分形理论在心音信号的分析与识别中的应用研究

【作者】 贾丽会；

【导师】 张修如；

【作者基本信息】 中南大学 ， 计算机应用技术， 2007， 硕士

【摘要】 心音信号是人体最重要的声信号之一，它包含着心脏各部分的生理和病理信息，是心脏及心血管系统机械运动状况的反映。在心血管疾病尚未发展到足以产生临床及病理改变时，心音中出现的杂音和畸变就是重要的诊断信息。因此，准确地分析和识别心音信号对心血管系统疾病的诊断具有重要的意义。论文将分形理论引入到心音信号的研究中，以分形维数为基础进行心音信号的分析与识别，为心血管疾病提供一种新的无损诊断方法。首先对两种分形维数估算方法：方差分形维数法和二进盒维数法进行研究，并通过实验对两种估算方法进行验证和比较；接着对心音信号的分形特征进行研究，并对正常心音和病态心音的分形维数进行比较；然后给出心音信号分形维数轨迹的构造算法，讨论时间窗口参数对心音信号分形维数轨迹产生的影响，并分析心音信号分形维数轨迹的特征；最后结合心音信号分形维数轨迹的特征和心音信号的时域特性，提出一种基于分形维数轨迹的心音信号自动分段算法，给出了分段算法的策略和具体步骤，并用大量病例对分段算法的性能进行了验证。研究结果表明，心音信号存在无标度区间，具有明显的分形特征；分形维数能够定量地描述心音信号的复杂程度，显著地区分正常心音和病态心音；基于分形维数轨迹的心音信号自动分段算法无需依赖任何参考信号，准确率高，鲁棒性强，具有良好的分段效果。更多还原

【Abstract】 Heart sound is one of the most important voice signals of human body. It includes physiology and pathologic information of each part of heart, and reflects the mechanical movement condition of the heart and the cardiovascular system. When the cardiovascular diseases haven’t developed to be good enough to produce clinical and pathologic change, murmur and aberration of heart sound is important information for diagnosis. Therefore, correct analysis and recognition of heart sound is significant to the diagnosis of cardiovascular diseases.This paper introduces fractal theory to the study of heart sound, and makes analysis and recognition of heart sound on the basis of fractal dimension, and provides a new noninvasive diagnostic for cardiovascular diseases. Firstly, this paper studies two kinds of fractal dimension estimation methods: variance fractal dimension and binary box-counting dimension, and verifies and compares the two methods. Next, it studies the fractal characteristic of heart sound, and draws a parallel between fractal dimension of normal and morbid heart sound. Then, this paper presents construction method of fractal dimension trajectory of heart sound, and discusses how time window parameters affect ’fractal dimension trajectory of heart sound, and analyses the characteristics of fractal dimension trajectory. Finally, a new automatic segmentation algorithm of heart sound is put forward by combining fractal dimension trajectory and time characteristics of heart sound, and the strategies and steps of segmentation are given, and the algorithm is tested with a large number of normal and abnormal heart sound data.The results show heart sound has non-scaling span and obvious fractal characteristics. Fractal dimension can quantitatively express the complexity of heart sound, and evidently distinguish normal and morbid heart sound. Automatic segmentation algorithm of heart sound based on fractal dimension trajectory is of high accuracy and robust without other signal as reference, and segment results are good.更多还原