基于虚拟仪器平台的心电信号采集与处理系统研究

发布时间：2018-01-09 06:16

本文关键词：基于虚拟仪器平台的心电信号采集与处理系统研究　出处：《东华理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：根据世界卫生组织统计数据表明,近年来心血管疾病已经对人类安全健康造成日益严重的威胁,是最主要的致死病因之一,全球每年死于心脏疾病的人数超过1300万,并且呈逐年增高的趋势。因此,对心脏疾病的健康诊断及医治在全世界医学界范围内越来越受到重视。然而早期对心电信号的监测诊断则是预防和治疗心脏疾病的常规手段,为医护人员提供能够准确提取心电信号并辅助分析的仪器是非常重要的。通过传统的心电图机可以实现心电监测、分析处理,不足之处也非常明显,价格昂贵、体积过大不便于携带、功能单一、技术更新周期较长、是互联网功能有限的独立设备等。针对传统心电图机的这些弊端,本课题设计了一套基于虚拟仪器平台的心电信号采集与分析处理系统。该系统采用上位机和下位机模式,研究内容为三大部分,下位机的硬件部分主要由传感器,放大电路,滤波电路,隔离电路,A/D转换和数据采集卡等组成。经初步放大和滤波处理后将采集到心电信号的模拟量转换成数字量,再通过USB通信接口传输给上位机软件部分,之后通过小波变换的滤波算法进行心电信号的降噪与识别的处理和分析。降噪识别预处理算法从理论出发,先介绍常用的小波理论,多分辨率小波分解与重构,阈值降噪,斜率特征及模极值等算法。再从原理和步骤上对降噪与识别进行了详细的阐述与对比,最后利用MIT-BIH数据库中大量数据的仿真实验来检验降噪与识别算法的可行性和准确性。上位机软件部分是通过由美国国家仪器(NI)公司的图形化编程软件LabVIEW编写,主要功能模块包括心电信号采集模块、分析处理模块、波形显示模块、诊断报警模块、存储回放模块和远程网络发布模块等。实验证明,该处理算法能够较好的实现对心电信号的降噪及特征波形的准确捕捉,系统能准确实现心电信号的采集、处理、显示、诊断、储存、回放和网络传输功能。具备价格低廉、携带方便、操作简单、方便与网络和其他设备互联等特点,具有一定的理论意义和较强的实用价值。
[Abstract]:According to the WHO statistics show that in recent years, cardiovascular disease has on human health and safety caused by the increasingly serious threat, is one of the leading causes of death, the number of deaths from heart disease worldwide each year more than 13 million, and is increasing year by year. Therefore, the health diagnosis of heart disease and treatment in the world within the scope of the medical profession and more attention. However, early monitoring and diagnosis of ECG signal is the conventional means of prevention and treatment of heart disease, can provide accurate extraction of ECG signal and instrument aided analysis is very important for medical personnel. Through the traditional ECG machine can achieve ECG monitoring, analysis and processing, also very obvious shortcomings, the price is expensive, the volume is too large and not easy to carry, single function, technology update cycle is longer, the Internet is a limited function independent equipment. To pass These drawbacks of ECG system, this paper designs a set of virtual instrument platform of ECG signal acquisition and processing system based on the analysis. The system adopts upper and lower machine model, the research content is divided into three parts, the hardware part is mainly composed of sensor, amplifier circuit, filter circuit, isolation circuit, A/D conversion. And the data acquisition card. After the preliminary amplification and filtering processing the collected analog ECG signal is converted into digital quantity, and then to the host computer software is transmitted through the USB communication interface, after the processing and analysis of noise reduction and recognition of ECG signal by filtering algorithm of wavelet transform denoising. Recognition preprocessing algorithm in theory starting, first introduced the commonly used wavelet theory, wavelet decomposition and reconstruction, threshold denoising, slope characteristics and modulusmaxima algorithm. From the principle and steps of noise reduction and recognition The line described and compared in detail, finally the simulation experiments in MIT-BIH database to test the feasibility and accuracy of noise reduction and recognition algorithm. The PC software is adopted by the United States National Instruments (NI) LabVIEW graphical programming software company, main function modules including ECG signal acquisition module, analysis module the waveform display module, alarm module, diagnosis, storage and playback module and the remote network release module. Experiments show that the algorithm can achieve accurate capture denoising and feature waveform of ECG signal is good, the system can accurately achieve the ECG signal acquisition, processing, display, storage, playback and diagnosis, network transmission function. With low price, convenient carrying, simple operation, convenient and interconnection network and other equipment etc., has certain theoretical significance and practical value.

【学位授予单位】：东华理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R540.4;TN911.7

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