Heart disease remains one of the leading causes of death worldwide, highlighting the need for an early and accurate monitoring system. This research aims to design an Arduino-based heart rate monitoring system that integrates the MAX30102 pulse sensor and the MLX90614 body temperature sensor. Using the Mamdani fuzzy logic method, the system classifies a user's health condition into three categories: healthy, alert, and at risk, based on inputs from heart rate, body temperature, and age. A total of 27 fuzzy rules are applied, and the results are displayed in real-time via a laptop monitor. Compared to conventional heart monitoring methods, this system offers a lower-cost and portable solution suitable for household use. Preliminary tests conducted on six samples yielded an average error rate of 16.3% (beats per minute, bpm) for the pulse sensor, which falls into the medium error category, and 3.95% (°C) for the temperature sensor, which falls into the low error category. The system was evaluated by comparing sensor readings with those of standard commercial devices, indicating acceptable accuracy for a prototype stage. While the system functions well, its performance could be further improved with enhanced sensor accuracy, wireless data transmission, and integration with mobile applications. Future developments could also focus on increasing the sample size and benchmarking against clinical-grade devices to strengthen reliability and usability. The proposed system is unique in combining heart rate, body temperature, and age data through fuzzy logic to provide real-time classification of health status in a low-cost and portable design, making it a promising tool for household-based preventive heart health monitoring.
Zubaidah et al. (Tue,) studied this question.
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