经络电阻抗特性的特征提取及模式分类方法研究
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摘要
经络电信号含有丰富的人体病理和生理状态信息,对这些电信号的判读在中医经络科学研究及其临床诊断应用方面有着重要作用。作为一个新兴的交叉学科,现代中医经络电特性研究是将传统的中医经络学与信息科学结合起来,提取其电阻抗特征来研究人体经络的内在规律以及其与人体生理状态的关联特性,以探讨经络的实质。当前经络电阻抗特性研究虽取得了一定的成果,但是仍存到很多问题,还处于一个起步阶段。一方面,经络电信号是一种非线性非平稳的频谱时变的微弱信号,且其背景噪声很强,这使得经络电信号的有效、准确检测和采集非常困难；另一方面,缺乏有针对性和更为有效的信号处理与分析方法,特别是缺乏经络电阻抗特性的特征提取和模式分类方法,导致经络电阻抗特性的挖掘和发现不是理想的最优结果。
针对这些问题,本论文从以下几个方面展开了研究和创新：
1)对经络电阻抗信号的自动检测进行了研究。
以生物阻抗技术为基础,设计数据采集模块、激励信号源等硬件,建立一套基于四电极法的人体经络电阻抗测量系统,分析其噪声干扰源并给出其解决方案。利用巴什瓦定理确立激励信号的不确定谱模型,采用二层遗传优化算法求解其鞍点解,解决系统的激励信号畸变问题,提出一种基于稳健匹配滤波的激励信号不确定度去除方法,并对其进行了理论分析。
2)对单经穴电阻抗特性的特征提取进行了研究。
在对AR模型和ARMA模型对经穴生理状态特征的建模辨识等价性进行验证的基础上,建立了一种基于AR参数模型的单经穴电阻抗特征模型,分析模型的定阶准则和求解算法,并重构其信息的AR谱结构特征,进行仿真比较。为了解决单经穴原始特征集的亢余问题,提出一种基于遗传算法的经穴电阻抗特征优化方法,研究了其编码方案、适应度函数以及其个体的选择、交叉变异等算子,并实验验证了算法的有效性。
3)对多经穴电阻抗特性的特征提取进行了研究。
为了提高数据压缩率、降低特征维数和计算复杂度,提出了一种多经穴电阻抗线性特征的PCA提取算法,研究了最优主成分的求解方法及其建模过程；将原始输入向量映射到高维特征空间,通过合理选择核函数及重算算法,提出一种多经穴电阻抗非线性特征的KPCA提取算法。将PCA与投影法相结合,利用客观赋权法构建原始特征集的理想特征向量,并基于主成分投影法得到其修正加权特征矩阵的投影值,进而提出一种新的经脉信息PCP综合特征指标；实验结果表明PCP综合特征指标比单经穴特征指标更能有效地进行模式分类。
4)对经穴电阻抗特征的模式分类进行了研究。
研究了经验风险最小化原则及SVM分类模型理论,并针对经穴多类模式分类与识别问题,提出一种基于LS-SVM的经穴电阻抗特征分类方法,分析了LS-SVM算法的多类器方法和参数优化选择问题,并对其进行实验比较,结果表明基于决策有向无环图方法的经穴电阻抗特征分类方法更能有效地提高其分类识别率。
5)对经络系统的整体演化特性进行了研究。
研究了经络系统的信息本原实质及其信息流过程；在时间、空间和状态上通过对经络系统离散化构建经穴元胞及空间,制定其状态演化更新规则,进而提出了一种基于元胞自动机的经络系统演化模型,仿真结果表明,该模型能有效地仿真经络系统的自循环、自组织、自演化等特性。
The meridian electrical signals involve a great deal of human pathological and physiological status information, to understand the complex dynamical behavior is of great significance for the meridian scientific research and clinical diagnostic application. The modern study of meridian and acupoint is a developing and crossing discipline, which is based on the combination of Traditional Chinese Medicine Science and Information Science to obtain the internal laws of human meridian and its associated characteristics with the human physiological state by extracting its electrical impedance characteristics, thus to explore the essence of meridian ultimately. At present, many achievements have been made by the scientists, but the study is still in progress, much work should be done. On the one hand, the meridian electrical signal is the very weak signal which can be described as nonlinear, non-stationary and spectrum-of-time-varying. It is very difficult to be detected and collected effectively and accurately. On the other hand, there has no effective and targeted processing and analysis methods for the studies, especially the lack of useful ways to extract electrical feature and classify patterns on meridian and acupoint, which leads to its conclusion is not ideal for optimal results.
Concerning about the problems, the main studies and innovations in this thesis ahead in the following aspects:
■Based on bioimpedance technology, an electrical impedance measurement system for human meridian signal was proposed through designing hardware modules, data acquisition modules and incentive source, and the sources of its interference noise were analyzed and solved by a suppression program with software and hardware line. For Solving the distortion problem of the excitation signal, A removal method based on robust matched filtering was simultaneously proposed, and the uncertainty spectrum model was establish by Bashi Wa theorem and its saddle point was saluted by two-Layer genetic optimization algorithm in the method, and Finally its theoretical analysis was given.
■The electrical impedance feature extraction of single meridian signal was investigated. For obtaining its purpose to the dimension reducibility and the maximum utilization and the improvement on accurate recognition, an electrical impedance feature model of single meridian was established based on the AR parameter model, and on which the different order determined criteria and the model solution algorithms were analyzed and compared. Then structural features of the model spectrum were reconstructed and which solved the problem effectively, that is, the AR parameters can only expressed part of system information. In addition, in order to solve the redundant information problem of single-meridian original feature set, the optimization method based on the genetic algorithm for the single meridian electrical impedance signal was proposed. In the method, encoding scheme used binary encoding, fitness function using the within-and-between-class distance criterion, and the individual is generated by selection operator, crossover operator and mutation operator.
■The electrical impedance feature extraction of multiple meridian signals was investigated. For improving the data compression rate and reduce feature dimensions and computational complexity, the multi-meridian linear feature extraction algorithm based on PCA was presented, and in which two principal components solution algorithm based on covariance matrix or correlation matrix were compared. Then, the original input vector is mapped to a high dimensional feature space, and the multi-meridian nonlinear algorithm based on KPCA was presented, and in which kernel function was selected and recalculated. Finally, a new comprehensive feature index for the channel based on the PCA method and projection method was established, and in which the ideal Eigenvectors of the original feature set was given by the objective weighting method and projection value of amendments weighted feature matrix was constructed based on the projection of main constituents, Experimental results show that the comprehensive feature index was more effective for pattern classification than single meridian feature index.
■The pattern classification on the electrical impedance feature of meridian and acupoint was investigated. For the classification and identification problems of multi-class model, based on Statistical Learning Theory, Empirical Risk Minimization was analyzed and the SVM modeling algorithms for different classification problems were compared, and then a pattern classification method based on LS-SVM for the electrical impedance feature of meridian and acupoint was presented. In the method, grid search method and K cross-validation method were used to solve the problem about approximate optimal parameter of LS-SVM, and various multi-class device methods were discussed. The experimental result showed that the pattern classification based on Directed Acyclic Graph More was effective to improve the recognition rate.
■The overall evolution feature of the meridian system was investigated. The systematic characteristics of meridian were analyzed and proposed, and it was pointed out and demonstrated that the meridian system is a primitive information system with relationship existing. Secondly, on this basis, an overall evolution model based on Cellular Automata for the meridian system was presented. In the model, meridian cellular and its space was obtained by the meridian system discredited in time, space and state, and cellular evolution rules in the state transition of single meridian cellular, associated conversion of the channel and historical condition of the meridian were formulated. The simulation results showed that the model can effectively simulate the meridian system with the characteristics of self-loop, self-organization and self-evolution.
针对这些问题,本论文从以下几个方面展开了研究和创新：
1)对经络电阻抗信号的自动检测进行了研究。
以生物阻抗技术为基础,设计数据采集模块、激励信号源等硬件,建立一套基于四电极法的人体经络电阻抗测量系统,分析其噪声干扰源并给出其解决方案。利用巴什瓦定理确立激励信号的不确定谱模型,采用二层遗传优化算法求解其鞍点解,解决系统的激励信号畸变问题,提出一种基于稳健匹配滤波的激励信号不确定度去除方法,并对其进行了理论分析。
2)对单经穴电阻抗特性的特征提取进行了研究。
在对AR模型和ARMA模型对经穴生理状态特征的建模辨识等价性进行验证的基础上,建立了一种基于AR参数模型的单经穴电阻抗特征模型,分析模型的定阶准则和求解算法,并重构其信息的AR谱结构特征,进行仿真比较。为了解决单经穴原始特征集的亢余问题,提出一种基于遗传算法的经穴电阻抗特征优化方法,研究了其编码方案、适应度函数以及其个体的选择、交叉变异等算子,并实验验证了算法的有效性。
3)对多经穴电阻抗特性的特征提取进行了研究。
为了提高数据压缩率、降低特征维数和计算复杂度,提出了一种多经穴电阻抗线性特征的PCA提取算法,研究了最优主成分的求解方法及其建模过程；将原始输入向量映射到高维特征空间,通过合理选择核函数及重算算法,提出一种多经穴电阻抗非线性特征的KPCA提取算法。将PCA与投影法相结合,利用客观赋权法构建原始特征集的理想特征向量,并基于主成分投影法得到其修正加权特征矩阵的投影值,进而提出一种新的经脉信息PCP综合特征指标；实验结果表明PCP综合特征指标比单经穴特征指标更能有效地进行模式分类。
4)对经穴电阻抗特征的模式分类进行了研究。
研究了经验风险最小化原则及SVM分类模型理论,并针对经穴多类模式分类与识别问题,提出一种基于LS-SVM的经穴电阻抗特征分类方法,分析了LS-SVM算法的多类器方法和参数优化选择问题,并对其进行实验比较,结果表明基于决策有向无环图方法的经穴电阻抗特征分类方法更能有效地提高其分类识别率。
5)对经络系统的整体演化特性进行了研究。
研究了经络系统的信息本原实质及其信息流过程；在时间、空间和状态上通过对经络系统离散化构建经穴元胞及空间,制定其状态演化更新规则,进而提出了一种基于元胞自动机的经络系统演化模型,仿真结果表明,该模型能有效地仿真经络系统的自循环、自组织、自演化等特性。
The meridian electrical signals involve a great deal of human pathological and physiological status information, to understand the complex dynamical behavior is of great significance for the meridian scientific research and clinical diagnostic application. The modern study of meridian and acupoint is a developing and crossing discipline, which is based on the combination of Traditional Chinese Medicine Science and Information Science to obtain the internal laws of human meridian and its associated characteristics with the human physiological state by extracting its electrical impedance characteristics, thus to explore the essence of meridian ultimately. At present, many achievements have been made by the scientists, but the study is still in progress, much work should be done. On the one hand, the meridian electrical signal is the very weak signal which can be described as nonlinear, non-stationary and spectrum-of-time-varying. It is very difficult to be detected and collected effectively and accurately. On the other hand, there has no effective and targeted processing and analysis methods for the studies, especially the lack of useful ways to extract electrical feature and classify patterns on meridian and acupoint, which leads to its conclusion is not ideal for optimal results.
Concerning about the problems, the main studies and innovations in this thesis ahead in the following aspects:
■Based on bioimpedance technology, an electrical impedance measurement system for human meridian signal was proposed through designing hardware modules, data acquisition modules and incentive source, and the sources of its interference noise were analyzed and solved by a suppression program with software and hardware line. For Solving the distortion problem of the excitation signal, A removal method based on robust matched filtering was simultaneously proposed, and the uncertainty spectrum model was establish by Bashi Wa theorem and its saddle point was saluted by two-Layer genetic optimization algorithm in the method, and Finally its theoretical analysis was given.
■The electrical impedance feature extraction of single meridian signal was investigated. For obtaining its purpose to the dimension reducibility and the maximum utilization and the improvement on accurate recognition, an electrical impedance feature model of single meridian was established based on the AR parameter model, and on which the different order determined criteria and the model solution algorithms were analyzed and compared. Then structural features of the model spectrum were reconstructed and which solved the problem effectively, that is, the AR parameters can only expressed part of system information. In addition, in order to solve the redundant information problem of single-meridian original feature set, the optimization method based on the genetic algorithm for the single meridian electrical impedance signal was proposed. In the method, encoding scheme used binary encoding, fitness function using the within-and-between-class distance criterion, and the individual is generated by selection operator, crossover operator and mutation operator.
■The electrical impedance feature extraction of multiple meridian signals was investigated. For improving the data compression rate and reduce feature dimensions and computational complexity, the multi-meridian linear feature extraction algorithm based on PCA was presented, and in which two principal components solution algorithm based on covariance matrix or correlation matrix were compared. Then, the original input vector is mapped to a high dimensional feature space, and the multi-meridian nonlinear algorithm based on KPCA was presented, and in which kernel function was selected and recalculated. Finally, a new comprehensive feature index for the channel based on the PCA method and projection method was established, and in which the ideal Eigenvectors of the original feature set was given by the objective weighting method and projection value of amendments weighted feature matrix was constructed based on the projection of main constituents, Experimental results show that the comprehensive feature index was more effective for pattern classification than single meridian feature index.
■The pattern classification on the electrical impedance feature of meridian and acupoint was investigated. For the classification and identification problems of multi-class model, based on Statistical Learning Theory, Empirical Risk Minimization was analyzed and the SVM modeling algorithms for different classification problems were compared, and then a pattern classification method based on LS-SVM for the electrical impedance feature of meridian and acupoint was presented. In the method, grid search method and K cross-validation method were used to solve the problem about approximate optimal parameter of LS-SVM, and various multi-class device methods were discussed. The experimental result showed that the pattern classification based on Directed Acyclic Graph More was effective to improve the recognition rate.
■The overall evolution feature of the meridian system was investigated. The systematic characteristics of meridian were analyzed and proposed, and it was pointed out and demonstrated that the meridian system is a primitive information system with relationship existing. Secondly, on this basis, an overall evolution model based on Cellular Automata for the meridian system was presented. In the model, meridian cellular and its space was obtained by the meridian system discredited in time, space and state, and cellular evolution rules in the state transition of single meridian cellular, associated conversion of the channel and historical condition of the meridian were formulated. The simulation results showed that the model can effectively simulate the meridian system with the characteristics of self-loop, self-organization and self-evolution.
引文
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