【作者】 李罗；

【导师】 卢建刚；

【作者基本信息】 浙江大学 ， 控制理论与控制工程， 2006， 硕士

【摘要】 远程医疗监护特别是心电图监护对提高人们的生活质量,促进社会健康协调发展有着极为重要的作用,是近年来国际上迅速发展的一个研究热点。本文提出了一种基于无线技术的心电采集方案,介绍了关键技术及软硬件设计。还进行了基于Matlab的小波分析研究,并将小波分析应用于心电信号处理。最后讨论了未来研究发展的方向。 本文的内容主要包括: 1.首先介绍了当今国内外远程医疗研究的概况及几种典型的远程医疗系统,详细比较了它们的特点。其次介绍了小波理论的发展历史及其在心电信号处理应用中的发展。 2.介绍了社区远程医疗监护系统的组成,无线心电信号采集器的硬件、软件及无线模块的设计。其中就信号放大滤波电路,MSP430单片机以及nRF905无线收发模块的设计作了较详细的介绍。 3.介绍了小波分析理论,包括小波分析的基础知识、多分辨率分析及常用小波。 4.介绍了基于小波分析的心电信号处理研究。并就小波分析在心电信号消噪和压缩等处理中的应用进行了详细的介绍。选取coil3小波,对心电信号进行消噪压缩等处理,取得了较好的效果。 5.在本文的最后,讨论了未来的研究发展方向更多还原

【Abstract】 Telemedicine monitoring, especially the electrocardiogram(ECG) monitoring, plays an important role in improving the quality of people’s lives and promoting the healthy and harmonious development of the society. It is an international research hot spot in recent years. This article presents an ECG signal sampling scheme based on wireless technology. It also introduced the key technologies and the design of software and hardware. Besides, the research of wavelet analysis based on Matlab and the applications of wavelet analysis in ECG signal processing is illustrated. Finally, the direction of further research is discussed.The main content of this thesis is as follow:1. Firstly, the current situation of telemedicine research in the domestic and international is introduced, and several typical telemedicine systems are bringed forward and compared in detail. Secondly, the history of wavelet theory and the development of its application in ECG signal processing are introduced.2. We introduce the composition of the community telemedicine monitoring system, and the design of hardware, software and wireless module of wireless ECG signal sampler. The design of signal amplifying and filtering circuit, MSP430 microprocessor and nRF905 wireless module are described in detail.3. We introduce the wavelet analysis theory which includes basic knowledge, multi-resolution analysis and common wavelet.4. The research of ECG signal processing based on wavelet analysis is introduced, and the noise reduction and compression techniques of ECG signal are especially detailed. We selected wavelet coif3 in application and achieved good results.5. At last, we discussed the direction of future research.更多还原