Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, 6-3-1 Niijuku, Katsushika, Tokyo 125-8585, Japan.
International Research Center for Neurointelligence, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo 113-0033, Japan.
Sensors (Basel). 2022 Jul 9;22(14):5154. doi: 10.3390/s22145154.
Photoplethysmography is a widely used technique to noninvasively assess heart rate, blood pressure, and oxygen saturation. This technique has considerable potential for further applications-for example, in the field of physiological and mental health monitoring. However, advanced applications of photoplethysmography have been hampered by the lack of accurate and reliable methods to analyze the characteristics of the complex nonlinear dynamics of photoplethysmograms. Methods of nonlinear time series analysis may be used to estimate the dynamical characteristics of the photoplethysmogram, but they are highly influenced by the length of the time series, which is often limited in practical photoplethysmography applications. The aim of this study was to evaluate the error in the estimation of the dynamical characteristics of the photoplethysmogram associated with the limited length of the time series. The dynamical properties were evaluated using recurrence quantification analysis, and the estimation error was computed as a function of the length of the time series. Results demonstrated that properties such as determinism and entropy can be estimated with an error lower than 1% even for short photoplethysmogram recordings. Additionally, the lower limit for the time series length to estimate the average prediction time was computed.
光体积描记法是一种广泛应用于无创评估心率、血压和血氧饱和度的技术。该技术在生理和心理健康监测等领域具有很大的应用潜力。然而，光体积描记图复杂非线性动力学特征的精确和可靠分析方法的缺乏限制了其更先进的应用。非线性时间序列分析方法可用于估计光体积描记图的动力学特征，但这些方法受限于时间序列的长度，而实际的光体积描记图应用中时间序列的长度往往是有限的。本研究旨在评估与时间序列长度有限相关的光体积描记图动力学特征估计的误差。采用递归定量分析评估动力学特性，并将估计误差作为时间序列长度的函数进行计算。结果表明，即使对于短时间的光体积描记记录，确定性和熵等特性也可以以低于 1%的误差进行估计。此外，还计算了估计平均预测时间的时间序列长度下限。
