Data-driven spectral analysis for coordinative structures in periodic human locomotion
Data-driven spectral analysis for coordinative structures in periodic human locomotion
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DOI：
10.1038/s41598-019-53187-1
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发表时间：
2019-11
影响因子：
4.6
通讯作者：
Keisuke Fujii;Naoya Takeishi;Benio Kibushi;M. Kouzaki;Y. Kawahara
中科院分区：
文献类型：
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作者：
Keisuke Fujii;Naoya Takeishi;Benio Kibushi;M. Kouzaki;Y. Kawahara
生物有机体动态和灵活地操作大量组件。作为一种冗余控制机制，多个部件之间的低维协调结构已被研究。然而，从传统的统计降维方法提取的结构并不反映原则上的动力学性质。在这里，我们认为协调结构的生物周期系统的未知和冗余的动力学作为一个非线性极限环振荡，并应用数据驱动的算子理论谱分析，得到的动力学性质的协调结构，如频率和相位从估计的特征值和特征函数的组合操作。以人体行走过程中的节段角度序列为例，首先提取了基于动力学的协调结构，即步态频率谐波中与速度无关的协调结构。其次，我们发现了速度依赖的时间演化行为的相位通过估计本征函数，通过我们的方法对传统的低维结构。我们还使用双摆和步行模型的仿真数据验证了我们的方法。我们的运动分析的结果表明，我们的方法可以是有用的，从非线性动力系统的角度来分析生物周期现象。
Living organisms dynamically and flexibly operate a great number of components. As one of such redundant control mechanisms, low-dimensional coordinative structures among multiple components have been investigated. However, structures extracted from the conventional statistical dimensionality reduction methods do not reflect dynamical properties in principle. Here we regard coordinative structures in biological periodic systems with unknown and redundant dynamics as a nonlinear limit-cycle oscillation, and apply a data-driven operator-theoretic spectral analysis, which obtains dynamical properties of coordinative structures such as frequency and phase from the estimated eigenvalues and eigenfunctions of a composition operator. Using segmental angle series during human walking as an example, we first extracted the coordinative structures based on dynamics; e.g. the speed-independent coordinative structures in the harmonics of gait frequency. Second, we discovered the speed-dependent time-evolving behaviours of the phase by estimating the eigenfunctions via our approach on the conventional low-dimensional structures. We also verified our approach using the double pendulum and walking model simulation data. Our results of locomotion analysis suggest that our approach can be useful to analyse biological periodic phenomena from the perspective of nonlinear dynamical systems.