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Ricki Septiando Sinaga
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Computer Science & IT

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IoT Heart Beat Monitoring Based on Nodemcu ESP32 Ricki Septiando Sinaga; Beni Satria; Hamdani, Hamdani
INFOKUM Vol. 13 No. 05 (2025): Infokum
Publisher : Sean Institute

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Abstract

Cardiovascular disease is a leading cause of global death, with early detection of heart rate anomalies key to preventing complications such as arrhythmias. However, conventional monitoring systems are often expensive, non-portable, and less accessible in remote areas. This study aims to develop an affordable and portable Internet of Things (IoT)-based heart rate monitoring system using the MAX30100 sensor and an ESP32 microcontroller. The system is designed to measure heart rate in real time, transmit data to the Blynk IoT platform, and provide automatic notifications when the heart rate is outside the normal range (60–100 beats per minute). The research methods include system design, hardware and software implementation, and testing on 10 subjects aged 20–40 years. Heart rate data was processed using a moving average filter to reduce motion noise. The test results showed heart rate measurement accuracy with an average relative error of 2.57%, an average data transmission latency of 1.39 seconds, and a notification response time of 1.8 seconds. The system is also power-efficient with a consumption of 80 milliamperes, making it suitable for long-term use. This research has successfully produced an efficient and accessible heart rate monitoring solution, supporting early detection of heart disorders in resource-limited settings.
Co-Authors Beni Satria Hamdani Hamdani