Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (32): 148-150.

• 数据库、信号与信息处理 • Previous Articles     Next Articles

Study on clustering validity evaluation method on AECG waveform data

MOU Shanling1,2,ZHENG Gang1,2   

  1. 1.Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology,Tianjin University of Technology,Tianjin 300191,China
    2.Laboratory of Biological Signal and Intelligent Processing,Tianjin University of Technology,Tianjin 300191,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-11-11 Published:2011-11-11

动态心电波形数据的聚类有效性评价方法研究

牟善玲1,2,郑 刚1,2   

  1. 1.天津理工大学 天津市智能计算及软件新技术重点实验室,天津 300191
    2.天津理工大学 生物信号与智能处理实验室,天津 300191

Abstract: According to the study on the feature of Ambulatory Electrocardiogram waveform(AECG),a cluster assessment strategy——HW-FOM(Hausdorff Weighted-Figure Of Merit) is presented on the base of Figure Of Merit(FOM).The strategy divides whole ECG waveform into several segments,and assigns weights to each segment.It computes corresponding segment distance of any two ECG waveforms by Hausdorff method,which can fit data to ECG shape.It describes the difference among ECG waveform by summed result,which is used to evaluate the effective of cluster result.MIT/BIH arrhythmia data is used in the experiment,the result shows that the result of HW-FOM is linear correlation with the real classification result,and HW-FOM is suitable for cluster validity evaluation on AECG data.

Key words: Ambulatory Electrocardiogram waveform(AECG), validity evaluation, Hausdorff Weighted-Figure Of Merit(HW-FOM)

摘要: 研究了动态心电信号的波形形态特点,提出了改进的基于品质因子(Figure Of Merit,FOM)的聚类有效性评价策略——HW-FOM(Hausdorff Weighted-Figure Of Merit)。该策略将完整的心电波形分段,并赋予不同的权重。分别计算任意两个心电波形间的对应段的Hausdorff 距离,用以拟合心电波形的形态。通过汇总计算结果描述心电波形间的差异,评价动态心电波形聚类结果的有效性。通过利用MIT-BIH心律失常数据进行实验,结果表明HW-FOM方法的评价结果与实际的数据分类状况呈线性相关,适于动态心电波形的聚类有效性结果的评价。

关键词: 动态心电波形, 有效性评价, 具有Hausdorff距离权重的品质因子(HW-FOM)