Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot

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.

Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance

“…In retrospect, a stimulus with an amplitude smaller than 2° would have been a better choice since a 2° stimulus can cause falls in subjects with abnormally low neural controller stiffness and torque feedback (Figure 10). Other similar recent studies have used lower amplitudes (0.5 and 1°) (13, 15, 19). Lower amplitudes have the additional potential benefit that subjects may not even perceive that their balance is being perturbed, and yet they respond reliably even to a 0.5° stimulus (6).…”

“…Additionally, the magnitude of frequency spectral components of the waveform based directly on a maximal length ternary number sequence is approximately flat out to a frequency of about 2 Hz = 1/(2 * 25 samples per sequence number/100 samples/s) and then diminishes. Since we use the mathematically integrated waveform to control the angular tilt position of the surface or visual surround, the magnitude of spectral components of the integrated stimulus declines in proportion to inverse frequency [see Figure 3 in (19) to see power spectrum representation of a stimulus nearly identical to our stimulus].…”

Reductions in body sway responses to a rhythmic support surface tilt perturbation can be caused by other mechanisms than prediction

“…The relation of stimulus input and body sway evoked by the stimulus provides insight into the dynamics of the control mechanism. Several studies succeeded in reproducing this relation of stimulus and sway response using model (Peterka 2002;Mergner et al 2003;Assländer et al 2015;Pasma et al 2017), and robot simulations (Mergner et al 2009;Hettich et al 2014;Pasma et al 2018). The identified control mechanisms are solely based on delayed sensory feedback and do not contain any predictive components.…”

Evaluating Robot Posture Control and Balance by Comparison to Human Subjects using Human Likeness Measures

“…The time delay represents all the delays in the control loop. In order to simulate a robot control experiment similar to the ones performed with the robot Posturob II in (Pasma et al, 2018) the system has been simulated in "closed-eyes" conditions. The coefficient W vis is thus set to zero.…”

“…B . The IC control scheme as presented in (Pasma et al, 2018). The three weights W prop , W vest , and W vis are associated with proprioception (α BF ), vestibular signal (α BS ) and vision (α BS ) respectively.…”