Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot
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, wher...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-03-01
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| Series: | Frontiers in Computational Neuroscience |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fncom.2018.00013/full |
| _version_ | 1819097109563965440 |
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| author | Jantsje H. Pasma Lorenz Assländer Lorenz Assländer Joost van Kordelaar Joost van Kordelaar Digna de Kam Thomas Mergner Alfred C. Schouten Alfred C. Schouten |
| author_facet | Jantsje H. Pasma Lorenz Assländer Lorenz Assländer Joost van Kordelaar Joost van Kordelaar Digna de Kam Thomas Mergner Alfred C. Schouten Alfred C. Schouten |
| author_sort | Jantsje H. Pasma |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T00:09:52Z |
| format | Article |
| id | doaj.art-7049bbd1f86b42c88786d0f35c824aa8 |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-12-22T00:09:52Z |
| publishDate | 2018-03-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-7049bbd1f86b42c88786d0f35c824aa82022-12-21T18:45:28ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882018-03-011210.3389/fncom.2018.00013305140Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid RobotJantsje H. Pasma0Lorenz Assländer1Lorenz Assländer2Joost van Kordelaar3Joost van Kordelaar4Digna de Kam5Thomas Mergner6Alfred C. Schouten7Alfred C. Schouten8Department of Biomechanical Engineering, Delft University of Technology, Delft, NetherlandsDepartment of Neurology, University Clinics Freiburg, Freiburg, GermanySensorimotor Performance Lab, University of Konstanz, Konstanz, GermanyDepartment of Biomechanical Engineering, Delft University of Technology, Delft, NetherlandsDepartment of Biomechanical Engineering, Institute for Biomedical Technology and Technical Medicine (MIRA), University of Twente, Enschede, NetherlandsDepartment of Rehabilitation, Donders Centre for Neuroscience, Radboud University Medical Center, Nijmegen, NetherlandsDepartment of Neurology, University Clinics Freiburg, Freiburg, GermanyDepartment of Biomechanical Engineering, Delft University of Technology, Delft, NetherlandsDepartment of Biomechanical Engineering, Institute for Biomedical Technology and Technical Medicine (MIRA), University of Twente, Enschede, NetherlandsThe 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.http://journal.frontiersin.org/article/10.3389/fncom.2018.00013/fullbalance control modelsystem identificationparameter estimationroboticshuman balance control |
| spellingShingle | Jantsje H. Pasma Lorenz Assländer Lorenz Assländer Joost van Kordelaar Joost van Kordelaar Digna de Kam Thomas Mergner Alfred C. Schouten Alfred C. Schouten Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot Frontiers in Computational Neuroscience balance control model system identification parameter estimation robotics human balance control |
| title | Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot |
| title_full | Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot |
| title_fullStr | Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot |
| title_full_unstemmed | Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot |
| title_short | Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot |
| title_sort | evidence in support of the independent channel model describing the sensorimotor control of human stance using a humanoid robot |
| topic | balance control model system identification parameter estimation robotics human balance control |
| url | http://journal.frontiersin.org/article/10.3389/fncom.2018.00013/full |
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