Humans self-organise balance control strategies on a dynamic platform.

The human body continuously detects and predicts environmental disturbances and adaptively generates corrective responses to maintain standing balance. According to dynamical systems theory, these responses are self-organised, emerging naturally during human-environment interaction. Building on this, we introduce a model predictive controller (MPC) framework to simulate postural responses to environmental perturbations caused by a dynamic underfloor platform. The model uses a four-segment biomechanical system with sensory feedback and predicts the optimal response for maintaining balance, while accounting for biomechanical constraints, as the frequency of mechanical perturbation increases. The model findings, validated by the performance of nine young participants, provide evidence that indeed postural strategies emerge autonomously from the body's dynamic interaction with the mechanical perturbation, without manual tuning. The emergent behaviour involves non-linear transitions from ankle to knee strategy, followed by transition in the relative motion between the centre of pressure and centre of mass as platform frequency increases. We demonstrate that effective models should include ankle, knee, and hip joint motion, with hip motion being less mechanically efficient in young people. The proposed framework also overcomes the limitations of traditional models which fail to capture the transitional dynamics and provides novel insights into the self-organising nature of postural responses.