Abstract
We tested whether human postural responses can be described in terms of feedback control gains, and whether these gains are scaled by the central nervous system to accommodate biomechanical constraints. A feedback control model can describe postural responses for a wide range of perturbations, but biomechanical constraints - such as on the torque that can be exerted on the ground - make a single set of feedback gains inappropriate for all perturbations. To observe how postural responses change with perturbation magnitude, we applied fast, backward perturbations of magnitudes 3-15 cm to 13 healthy young volunteers (4 men, 9 women, aged 20-32 years). We used a 3-segment, sagittal-plane biomechanical model and a linear state feedback controller to reproduce the observed postural responses. Optimization was used to identify the best-fit feedback control gains for each trial. Results showed that trajectories of joint angles and joint torques were scaled with perturbation magnitude. This scaling occurred gradually, rather than abruptly changing at magnitudes where biomechanical constraints became active. Feedback gains were found to fit reasonably well with data (R2=0.92) and to be multivariate and heterogenic in character, meaning that the torque produced at any joint is generally a function of motions not only at the same joint, but other joints as well. Hip gains increased and ankle gains decreased nearly linearly with perturbation magnitude, in accordance with biomechanical limitations on ground reaction torque. These results indicate that postural adjustments can be described as a single feedback control scheme, with scalable heterogenic gains that are adjusted according to biomechanical constraints.
Original language | English (US) |
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Pages (from-to) | 417-427 |
Number of pages | 11 |
Journal | Experimental Brain Research |
Volume | 154 |
Issue number | 4 |
DOIs | |
State | Published - Feb 2004 |
Externally published | Yes |
Keywords
- Balance
- Biomechanics
- Equilibrium
- Motor control
- Posture
ASJC Scopus subject areas
- General Neuroscience