Contribution of Sensorimotor Integration to Spinal Stabilization in Humans

Abstract

The control of upper body (UB) orientation relative to the pelvis in the frontal plane was characterized by analyzing responses to external perturbations consisting of continuous pelvis tilts (eyes open [EO] and eyes closed [EC]) and visual surround tilts (EO) at various amplitudes. Lateral sway of the lower body was prevented on all tests. UB sway was analyzed by calculating impulse-response functions (IRFs) and frequency-response functions (FRFs) from 0.023 to 10.3 Hz for pelvis tilt tests and FRFs from 0.041 to 1.5 Hz for visual tests. For pelvis tilt tests, differences between FRFs were limited to frequencies<3 Hz and were dependent on stimulus amplitude. IRFs were nearly identical across all pelvis tilt tests for the first 0.2 s, but showed amplitude-dependent changes in their time course at longer time lags. The availability of visual orientation cues (EO vs. EC) had only a small effect on the UB sway during pelvis tilt tests. This small effect of vision was consistent with the small UB sway evoked on visual tilt tests. Experimental results were interpreted using a feedback model of UB orientation control that included time-delayed sensory integration, short-latency reflexive mechanisms, and intrinsic biomechanical properties of the UB. Variation in model parameters indicated that subjects shifted toward reliance on vestibular information and away from proprioceptive information as pelvis tilt amplitudes increased. For visual tilt stimuli, model parameters indicated that subjects shifted toward reliance on vestibular and proprioceptive information and away from visual information as the stimulus amplitude increased.

Intrinsic and Extrinsic Contributions to Seated Balance in the Sagittal and Coronal Planes: Implications for Trunk Control After Spinal Cord Injury

“…The value for τ 11 was comparable to our value for this parameter in the ML direction but not in the AP direction, but our values of τ sl for both directions and injury groups were lower than those reported by Goodworth and Peterka. 7 The increase in values of τ 11 in both AP and ML directions after spinal cord injury may again underscore the observation that spinal cord injury not only reduces the magnitudes of the extrinsic parameters but also results in further delay of their effects, perhaps as a consequence of damage to the central and/or peripheral nervous structures.One advantage of estimating the parameters in the time domain was the ability to simultaneously obtain the joint torques generated by the model. The intrinsic and extrinsic joint torques from the 2 control mechanisms were of interest.…”

“…7 In that method, magnitude and phase of the experimental data are computed and fit to equivalent quantities of the linear model (Equation 4). The approach requires extensive preprocessing of the experimental data and smoothing of the frequency-domain signal functions.…”

“…The path containing B and τ sl modeled a short-latency stretch-reflex pathway. 7 Active control was assumed to be a proportional- Using the transfer function between the change in trunk angle (θ B ) and platform translation (X) in Figure 3, the linear model of the trunk in the frequency domain was written as: 7,15 ( 4) where θ B = change in trunk angle, m = mass of the trunk, h = height of the center of mass from the support platform, J = moment of inertia about the combined hip/lumbar joint, g = acceleration due to gravity, X(s) is the Laplace transform of the platform input disturbance, and s is the Laplace transform parameter. The quantity M(s) in Equation 4 is defined as:…”

“…Goodworth and Peterka 7 investigated both active and passive contributions to trunk stability in the coronal plane and assumed that upper body control either followed a similar trend as whole body control, in which sensory integration mechanisms were dominated by long feedback delays, or was dominated by intrinsic mechanisms and/or rapid stretch reflexes characterized by short time delays. That study was the first to derive explicit values for extrinsic and intrinsic parameters that mediate postural balance in the seated human.…”

Modelling human balance using switched systems with linear feedback control

“…In spite of recent advances in revealing the mechanisms responsible for balancing during quiet standing (see [1][2][3][4][5][6][7][8][9][10][11]) the physiological mechanisms are far from being understood. In recent years, there has been a growing interest among scientists to use mathematical modelling and numerical simulations to gain new insights into the problem of balancing.…”