Julius Wolff Institute for Biomechanics and Musculoskeletal Regeneration, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.
Ann Biomed Eng. 2018 Jan;46(1):60-70. doi: 10.1007/s10439-017-1934-1. Epub 2017 Sep 25.
Stride-to-stride time intervals during human walking are characterised by predictability and statistical persistence quantified by sample entropy (SaEn) and detrended fluctuation analysis (DFA) which indicates a time dependency in the gait pattern. However, neither analyses quantify time dependency in a physical or physiological interpretable time scale. Recently, entropic half-life (ENT½) has been introduced as a measure of the time dependency on an interpretable time scale. A novel measure of time dependency, based on DFA, statistical persistence decay (SPD), was introduced. The present study applied SaEn, DFA, ENT½, and SPD in known theoretical signals (periodic, chaotic, and random) and stride-to-stride time intervals during overground and treadmill walking in healthy subjects. The analyses confirmed known properties of the theoretical signals. There was a significant lower predictability (p = 0.033) and lower statistical persistence (p = 0.012) during treadmill walking compared to overground walking. No significant difference was observed for ENT½ and SPD between walking condition, and they exhibited a low correlation. ENT½ showed that predictability in stride time intervals was halved after 11-14 strides and SPD indicated that the statistical persistency was deteriorated to uncorrelated noise after ~50 strides. This indicated a substantial time memory, where information from previous strides affected the future strides.
人类行走时的步间时间间隔具有可预测性和统计持久性，可通过样本熵（SaEn）和去趋势波动分析（DFA）来量化，这表明步态模式存在时间依赖性。然而，这两种分析都无法在物理或生理上可解释的时间尺度上量化时间依赖性。最近，熵半衰期（ENT½）已被引入作为衡量可解释时间尺度上的时间依赖性的度量。一种新的基于 DFA 的时间依赖性度量，即统计持久性衰减（SPD），已经被引入。本研究在已知的理论信号（周期性、混沌性和随机性）以及健康受试者在地面和跑步机上行走的步间时间间隔中应用了 SaEn、DFA、ENT½和 SPD。分析结果证实了理论信号的已知特性。与在地面行走相比，跑步机行走时的可预测性（p=0.033）和统计持久性（p=0.012）显著降低。在行走条件下，ENT½和 SPD 之间没有观察到显著差异，它们之间的相关性较低。ENT½ 表明，步间时间间隔的可预测性在 11-14 步后减半，而 SPD 表明，在~50 步后，统计持久性恶化到不相关的噪声。这表明存在大量的时间记忆，即前几步的信息会影响未来的步。
