Design of a wearable sensor network for home monitoring of human behavior

In this paper we describe a wearable ubiquitous healthcare monitoring system that integrates electrocardiogram (ECG device) and an accelerometer sensor with a mobile device in a Bluetooth-based body surface network (BSN). Our research focused on the right connection of the hardware units, combination of the detection of QRS complexes, calculation of heart rate (HR) and the detection of human falls. The main aim of this research was the early detection of abnormal situations (high/low HR, a fall) and the heart rate variability analysis. The human falls are very risky events that occur not only in the elderly people’s daily living but also by epileptics and asthmatics. For these people independent living is strictly forbidden. A wearable sensor based monitoring system can inhibit serious injuries and allow those people live an independent life. Additionally, an SMS messaging module was integrated with the monitoring system. After detecting a nonstandard situation a short notice is sent. The implementation of the QRS complex detection algorithm, that was based on the Tompkins formula, was tested on the records from the MITBIH database.