Abstract
Human balance control is a complex feedback system that must be adaptable and robust in an infinitely varying external environment. It is probable that there are many concurrent control loops occurring in the central nervous system that achieve stability for a variety of postural perturbations. Though many engineering models of human balance control have been tested, no models of how these controllers might operate within the nervous system have yet been developed. We have created a synthetic nervous system that provides Proportional-Derivative (PD) control to a single jointed inverted pendulum model of human balance. In this model, angular position is measured at the ankle and corrective torque is applied about the joint to maintain a vertical orientation. The neural network computes the derivative of the angular position error, which allows the system to maintain an unstable equilibrium position and provide corrections at perturbations. This controller demonstrates the most basic components of human balance control, and will be used as the basis for more complex controllers and neuromechanical models in future work.
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Acknowledgements
The authors would like to acknowledge the support by the NASA Office of the Chief Technologist, Grant Number NNX12AN24H.
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Hilts, W.W., Szczecinski, N.S., Quinn, R.D., Hunt, A.J. (2017). Simulation of Human Balance Control Using an Inverted Pendulum Model. In: Mangan, M., Cutkosky, M., Mura, A., Verschure, P., Prescott, T., Lepora, N. (eds) Biomimetic and Biohybrid Systems. Living Machines 2017. Lecture Notes in Computer Science(), vol 10384. Springer, Cham. https://doi.org/10.1007/978-3-319-63537-8_15
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DOI: https://doi.org/10.1007/978-3-319-63537-8_15
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