【作者】 姜斌；

【导师】 宋蜇存；

【作者基本信息】 东北林业大学 ， 控制理论与控制工程， 2007， 硕士

【摘要】 脉诊是中医学中最具特色的诊断方法。随着现代科学技术的发展，人们希望能运用现代化的脉象采集仪器和信号处理方法，对传统的中医脉诊进行客观化研究与探讨。因此，脉诊的客观化研究对我国中医脉学的继承和开拓有着重要的意义。本论文的研究主要是基于这方面来进行的。首先，介绍了脉象信号采集系统的设计，本文的信号采集程序是用VB编制的，且VB在图形用户界面开发方面有较强的优势，而数据的处理分析与识别是利用MATLAB软件进行的，所以介绍了MATLAB与VB之间的数据交换。其次，利用频域分析方法，对时域脉象信号进行频谱分析，得到相应的脉搏频谱曲线，通过频谱曲线的特征分析，提取频域特征值。着重对双谱的基本概念和基本理论进行了详细的阐述，探讨了其物理意义，在利用间接算法分析脉象信号时，对算法进行了推导、验证和应用。最后，提出了利用径向型神经网络对4种脉象信号进行分类，比较了以脉象信号的频谱特征及双谱分析的相位平均值作为神经网络输入时的训练结果的差异。尽管文中的训练样本有限，但仿真结果表明：对脉象信号的一些特定的特征值，利用神经网络进行识别是一种可行而有效的方法。更多还原

【Abstract】 Pulse-feeling is the most characteristic diagnostic methods in traditional Chinese medicine. Along with the development of science and technology, people hope to apply sensors and modern signal processing technology to human pulse diagnosis in order to carrying on an investigation in the objectivity of the Chinese medicine Pulse- feeling, Thus, impersonal research of the pulse-diagnosis has important meaning for inheriting and expanding of our country Chinese medicine.First, designing the system for collecting pulse signal is introduced. The signal collection system procedure is established by VB in this paper, and the VB has the stronger advantage in the sketch customer interface development, but the software of MATLAB is made use of when processing, analyzing and identifying the signal, so it introduced the commutating the data between MATLAB and VB. Second, making use of the spectral analysis method, carried on the spectrum analysis to the time domain pulse signal, and get the frequency chart curve. Then by the characteristic analysis of the frequency chart distilled the spectral feature. This paper represents the basic conceptions and theories of Bispectrum estimationin detail, and discusses the physical meaning of the Bispectrum. While using the indirect algorithm and parametric model algorithm to analyze pulse signals, this paper also derives, verifies and uses them..Lastly, applies the network of RBF in the classification for four kinds of pulse, signal, and compares with the difference between the spectral characteristic and the energy of on the different dimensions by wavelet transformation and the boxing dimension and the spectral characteristic as the neural network input. Though the training sample is limited in the text, the emulational result indicates: for some particular characteristic of the pulse signal, we make use of the neural network to identify pulse is a viable and effective, and it has obviously superiority compared with the conventional pattern recognition method.更多还原