Embedded Software For Ecg Control In A Wireless Sensor Network

Abstract

The widespread cardiovascular diseases around the world and their constant rise have rendered new ways of healthcare delivery imminent. Recent technological advances in wireless sensors and mobile communication enable new types of healthcare systems. Especially the availability of small, lightweight and ultra-low power sensors gives new possibilities for a continuously monitoring of human biomedical data and therefore allows an early detection of potential illness.Furthermore, the need for data size reduction has lead to the use of various compression techniques. The purpose of this bachelor thesis is to create an embedded software for the control of an electrocardiograph signal in a wireless sensor network. An embedded software is a software installed via an operatin g system on a hardware device thus designating the device's behavior accordingly. A wireless sensor network(WSN) is a network of sensor nodes (also known as motes) placed in strategic locations designated to measure temperature, light, humidity etc. Sensor nodes are tiny hardware devices that contain a microprocessor, a transceiver, an external memory , power supply and one or more sensors . Their purpose is to gather information about their environment, process data and send them throughout the network. In our project the operating system we will use to program the embedded software is the open source system TinyOS from Berkeley University of California. TinyOS uses the nesC language, an extension of C programming language. Since we won't be using any hardw are for a wide variety of reasons we will simulate our software with the help of the mspsim simulator an MSP430(an ultra low-power microprocessor that most of the motes contain) simulator. Our software will perform the following: 1) Sense an ECG signal by getting a number of ECG samples.2) Modify the signal with a Frequency-Domain Technique3) Transceive the modified signal with an RF Transceiver the CC2420 chip that the mote contains.Also we will simulate our software with the shimmer mote. Our goal is to analyze and evaluate different methods for compressing the ECG signal and detect the methods that succeed power consumption. We expect to reach this conclusion by gathering data from the MSPSim simulator and compare the results.