Neuroscience 2005 Abstract
| Presentation Number: | 868.3 |
|---|---|
| Abstract Title: | Influences of mechanical stability on neural control demands in postural responses during lateral perturbations. |
| Authors: |
Scrivens, J. E.*1
; DeWeerth, S. P.1
; Ting, L. H.1
1Georgia Inst. of Technology, Atlanta, GA |
| Primary Theme and Topics |
Sensory and Motor Systems - Kinematics and EMG -- Posture |
| Session: |
868. Posture: Animal and Clinical Studies Poster |
| Presentation Time: | Wednesday, November 16, 2005 10:00 AM-11:00 AM |
| Location: | Washington Convention Center - Hall A-C, Board # BB20 |
| Keywords: | KINEMATICS, CONTROL, MODELING, MOTOR CONTROL |
It has been shown that EMGs during postural responses in cats can be described by a feedback controller on center of mass (COM) kinematics (Lockhart 2005 SfN Abstract). We also know empirically that mechanical stability due to increasing the base of support (BOS) influences neural control demands. Using a robotic model of a cat to explore the relationship between feedback control gain, neural delay, and mechanical stability we demonstrate quantitative tradeoffs between mechanical and neural stabilization. We hypothesize that neural control gains must be increased to maintain stability under perturbation when the BOS is reduced.
Our robot is a two-legged device with one degree of freedom per leg. It simulates the lateral motion of a cat through abduction/adduction of the hip/shoulder combination. Muscle activation is controlled using delayed (30 ms) and non-delayed feedback on joint kinematics to create neural and passive feedback loops. The advantage of the robot is that the mechanics of the system are more realistic than in a simulation, as the robot feet are compliant and can lift off the support surface. Postural responses of the robot are analyzed in response to lateral translations of the support surface. The stance width is varied to change the mechanical stability of the robot while the minimal active control gains required to stabilize the system are determined.
Similar to a cat, the robot leans to the side when perturbed, then returns the COM to the center of the base of support due to the low passive stiffness and delayed active control. We observe a 500% increase in the necessary control gain as we decrease stance width by 53%. Therefore there is a significant decrease in neural control gain with wide stance. This correlates with experimental findings in cat and human postural responses where EMG decreases as stance width increases (Henry et al. 2001). Our results suggest that even a small increase in stance width can compensate for a decrease in neural control ability associated with motor impairments.
Our robot is a two-legged device with one degree of freedom per leg. It simulates the lateral motion of a cat through abduction/adduction of the hip/shoulder combination. Muscle activation is controlled using delayed (30 ms) and non-delayed feedback on joint kinematics to create neural and passive feedback loops. The advantage of the robot is that the mechanics of the system are more realistic than in a simulation, as the robot feet are compliant and can lift off the support surface. Postural responses of the robot are analyzed in response to lateral translations of the support surface. The stance width is varied to change the mechanical stability of the robot while the minimal active control gains required to stabilize the system are determined.
Similar to a cat, the robot leans to the side when perturbed, then returns the COM to the center of the base of support due to the low passive stiffness and delayed active control. We observe a 500% increase in the necessary control gain as we decrease stance width by 53%. Therefore there is a significant decrease in neural control gain with wide stance. This correlates with experimental findings in cat and human postural responses where EMG decreases as stance width increases (Henry et al. 2001). Our results suggest that even a small increase in stance width can compensate for a decrease in neural control ability associated with motor impairments.
Supported by NIH EB00786-01
Sample Citation:
[Authors]. [Abstract Title]. Program No. XXX.XX. 2005 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2005. Online.
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