Mujib Kamal Shahul, Babini Mohammad Hossein, Krejcar Ondrej, Namazi Hamidreza
School of Engineering, Monash University Malaysia, Selangor, Malaysia.
Center for Basic and Applied Research, Faculty of Informatics and Management, University of Hradec Králové, Hradec Králové, Czechia.
Front Physiol. 2020 Nov 25;11:602027. doi: 10.3389/fphys.2020.602027. eCollection 2020.
Walking is an everyday activity in our daily life. Because walking affects heart rate variability, in this research, for the first time, we analyzed the coupling among the alterations of the complexity of walking paths and heart rate. We benefited from the fractal theory and sample entropy to evaluate the influence of the complexity of paths on the complexity of heart rate variability (HRV) during walking. We calculated the fractal exponent and sample entropy of the R-R time series for nine participants who walked on four paths with various complexities. The findings showed a strong coupling among the alterations of fractal dimension (an indicator of complexity) of HRV and the walking paths. Besides, the result of the analysis of sample entropy also verified the obtained results from the fractal analysis. In further studies, we can analyze the coupling among the alterations of the complexities of other physiological signals and walking paths.
步行是我们日常生活中的一项日常活动。由于步行会影响心率变异性,在本研究中,我们首次分析了步行路径复杂性变化与心率之间的耦合关系。我们利用分形理论和样本熵来评估路径复杂性对步行过程中心率变异性(HRV)复杂性的影响。我们计算了九名参与者在四条具有不同复杂性的路径上行走时R-R时间序列的分形指数和样本熵。研究结果表明,HRV的分形维数(复杂性指标)变化与步行路径之间存在很强的耦合关系。此外,样本熵分析结果也验证了分形分析所得结果。在进一步的研究中,我们可以分析其他生理信号复杂性变化与步行路径之间的耦合关系。