使用可见性图复杂度分析冥想期间的心率信号。
Analysis of heart rate signals during meditation using visibility graph complexity.
作者信息
Nasrolahzadeh Mahda, Mohammadpoory Zeynab, Haddadnia Javad
机构信息
Department of Biomedical Engineering, Hakim Sabzevari University, Sabzevar, Iran.
出版信息
Cogn Neurodyn. 2019 Feb;13(1):45-52. doi: 10.1007/s11571-018-9501-5. Epub 2018 Aug 27.
Abstract
In the dynamics analysis of heart rate, the complexity of visibility graphs (VGs) is seen as a sign of short term variability in signals. The present study was conducted to investigate the possible impact of meditation on heart rate signals complexity using VG method. In this study, existing heart rate signals in Physionet database were used. The dynamics of the signals were then studied both before and during meditation by examining the complexity of VGs using graph index complexity (GIC). Generally, the obtained results showed that the heart rate signals were more complex during meditation. The simple process of calculating the GIC of VG and its adaptability to the chaotic nature of the biological signals can help in estimating the heart rate complexity in meditation.
摘要
在心率动态分析中，可见性图（VG）的复杂性被视为信号短期变异性的一个标志。本研究旨在使用VG方法探究冥想对心率信号复杂性可能产生的影响。在本研究中，使用了生理信号数据库中的现有心率信号。然后，通过使用图指数复杂性（GIC）检查VG的复杂性，对冥想前和冥想期间的信号动态进行了研究。一般来说，所获得的结果表明，冥想期间心率信号更为复杂。计算VG的GIC的简单过程及其对生物信号混沌特性的适应性有助于估计冥想时的心率复杂性。
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