在健康人和有疾病人的生理信号的复杂度问题的量化受到普遍关注.复杂度的降低已被指出是病理动力学的一个普遍特征.本文使用前人提出的算法研究了心电图(ECG)的基本尺度熵(BSE)的特性,研究发现健康人的心电图的基本尺度熵比较稳定在某个范围之内(在每个图的中间区间),示出心电图处于稳定阶段,心脏的健康状况良好;而冠心病人的基本尺度熵变动范围比较大,在某个时段会波动很小、在另一个时段则会波动很大,显示出心电图处于不稳定阶段,心脏的健康状况正在变差;心梗病人则在任何时段都会表征为基本尺度熵变动范围比较小、慢慢在收敛,基本尺度熵值波变动范围最小,说明心脏的健康状况处于恶化阶段,即将危及生命.研究表明基本尺度熵值变动情况对临床诊断心脏疾病的发展演化阶段有重要的指征意义.
Complexity quantification of physiological signal from healthy and sick subjects is of extensive interest.Reduction of complexity has been pointed out to be a universal characteristics of pathology dynamics.Our paper applied electrocardiogram(ECG) data of six healthy people,six coronary heart disease patients and three myocardial infarction patients,collected from a 12-lead simultaneous electrocardiogram test analyzer.Firstly,the data was wavelet filtered(using a wavelet function bior6.8) to remove breath w...