Design flow of wearable heart monitoring and fall detection system using wireless intelligent personal communication node

Most current remote health monitoring systems provide limited physiological information on the user end. Raw physiological data collected from the on-body sensors are sent to a distant location for data storage and analysis without being analyzed on the user end. In this paper, we present the design flow of a system utilizing the Wireless Intelligent Personal Communication Node (W-iPCN) for analyzing heart activities and detecting sudden fall situations of a remote patient. The W-iPCN is a small, compact and lightweight system which has the ability to process and analyze body sensor data. Furthermore, this system is capable of communicating with other devices through wireless protocols. The purpose of having the W-iPCN for wireless body sensor network system is to provide in-depth biomedical data to the user in real-time. As an example, we emphasize on electrocardiography (ECG), accelerometer and gyroscope data analysis to show the feasibility and capability of the W-iPCN. The ECG sensor data is useful to determine current heart conditions of the user. Accelerometer and gyroscope data are useful to detect sudden collapse events. In this paper, we expand our system design to an Android smartphone to present acquired analyzed sensor data to the user. In addition, the Android smartphone transmits the data to the distant server for data logging and history keeping through the Internet in realtime. Our system targets standard Android smartphone users to be able to install and run our Android application software without requiring expert software knowledge.