Mörtl Alexander, Lorenz Tamara, Vlaskamp Björn N S, Gusrialdi Azwirman, Schubö Anna, Hirche Sandra
Institute of Automatic Control Engineering, Technische Universität München, Munich, Germany,
Biol Cybern. 2012 Jul;106(4-5):241-59. doi: 10.1007/s00422-012-0492-8. Epub 2012 May 31.
Human interaction partners tend to synchronize their movements during repetitive actions such as walking. Research of inter-human coordination in purely rhythmic action tasks reveals that the observed patterns of interaction are dominated by synchronization effects. Initiated by our finding that human dyads synchronize their arm movements even in a goal-directed action task, we present a step-wise approach to a model of inter-human movement coordination. In an experiment, the hand trajectories of ten human dyads are recorded. Governed by a dynamical process of phase synchronization, the participants establish in-phase as well as anti-phase relations. The emerging relations are successfully reproduced by the attractor dynamics of coupled phase oscillators inspired by the Kuramoto model. Three different methods on transforming the motion trajectories into instantaneous phases are investigated and their influence on the model fit to the experimental data is evaluated. System identification technique allows us to estimate the model parameters, which are the coupling strength and the frequency detuning among the dyad. The stability properties of the identified model match the relations observed in the experimental data. In short, our model predicts the dynamics of inter-human movement coordination. It can directly be implemented to enrich human-robot interaction.
在诸如行走等重复性动作中，人类互动伙伴往往会使他们的动作同步。对纯节奏性动作任务中的人际协调研究表明，观察到的互动模式主要由同步效应主导。基于我们的发现，即人类二元组即使在目标导向的动作任务中也会使他们的手臂动作同步，我们提出了一种构建人际运动协调模型的逐步方法。在一项实验中，记录了十个二元组人类的手部轨迹。在相位同步的动态过程支配下，参与者建立了同相和反相关系。受Kuramoto模型启发的耦合相位振荡器的吸引子动力学成功再现了出现的关系。研究了三种将运动轨迹转换为瞬时相位的不同方法，并评估了它们对模型与实验数据拟合的影响。系统识别技术使我们能够估计模型参数，即二元组之间的耦合强度和频率失谐。所识别模型的稳定性特性与实验数据中观察到的关系相匹配。简而言之，我们的模型预测了人际运动协调的动态过程。它可以直接用于丰富人机交互。
