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将基本尺度熵的方法在时间上做多尺度化的扩展,并将其应用到心跳间隔序列的分析研究中.研究发现,健康人的心率变异性是小时间尺度下的模式特定性与大时间尺度下的模式丰富性相结合的,而充盈性心衰患者则正好相反.这说明充盈性心衰患者在小时间尺度下心脏动力系统的控制不力,导致随机性增加,而在大时间尺度下对外界环境变化反应又不够丰富,从而导致生命更容易受威胁.据此提出了以小时间尺度下的基本尺度熵值相对于大时间尺度下平台区基本尺度熵值的变异参数δ作为区分健康人和充盈性心衰患者的诊断依据.通过对72例健康人和44例充盈性心衰患者的计算,发现两组样本差异显著,证明了参数δ的有效性.
The method of basic scale entropy is expanded in time and applied to the analysis of heartbeat interval sequence.The study found that the heart rate variability of healthy people is mode specificity and large time Scale model richness, and patients with heart failure in the opposite is true.This shows that patients with heart failure on a small scale under the control of cardiac power system ineffective, leading to increased randomness, and in a large time scale The response to the external environment is not rich enough, resulting in life more vulnerable to threats.Accordingly, the basic scale entropy on a small time scale is compared with the δ People and patients with heart failure diagnosis based on 72 healthy subjects and 44 patients with heart failure were calculated and found significant differences between the two groups of samples to prove the validity of the parameter δ.