Modeling inter-human movement coordination: synchronization governs joint task dynamics

Abstract

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.

Movement synchronization fails during non-adaptive human-robot interaction

“…Summing up it was found, that with a non-adaptive robot, synchronization does not emerge naturally like it would during the interaction of two humans in a similar task (see [7], [11]). This is in line with a suggestion of [6], claiming that if the robot never changes its behavior, this could be uncomfortable and the human would stop adapting his/her behavior.…”

“…In line with [11,12], the relative phase difference between movement signals was calculated per trial and averaged for each start condition respectively. If in-phase synchronization occurred, a peak for data in the 0-20° region should be found, for anti-phase synchronization in the 160-180° region.…”

“…As a next step, an exploration of the appropriate adaptation would be required. The synchronization model presented in [11] has to be implemented onto a robotic platform which will allow to test human-robot synchronization behavior.…”

Sensorimotor synchronization: A review of recent research (2006–2012)

“…A dynamic-systems model and several methods for analyzing the interpersonal synchronization of continuous movements have recently been set forth in great detail by Mörtl et al (2012). These authors also presented empirical data from spontaneous synchronization of goal-directed arm movements, though the focus of their article was theoretical and methodological.…”

Comparing different control approaches to implement a human-like virtual player in the mirror game

“…Synergetic movements of two or more people mirroring each other frequently occur in many activities such as handling objects, manipulating a common workpiece, dancing and choir singing ( [1], [2], [3] and references therein). In order to understand the mechanisms that underly the coordination between two humans, interpersonal coordination and synchronization between their motion have been extensively studied over the past few decades [4], [5], [6].…”