Humans self-organise balance control strategies on a dynamic platform

Area of Science:

• Biomechanics
• Human Movement Science
• Systems Neuroscience

Background:

• Human postural control involves continuous detection and adaptive responses to environmental disturbances.
• Dynamical systems theory suggests these responses are self-organized and emerge from human-environment interaction.

Purpose of the Study:

• To introduce and validate a model predictive controller (MPC) framework for simulating human postural responses to dynamic perturbations.
• To investigate the autonomous emergence of postural strategies and their non-linear transitions.

Main Methods:

• A four-segment biomechanical model with sensory feedback was developed.
• The MPC framework simulated responses to varying frequencies of underfloor platform perturbations.
• Model findings were validated against experimental data from nine young participants.

Main Results:

• Postural strategies emerged autonomously, without manual tuning, from dynamic interaction with perturbations.
• Non-linear transitions were observed from ankle to knee strategies as perturbation frequency increased.
• Hip joint motion was found to be less mechanically efficient in young individuals.

Conclusions:

• Human postural responses to environmental perturbations are self-organizing and emerge dynamically.
• The proposed MPC framework accurately captures transitional dynamics, overcoming limitations of traditional models.
• Understanding these emergent strategies offers novel insights into the self-organizing nature of balance control.