复杂性和非线性途径能被用来在心率可变性(HRV ) 学习时间、结构的顺序表明内在的规则和心血管的规定的生理的本质,它对理解有用。为临床的应用,对短期的 HRV 分析合适的方法是更珍贵的。在这篇论文,符号系列熵分析(SSEA ) 被建议描绘 HRV 的方向变化的特征。结果证明那个 SSEA 方法能从短期的 HRV 信号检测易感知地生理、病理学的变化,并且方法也显示出它的坚韧性到 nonstationarity 和噪音。因此,它为临床的 HRV 和另外的复杂生理的信号的分析作为一个有效方法被建议。
Complexity and nonlinearity approaches can be used to study the temporal and structural order in heart rate variability (HRV) signal, which is helpful for understanding the underlying rule and physiological essence of cardiovascular regulation. For clinical applications, methods suitable for short-term HRV analysis are more valuable. In this paper, sign series entropy analysis (SSEA) is proposed to characterize the feature of direction variation of HRV. The results show that SSEA method can detect sensitively physiological and pathological changes from short-term HRV signals, and the method also shows its robustness to nonstationarity and noise. Thus, it is suggested as an efficient way for the analysis of clinical HRV and other complex physiological signals.