Dynamics of human postural transitions.

Abstract

In the present study, the authors examined transitions between postural coordination modes involved in human stance. The analysis was motivated by dynamical theories of pattern formation, in which coordination modes and transitions between modes are emergent, self-organized properties of the dynamics of animal-environment systems. In 2 experiments, standing participants tracked a moving target with the head. Results are consistent with the hypothesis that changes in body coordination follow typical nonequilibrium phase transitions, exhibiting multistability, bifurcation, critical fluctuations, hysteresis, and critical slowing down. The findings suggest that posture may be organized in terms of dynamical principles and favor the existence of general and common principles governing pattern formation and flexibility in complex systems.

A closed loop musculoskeletal model of postural coordination dynamics

“…These observations hold for all participants and are in accordance with [11], [1], [13], even though the actual transition frequency and joint amplitudes depend on the specific subject body type.…”

“…In a previous work [4], we studied in more details Bardy et al's [1] paradigm with a method similar to the one used in [3]. Then we implemented the obtained coordination modes onto the HOAP-3 and HRP2 humanoid robots.…”

“…Martin et al [3] used a constrained optimization process to analyze Bardy et al's [1] results, and showed that the location of the center of pressure (CoP) can drive the selection of the coordination mode. In a previous work [4], we studied in more details Bardy et al's [1] paradigm with a method similar to the one used in [3].…”

“…During a visual tracking task, Bardy et al [1] analyzed, in the framework of coordination dynamics [2], the joint coordination in the sagittal plane. They proposed the use of a collective variable to describe in a simple way the complex dynamical biological-segmental-articular-muscularcouplings.…”

Laterally focused attention modulates asymmetric coupling in rhythmic interlimb coordination

“…For the purpose of making comparisons across the three frequency conditions, the time series of / were resampled with respect to cycle duration (De Poel et al, in press; for related procedures, see Bardy, Oullier, Bootsma, & Stoffregen, 2002;Court et al, 2002) prior to the analysis of the return signal, using an anti-aliasing (low-pass) finite impulse response (FIR) filter with a 10-point Kaiser window (available in the Matlab Ò Signal Processing Toolbox). Subsequently, the return signal (i.e., the evolution of / after release of the perturbed arm) was analyzed using the procedure outlined by Post et al (2000b).…”