Faculty of Health Sciences, University of Macau, Taipa, Macau.
Department of Geriatrics, Centro Hospital Conde de Sao Januario, Macau.
Int J Biol Sci. 2017 Oct 17;13(10):1320-1328. doi: 10.7150/ijbs.19462. eCollection 2017.
With the fast development of wearable medical device in recent years, it becomes critical to conduct research on continuously measured physiological signals. Entropy is a key metric for quantifying the irregularity and/or complexity contained in human physiological signals. In this review, we focus on exploring how entropy changes in various physiological signals in cardiovascular diseases. Our review concludes that the direction of entropy change relies on the physiological signals under investigation. For heart rate variability and pulse index, the entropy of a healthy person is higher than that of a patient with cardiovascular diseases. For diastolic period variability and diastolic heart sound, the direction of entropy change is reversed. Our conclusion should not only give valuable guidance for further research on the application of entropy in cardiovascular diseases but also provide a foundation for using entropy to analyze the irregularity and/or complexity of physiological signals measured by wearable medical device.
近年来，可穿戴医疗设备发展迅速，对连续测量的生理信号进行研究变得至关重要。熵是量化人类生理信号中不规则性和/或复杂性的关键指标。在这篇综述中，我们专注于探索熵在心血管疾病中各种生理信号中的变化。我们的综述得出结论，熵变化的方向取决于所研究的生理信号。对于心率变异性和脉搏指数，健康人的熵高于心血管疾病患者的熵。对于舒张期变异性和舒张期心音，熵变化的方向相反。我们的结论不仅应该为熵在心血管疾病中的应用研究提供有价值的指导，而且应该为使用熵来分析可穿戴医疗设备测量的生理信号的不规则性和/或复杂性提供基础。
