【摘要】 体表电位分布图 (BodySurfacePotentialMappings :BSPM )比常规 12导联ECG含有更丰富的心脏疾病诊断信息 ,如何从BSPM中得到有价值的诊断特征或信息是将BSPM技术应用于临床的重要研究课题之一。本文基于计算机心脏仿真模型 ,详细研究了BSPM分析与处理方法对急性心肌梗塞部位与范围的识别能力。研究结果表明 :体表电位积分图的极大值位置及其周围的正电位分布区域对急性心肌梗塞发生部位的诊断具有较高的可靠性 ,并给出了左心室 12段心肌对应的BSPMI中的特征区域分布图 :ST期间BSPM电位数据组成的矩阵 ,经奇异值分解得到的最大奇异值随着心肌梗塞范围的增大而增加 ,可以用最大奇异值作为AMI范围或大小的识别参数更多还原

【Abstract】 Based on computer heart simulation model, this paper studies on detailed recognized ability to acute myocardial infarction (AMI) size and location using BSPM analyzing and processing methods. The experimental results showed that the maximum location and the positivepotential distribution field around the maximum in the body surface potential integral mappings had higher reliability of diagnosis of AMI locations. We deduced the BSPMI′s corresponding featurefield mapping with the 12segment myocardial wall of the left ventricular from this positivepotential distribution field around the maximum. We constructed a matrix with STperiod BSPMs. And the studied results indicated that the maximum singularvalues obtained with the singularvalue decomposition of the matrix would add along with the increases of the AMI′s sizes. So we could use the maximum singularvalues as the recognized parameters of AMI sizes.更多还原