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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    This study used a simulated inverted pendulum to investigate human sensorimotor control, revealing insights into balance and adaptation. Results suggest vision is crucial for controlling unstable systems, modeled by a proportional-derivative controller.

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    Area of Science:

    • Neuroscience
    • Robotics
    • Human-Computer Interaction

    Background:

    • Sensorimotor control is vital for maintaining balance, stability, and adapting to environmental changes.
    • Understanding human control strategies for unstable systems is crucial for developing advanced robotics and rehabilitation technologies.

    Purpose of the Study:

    • To introduce and validate a simulated inverted pendulum as a tool for studying human sensorimotor control.
    • To investigate how variations in pendulum length affect human control inputs and system stabilization.
    • To model human sensorimotor control of an unstable system using a computational approach.

    Main Methods:

    • Development of a simulated inverted pendulum task.
    • Recruitment of human participants to interact with the simulation.
    • Analysis of participant performance, including stabilization time and control input.
    • Modeling of experimental data using a proportional-derivative (PD) controller with time delay.

    Main Results:

    • The simulated inverted pendulum presented comparable control challenges to a physical one.
    • Increased pendulum length led to longer system stabilization times.
    • Control input varied non-monotonically but predictably with pendulum length.
    • Experimental data closely matched a PD controller model with a 140 ms time delay, consistent with human visuomotor delay.

    Conclusions:

    • A simulated inverted pendulum is a viable tool for studying human sensorimotor control of unstable systems.
    • Vision plays a significant role in the human control of dynamic and unstable environments.
    • The findings support the use of PD control models with time delays to represent human sensorimotor behavior.