Human Activity and Heart Rate Monitoring System in a Mobile Platform

This paper describes a real-time human activity recognition and heart rate tracking system using ultra-low power wearables in a mobile platform. The mobile application shows both real-time and historical data of activities performed by the user along with the average heart rate for each activity. Random Forest and k-Nearest Neighbors algorithms were used to classify, showing general accuracies of 97.3% and 98.6%, respectively, with only eight features. The presented heart rate monitor is compared with an Apple Watch series 3 and they were demonstrated to display statistically equal values, confirming the reliability of the built monitor. Both wearables have a diameter of 4.5cm and consume currents below 10mA on transmission events and are powered with coin cell batteries, setting feasible characteristics for the need of modern wearable systems.