摘要
由于心电(ECG)信号特征参数具有模糊性和随机性的特点,为ECG信号的自动分析增加了难度,使ECG自动分析往往很难完全达到专家诊断的效果。针对这一问题,本文探索性地将集随机性和模糊性于一体的定性定量不确定性转化模型——云模型用于ECG信号自动分析系统中。基于云变换和综合云的思想,实现ECG信号的聚类分析。进一步基于云模型理论描述心电专家在临床总结出的分类规则,进而分析诊断,从而克服了传统ECG自动分析诊断过程中判断指标、阈值的绝对化和判断规则的精确化的问题。与传统方法相比,分析过程更加接近于心电专家的思维与逻辑,分析结果更加符合医学专家的诊断结果。以MIT/BIH心电数据库为对象,实验结果表明,结果更加接近于心电专家的模糊逻辑思维分析的结果,是一种有效的ECG信号分析方法。
The characteristics of electrocardiogram（ECG） signal are fuzzy and random,so that they are difficult for automatic analysis and diagnosis.To solve this problem,an uncertainties transformation model——Cloud Model,which is a fusion of qualitative and quantitative information,was tried to use to analyze the ECG signal.The model fusions the characters of fuzzy and random,just suit to the ECG automatic analysis and diagnosis system.Based on the theory of the cloudy transform and comprehensive cloud,the clustering of ECG signal was finished.Further more,the clinic experience of expert was summarized as classification rules based on the theory.The experiment data were from MIT/BIH database.The experiment results showed more close to those of the expert＇s analysis.The describing result was more close to those of the more expert＇s with qualitative and quantitative information.It is well concluded that the method is an effective ECG signal analysis method.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2011年第1期27-31,共5页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(6304009)
河北省优秀专家出国项目资助
关键词
心电信号
云模型理论
聚类
诊断
Electrocardiogram（ECG） signal
Cloud model theory
Clustering
Diagnosis
