【作者】 孙光耀；

【导师】 余生晨；

【作者基本信息】 北方工业大学 ， 计算机应用技术， 2003， 硕士

【摘要】 本课题是小波变换在心电信号特征提取中的应用研究，它是小波变换在心电信号处理领域一个重要应用。心电图的QRS波群、P波、T波包含了人体心脏的丰富信息，它的识别的好坏对临床诊断具有重要意义。但是以前主要是通过临床医生经验进行判断，这不但使医生的工作繁重而且往往会因为个体的原因而产生误判。随着信息技术的发展，计算机在信号处理中得到了越来越多的应用。但心电信号包含的高频的工频干扰、肌电干扰以及低频的基线漂移干扰，这为特征点的提取以及疾病的识别带来难度。本课题就是基于这种背景把小波变换理论应用在心电信号的处理中，不但对信号的特征点进行检测，而且还探讨了对室早和室上早疾病的识别。 论文主要是在以下三个方面对心电信号进行处理： 1) QRS波的检测：运用小波多尺度分析的特性，提出了跨尺度的模极值检测方法，同时运用动态阈值算法并结合人体生理特点的综合检测策略进行复检。这不但有效地提高了QRS波群的检测准确率，还大大的节省了检测程序运行的时间。 2) P波和T波检测：充分利用小波变换抑制噪声的能力，结合过零点检测方法实行纵向检测。为提高精度，又在原信号上运用神经元网络(BP算法)，并结合人体生理特点进行横向检测。 3) 在室上早和室早的识别方面，识别疾病较好的方法是神经元网络，但是BP算法脱离不了梯度算法求局部精确解的本质。本文引入遗传算法求全局最优解的特点，再结合神经元网络的求局部精确解的优势，运用到室早和室上早疾病识别中。在这方面本文做了有益的探索。 论文在这三面做了理论的探讨，并根据所提的方法具体在编程中得以实现。但由于本人知识水平的有限，难免会有不足与错误之处，恳请专家给予批评指导。更多还原

【Abstract】 The paper is Wavelet Transform-Based ECG Charactericstic Detector. It is the more important application in signal process based Wavelet Transform(WT). QRS waves and P, T waves in electrocardiogram include abundance information about person heart, which are detected well or not provide with important meaning for clinic diagnoses. The clinician diagnosing electrocardiogram with using theirs experience before , but it is not only taking heavy work for doctor but also bringing mistakes in diagnoses because of doctor individual reason. With the information technology developing, The computer are more and more used in signal process. But ECG signal includes 60Hz power line interferce, muscle noise, and motion noise. It take difficulty in ECG signal process. This paper apply WT in ECG signal process under this background, not only detecing Charactericstic point but also discussing symptom detector.The paper mainly process ECG signal by three aspects:1) QRS waves detector: Using WT’s Multi-resolution Analysis(MRA) characteristic, bringing forward madule max value pair’s detector spaning scales and dynamic threshold arithmetic combining with body physiology and synthesis strategy which takes duplicate detector. It not only take a more detector right rate of QRS waves but also shorten the period of computing.2) P waves and T waves detector: Using WT’s restraining interferce capability, combining with acrossing zero detector method, practising vertical detector. For improving precision, taking landscape orientation detector in S=24 scale using BP arithmetic and at the same time combining with body physiology.3) The symptom detector: BP arithmetic is the preferable method of detectingsymptom. But BP arithmetic gets local precision value of grads arithmetic in essence. The project introduce Genetic Algorithms(GA)’s characteristic of getting whole optimization value at first , then combining with BP arithmetic’s predominance of getting local precision value , to detect symptom. Taking a availability explore under this direction in this paper.These arithmetic above were finished in computer program and take a preferably result. But because of finity of knowledge myself, The paper must take on deficiency or mistake, and hope experts bring forward valuable advice and comment.更多还原