Real-Time Heart Rate Classification: Advancements and Challenges Manuscript Received: 21 July 2023, Accepted: 30 August 2023, Published: 15 March 2024, ORCiD: 0000-0002-5151-2300, https://doi.org/10.33093/jetap.2024.6.1.6

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Published: Mar 15, 2024
DOI: https://doi.org/10.33093/jetap.2024.6.1.6
Keywords:
Heart rate, Detection, Prediction, Machine learning, IoT

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Chze Xin Loo
Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia.
Sumendra Yogarayan
Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia.
Siti Fatimah Abdul Razak
Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Melaka, Malaysia.

Abstract

This study focuses on the classification of heart rate, a condition with significant implications for health. The challenge lies in selecting an appropriate algorithm that can handle various types and severities of arrhythmia, enabling informed decisions and effective management. Factors such as accuracy, scalability, and efficiency are crucial for individuals without medical expertise. The selected algorithm should provide reliable classifications across different levels of severity, allowing individuals to monitor their heart rates in real-time and seek medical attention when needed. By addressing these challenges, this research aims to contribute to early diagnosis, treatment, and improved management of heart rate arrhythmia.

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Vol. 6 No. 1 (2024): https://doi.org/10.33093/jetap.2024.6.1
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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