A Real-time Cardiac Monitoring using a Multisensory Smart IoT System

The Internet of Things (IoT) with smartphone technologies contains vast applications in solving the problems of heart diseases in patients needing care. With wireless sensors and smart devices, remote monitoring can identify the real-time physical status of heart patients during normal physical activities. In this research, we designed and developed an embedded sensory system with a low power communication module to discreetly collect electrocardiogram (ECG) and body accelerations using a smartphone in a common environment. A wearable sensor is utilized to monitor the ECG patterns and the smartphone's built-in sensors; specifically, we use its accelerometer and GPS sensors to measure the body acceleration and location information of the user. Experimentation and verification are conducted on a number of test subjects with different test scenarios including sitting, walking, jogging, and running. Using signal classification and machine learning techniques, we show that it is possible to design a multisensory system that allows accurate classification and authentic prediction of heart rate quality.