4.2 Article

Multisensory control of human upright stance

期刊

EXPERIMENTAL BRAIN RESEARCH
卷 171, 期 2, 页码 231-250

出版社

SPRINGER
DOI: 10.1007/s00221-005-0256-y

关键词

postural control; dynamic model; multisensory integration; sensor fusion; set point principle; vestibular system

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The interaction of different orientation senses contributing to posture control is not well understood. We therefore performed experiments in which we measured the postural responses of normal subjects and vestibular loss patients during perturbation of their stance. Subjects stood on a motion platform with their eyes closed and auditory cues masked. The perturbing stimuli consisted of either platform tilts or external torque produced by force-controlled pull of the subjects' body on a stationary platform. Furthermore, we presented trials in which these two stimuli were applied when the platform was body-sway referenced (i.e., coupled 1:1 to body position, by which ankle joint proprioceptive feedback is essentially removed). We analyzed subjects' postural responses, i.e., the excursions of their center of mass (COM) and center of pressure (COP), using a systems analysis approach. We found gain and phase of the responses to vary as a function of stimulus frequency and in relation to the absence versus presence of vestibular and proprioceptive cues. In addition, gain depended on stimulus amplitude, reflecting a non-linearity in the control. The experimental results were compared to simulation results obtained from an 'inverted pendulum' model of posture control. In the model, sensor fusion mechanisms yield internal estimates of the external stimuli, i.e., of the external torque (pull), the platform tilt and gravity. These estimates are derived from three sensor systems: ankle proprioceptors, vestibular sensors and plantar pressure sensors (somatosensory graviceptors). They are fed as global set point signals into a local control loop of the ankle joints, which is based on proprioceptive negative feedback. This local loop stabilizes the body-on-foot support, while the set point signals upgrade the loop into a body-in-space control. Amplitude non-linearity was implemented in the model in the form of central threshold mechanisms. In model simulations that combined sensor fusion and thresholds, an automatic context-specific sensory re-weighting across stimulus conditions occurred. Model parameters were identified using an optimization procedure. Results suggested that in the sway-referenced condition normal subjects altered their postural strategy by strongly weighting feedback from plantar somatosensory force sensors. Taking this strategy change into account, the model's simulation results well paralleled all experimental results across all conditions tested.

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