An adaptive model of sensory integration in a dynamic environment applied to human stance control

Abstract

An adaptive estimator model of human spatial orientation is presented. The adaptive model dynamically weights sensory error signals. More specific, the model weights the difference between expected and actual sensory signals as a function of environmental conditions. The model does not require any changes in model parameters. Differences with existing models of spatial orientation are that: (1) environmental conditions are not specified but estimated, (2) the sensor noise characteristics are the only parameters supplied by the model designer, (3) history-dependent effects and mental resources can be modelled, and (4) vestibular thresholds are not included in the model; instead vestibular-related threshold effects are predicted by the model. The model was applied to human stance control and evaluated with results of a visually induced sway experiment. From these experiments it is known that the amplitude of visually induced sway reaches a saturation level as the stimulus level increases. This saturation level is higher when the support base is sway referenced. For subjects experiencing vestibular loss, these saturation effects do not occur. Unknown sensory noise characteristics were found by matching model predictions with these experimental results. Using only five model parameters, far more than five data points were successfully predicted. Model predictions showed that both the saturation levels are vestibular related since removal of the vestibular organs in the model removed the saturation effects, as was also shown in the e xperiments. It seems that the nature of these vestibular-related threshold effects is not physical, since in the model no threshold is included. The model results suggest that vestibular-related thresholds are the result of the processing of noisy sensory and motor output signals. Model analysis suggests that, especially for slow and small movements, the environment postural orientation can not be estimated optimally, which causes sensory illusions. The model also confirms the experimental finding that postural orientation is history dependent and can be shaped by instruction or mental knowledge. In addition the model predicts that: (1) vestibular-loss patients cannot handle sensory conflicting situations and will fall down, (2) during sinusoidal support-base translations vestibular function is needed to prevent falling, (3) loss of somatosensory information from the feet results in larger postural sway for sinusoidal support-base translations, and (4) loss of vestibular function results in falling for large support-base rotations with the eyes closed. These predictions are in agreement with experimental results.

Development of multisensory reweighting for posture control in children

“…Such amplitudedependent gain changes indicate some type of nonlinearity, for example, adaptation. In adults, amplitude-dependent gain changes have been reported for visual scene motion (Peterka and Benolken, 1995) and have been reproduced in models with sensory reweighting (Carver et al, 2005; van der Kooij et al, 2001). This amplitude-dependent gain change has important functional significance.…”

Event-Based Data Acquisition and Reconstruction—Mathematical Background

“…As discussed by Van Der Kooij, Jacobs, Koopman, and Grootenboer (1999) and Van Der Kooij et al (2001), such sensors are utilised with appropriate sensor integration. In control system terms, sensor redundancy can be incorporated into statespace control using observers or Kalman-Bucy filters (Kwakernaak and Sivan, 1972;Goodwin et al, 2001); this is the dual of the optimal control problem.…”

Coordinating Feet in Bipedal Balance

“…Models of human balance during stance typically take the form of an inverted pendulum with one or more links [1], [2]. Torques about some of these links represent the combined action of two joints or actuators, for example, the left and right ankles, but do not describe the individual contribution of each actuator.…”