Evidence in support of the Independent Channel Model describing the sensorimotor control of human stance using a humanoid robot

Evidence in support of the Independent Channel Model describing the sensorimotor control of human stance using a humanoid robot

Pasma, J.H. (TU Delft Biomechatronics & Human-Machine Control)
Assländer, Lorenz (University of Freiburg; University of Konstanz)
van Kordelaar, J. (TU Delft Biomechatronics & Human-Machine Control; University of Twente)
de Kam, Digna (Radboud Universiteit Nijmegen)
Mergner, Thomas (University of Freiburg)
Schouten, A.C. (TU Delft Biomechatronics & Human-Machine Control; Radboud Universiteit Nijmegen)

2018

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control.

balance control model
system identification
parameter estimation
robotics
human balance control
OA-Fund TU Delft

http://resolver.tudelft.nl/uuid:d849fcad-2c77-461d-bbc7-bb801bf87638

https://doi.org/10.3389/fncom.2018.00013

1662-5188

Frontiers in Computational Neuroscience, 12

Institutional Repository

journal article

© 2018 J.H. Pasma, Lorenz Assländer, J. van Kordelaar, Digna de Kam, Thomas Mergner, A.C. Schouten