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A Comparison of Noisy Photoplethysmography (PPG) Signals Using Heartpy With MAX30102 and Pulse Sensor
Carl Ludwi Hendiarta, Hanson Robertus, Alexander Agung Santoso Gunawan

Last modified: 2021-06-14


This research represents the implementation of Internet of Things (IoT) and Cloud Computing on heart rate estimation system. The Internet of Things (IoT) used is ESP32 PICO D4 as microchip of LilyGo T-Wristband with the MAX30102 heart rate module. The research aims to develop a heart rate sensor for accurate health diagnostic applications and evaluate the accuracy of a health diagnostic application using a heart rate sensor focus on creating a heart rate estimation system. This evaluation is done by comparing with another heart rate sensor which is Pulse Sensor. The % RMSE of the two sensor is calculated from two subjects. The value is 16.9% and 4.2% respectively. The results show that the performance of the two sensors is not much different.