量化多导联心电图临床成分丢失的诊断措施。
Diagnostic measure to quantify loss of clinical components in multi-lead electrocardiogram.
作者信息
Tripathy R K, Sharma L N, Dandapat S
机构信息
Department of Electronics and Electrical Engineering , Indian Institute of Technology Guwahati , Guwahati 781039 , India.
出版信息
Healthc Technol Lett. 2016 Feb 23;3(1):61-6. doi: 10.1049/htl.2015.0011. eCollection 2016 Mar.
In this Letter, a novel principal component (PC)-based diagnostic measure (PCDM) is proposed to quantify loss of clinical components in the multi-lead electrocardiogram (MECG) signals. The analysis of MECG shows that, the clinical components are captured in few PCs. The proposed diagnostic measure is defined as the sum of weighted percentage root mean square difference (PRD) between the PCs of original and processed MECG signals. The values of the weight depend on the clinical importance of PCs. The PCDM is tested over MECG enhancement and a novel MECG data reduction scheme. The proposed measure is compared with weighted diagnostic distortion, wavelet energy diagnostic distortion and PRD. The qualitative evaluation is performed using Spearman rank-order correlation coefficient (SROCC) and Pearson linear correlation coefficient. The simulation result demonstrates that the PCDM performs better to quantify loss of clinical components in MECG and shows a SROCC value of 0.9686 with subjective measure.
在本信函中，提出了一种基于新型主成分（PC）的诊断度量（PCDM），用于量化多导联心电图（MECG）信号中临床成分的损失。对MECG的分析表明，临床成分被捕获在少数几个主成分中。所提出的诊断度量被定义为原始和处理后的MECG信号的主成分之间加权百分比均方根差（PRD）的总和。权重值取决于主成分的临床重要性。PCDM在MECG增强和一种新型MECG数据缩减方案上进行了测试。将所提出的度量与加权诊断失真、小波能量诊断失真和PRD进行了比较。使用斯皮尔曼等级相关系数（SROCC）和皮尔逊线性相关系数进行定性评估。仿真结果表明，PCDM在量化MECG中临床成分的损失方面表现更好，并且与主观度量的斯皮尔曼等级相关系数值为0.9686。
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