Analog voltage to bit per minute (bpm) conversion in heart rate sensor: a least square regression-based approach using arduino microcontroller

Abstract

This work presents an approach for Analog voltage to bit per minute (bpm) conversion in heart rate sensors. The works entails the use of Photoplethysmography (PPG) heart/pulse rate sensor and Arduino uno microcontroller. Data were collected through simultaneous measurements from a mobile heart rate application and an Arduino-based analog pulse sensor. The paired dataset of analog input (voltage) and corresponding bpm values were analysed using least squares regression to establish a reliable mathematical conversion model between the two variables. The experimental results show a linear correlation between the analog input and the measured bpm. The method demonstrates robustness across different voltage ranges and is computationally efficient, making it suitable for real-time applications on resource limited embedded platforms. By integrating regression analysis with microcontroller-based signal processing, this work highlights a practical pathway toward improving the reliability of heart rate monitoring systems. The findings hold promise for applications in wearable devices, telemedicine, and continuous home-based patient monitoring, where effective and reliable heart rate measurement is essential.