Real-Time Heart Rate Pattern Analysis During Computer-Based Work Activities

Muhammad Fatiha Assyfa; Muhammad Fikry; Zara Yunizar

doi:10.30871/jaic.v10i4.13148

Authors

Muhammad Fatiha Assyfa Universitas Malikussaleh
Muhammad Fikry Universitas Malikussaleh
Zara Yunizar Universitas Malikussaleh

DOI:

https://doi.org/10.30871/jaic.v10i4.13148

Keywords:

Real-Time Monitoring, Sensor Pulse, Kurtosis, Stress Detection, Internet of Things (IoT)

Abstract

The development of Internet of Things (IoT) technology provides opportunities for real-time health monitoring systems, including stress detection based on users’ physiological conditions. This study aims to develop an IoT-based heart rate monitoring and stress detection system using a Pulse Sensor and ESP8266 microcontroller. The system is designed to read heart rate signals in real-time and transmit the data to a computer through serial USB communication for further processing using the Python programming language. The data processing stages include signal preprocessing, Beats Per Minute (BPM) calculation, sliding window processing, and kurtosis analysis as an indicator of user stress levels. The processed data are visualized through a Streamlit-based monitoring dashboard in the form of time-series graphs, gauge meters, and real-time user condition status. The study involved 20 Informatics Engineering students performing computer-based work activities within a certain duration. The results show that the system is capable of performing real-time heart rate monitoring and stress analysis effectively. The kurtosis values indicate changes in heart rate signal distribution patterns that can be used as indicators of normal and stress conditions. The developed system is expected to provide a simple, affordable, and extensible health monitoring solution.

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