Multi-agent Power Management System for ZigBee Based Portable Embedded ECG Wireless Monitoring Device with LabView Application

摘要

The techniques of multi-agent system bring intelligence and flexibility to embedded agent/multi-agent embedded system connected to internet presents a great advantage. Advantage of such multi-agent systems improves the use of expanded infrastructure. Installing simplified agents in embedded systems was shown necessary due to increasing use of embedded devices. Multi-agent power management system is based on battery control and anticipation of replacement. Wireless transmission of ECG (electrocardiogram) signal via ZigBee (XBee modules) brings some problem into focus. This paper presents concept realized and tested on real equipment. Using smart mobile phone (today a widely used device) interaction/actoric between end user embedded agent and embedded master agent can give feedback about end users health in real-time. Similar, off-line monitoring device exists, but not connected to the network (Holter). Monitoring of patients in real-time can be enabled by such device that exhibits wireless communication and allows transmission of real-time source signal. The agent on which this paper refers to is program/firmware function in program code in small embedded system for monitoring ECG signal. Simplified agent activates the watchdog for battery alert. Main focus is to control the power consumption of WSN (Wireless Sensor Node). Power management has the intelligence middleware and allows timely to respond and inform the end users. Artificial intelligence is integrated in master agent that is element of embedded system cloud and a primal high level layer. Secondary layer is integrated in dedicated servers which respond to device clouds. LabVIEW application for signal processing provides robust and efficient environment for resolving ECG signal processing problem. These tool/application can be also used in other biomedical signal processing applications such as Magnetic Resonance Imaging (MRI) and Electroencephalography (EEG).