach

et al. 2021

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Background Long-term care (LTC) services are a professional service-driven (PSD) system; to deliver appropriate care services to residents, health care providers first need to collect appropriate patient data and make a professional assessment. A well-designed LTC information system should therefore consider the information requirements of multidisciplinary health care providers to adequately support their care services. Objectives This study proposed a modified service blueprint—the PSD service blueprint—for visualizing interdisciplinary service providers' input and output information requirements, which correspond to their service activities. Methods The PSD service blueprint comprises five layers and seven elements. We also present a case study to illustrate the blueprint's application to daily LTC services. Results Our proposed approach could clearly illustrate the daily care activities, service providers (main actors), actors' input and output information, and suggestions for LTC information system–related applications. Conclusion The proposed PSD service blueprint can not only gather interdisciplinary LTC service providers' information system requirements but also act as a mapping tool for visualizing the care service process.

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“…Untuk mengawasi dan memantau pasien vertigo apakah terjadi insiden pusing, jatuh atau tidak, diperlukan suatu alat yang berfungsi untuk mengetahui keadaan posisi pasien itu sendiri dari jarak dekat maupun jauh. Beberapa penelitian terkait monitoring kesehatan telah dilakukan diantaranya untuk monitoring detak jantung [7][8][9] dan suhu tubuh [10][11] berbasis IoT. Penelitian yang dilakukan juga dapat melakukan diagnosis menggunakan smartphone [12,13,14] dan berbasis website [15][16].…”

Section: Pendahuluanunclassified

Alat Deteksi Jatuh Berbiaya Murah Dengan Tracking Position Untuk Pasien Vertigo dan Sinkop

Yulastri

Madona

Irmansyah

et al. 2020

RESTI

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In this study we propose a low-cost portable device to monitor the vertigo and syncope patients whether normal, dizziness or falls. The purpose of this study is design and manufactures a device using an accelerometer sensor to determining the condition of patients who are at risk of vertigo and syncope. The patient's condition is detected by accelerometer which read the values of the x, y and z axes to determine condition normal, dizzy, or fall. This device also uses a real time clock to remind the patient to take medication three times a day. The device outputs are LCD Oled, Voice, and SMS notification. If the patient condition is falls an SMS notification will be sent, the dizzy condition vertigo patient will press the panic button first and then an SMS notification will be sent. The results of tests carried out on the equipment can send SMS and phone calls at an angle of (50o - 70o) = Y (40o - 20o) = X, in a fainting state and falling. The test results of the navigation module prove that the GPS module can determine the exact location by moving the GPS module reading position to a small test point with an average of 2.97 meters.

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Internet of things–based vital sign monitoring system

Cited by 12 publications

References 24 publications

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

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

Daily Care Information System Requirements: Professional Service-Driven Service Blueprint Approach

Alat Deteksi Jatuh Berbiaya Murah Dengan Tracking Position Untuk Pasien Vertigo dan Sinkop

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