Abstract
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.
Highlights
Human balance control helps us to keep our body in an upright position during daily life activities
Computer simulations and robot experiments were robust with respect to the noise and the inaccuracies, and control stability was maintained throughout all conditions
This study showed that the Independent Channel (IC) model, a descriptive linear model in the frequency domain, is able to imitate human balance behavior in both the time and frequency domain, this both in computer simulations and robot experiments
Summary
Human balance control helps us to keep our body in an upright position during daily life activities. In human balance control several systems are involved, like the sensory systems, the nervous system, and the muscles, which interact continuously with each other (Horak, 1997). Proprioceptive (muscle spindles and Golgi tendon organs) and vestibular cues are integrated by the nervous system to obtain body orientation with respect to the visual scene, the support surface and gravitoinertial space, respectively. The nervous system integrates these sensory cues to generate a desired torque signal realized by the muscles. This torque results in a corrective movement to bring the body toward the desired upright position. Balance control can be described as a closed loop control system (Collins and De Luca, 1993; Peterka, 2002; van der Kooij et al, 2005)
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