An IoT Device for Monitoring the Respiratory Rate of People in Motion

This work presents the development of a wireless Internet of Things (IoT) device that continuously monitors the respiratory rate (RR) of a person in motion. Unlike existing solutions, whose sensors are adversely affected by perspiration and exhibit low accuracy at high velocities, the proposed IoT device integrates a triaxial magnetic sensor that measures changes in the magnetic field due to chest movement, using the Z-axis information to estimate respiratory rate. The developed device uses an IIR Butterworth low-pass filter and a peak detection algorithm to overcome noise inherent to user motion and accurately extract the respiratory signal. It incorporates dual communication (Bluetooth for local connection and WiFi for cloud transmission), ensuring highly reliable real-time data transmission. System validation consisted of measuring the percentage error in 10 volunteers under three scenarios (rest, normal motion, and accelerated motion). The results demonstrate an accuracy greater than 95% in estimating respiratory rate, achieving an average percentage error of 2.36% at rest, 2.32% during normal motion, and 1.61% during accelerated motion.