基于奇异值矩阵分解的腕式示波法血压测量算法  

Development of an Algorithm for Wrist Oscillometric Blood Pressure-measurement Using Singular Value Decomposition

作　　者：王陈海[1] 张鲁闽[1] 马继民[1] 吴太虎[2] 

机构地区：[1]南京军区福州总医院,福州350025 [2]军事医学科学院卫生装备研究所,天津300161

出　　处：《生物医学工程学杂志》2011年第4期715-720,共6页Journal of Biomedical Engineering

摘　　要：为了减小因手腕部生理结构导致腕式示波法测量中存在的内在干扰,本文提出一种基于奇异值矩阵分解(SVD)的新型曲线拟合算法(SCFA),用于提高测量精度。该方法是通过对腕式示波法测量的波形数据进行SVD,提取出主要特征成分,并对该波形成分应用曲线拟合算法(CFA)计算出血压值。根据对45例样本的测量和数据分析,以听诊法(AM)测量值为参照,基于新算法计算的血压值与测量值之间的相关系数为0.96。对比传统的曲线拟合算法(TCFA)计算值,新算法的结果更为准确。实验结果表明,SCFA能够部分消除腕式示波法血压测量过程中的内在干扰,有效的提高腕式血压测量的准确度。In order to eliminate the intrinsic noise due to special structure of the wrist,a new curve fitting algorithm based on singular value decomposition（SVD） was developed to increase the measurement accuracy.This algorithm could be subdivided into SVD and curve fitting algorithm（SCFA）.SVD was used to extract the dominant component of oscillation waves at wrist.Then oscillation amplitudes of dominant component and cuff pressure were used to determine arterial blood pressure（ABP） with curve fitting algorithm.To test the performance of SCFA,45 subjects underwent the ABP measurement with different methods.The correlation coefficient between the pooled blood pressure measured by the auscultation and those by SCFA was 0.96.Comparison the results of SCFA with those of traditional curve fitting algorithm（TCFA）,we found that the proposed SCFA could be used to reduce the partial intrinsic interference and efficiently improve the accuracy of the ABP at wrist.

关 键 词：血压测量 示波法 奇异值矩阵分解 曲线拟合算法 

分 类 号：R318.0[医药卫生—生物医学工程]