Modeling of Motorized Orthosis Control
Orthotic devices are defined as externally applied devices that are used to modify the structural and functional characteristics of the neuro-muscular and skeletal systems. The aim of the current study is to improve the control and movement of a robotic arm orthosis by means of an intelligent optimi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/9/12/2453 |
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| author | Iñigo Aramendia Ekaitz Zulueta Daniel Teso-Fz-Betoño Aitor Saenz-Aguirre Unai Fernandez-Gamiz |
| author_facet | Iñigo Aramendia Ekaitz Zulueta Daniel Teso-Fz-Betoño Aitor Saenz-Aguirre Unai Fernandez-Gamiz |
| author_sort | Iñigo Aramendia |
| collection | DOAJ |
| description | Orthotic devices are defined as externally applied devices that are used to modify the structural and functional characteristics of the neuro-muscular and skeletal systems. The aim of the current study is to improve the control and movement of a robotic arm orthosis by means of an intelligent optimization system. Firstly, the control problem settlement is defined with the muscle, brain, and arm model. Subsequently, the optimization control, which based on a differential evolution algorithm, is developed to calculate the optimum gain values. Additionally, a cost function is defined in order to control and minimize the effort that is made by the subject and to assure that the algorithm follows as close as possible the defined setpoint value. The results show that, with the optimization algorithm, the necessary development force of the muscles is close to zero and the neural excitation level of biceps and triceps signal values are getting lower with a gain increase. Furthermore, the necessary development force of the biceps muscle to overcome a load added to the orthosis control system is practically the half of the one that is necessary without the optimization algorithm. |
| first_indexed | 2024-12-12T03:53:45Z |
| format | Article |
| id | doaj.art-3106d73f66f247a9bbbdc95ded2c0e6f |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-12T03:53:45Z |
| publishDate | 2019-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-3106d73f66f247a9bbbdc95ded2c0e6f2022-12-22T00:39:19ZengMDPI AGApplied Sciences2076-34172019-06-01912245310.3390/app9122453app9122453Modeling of Motorized Orthosis ControlIñigo Aramendia0Ekaitz Zulueta1Daniel Teso-Fz-Betoño2Aitor Saenz-Aguirre3Unai Fernandez-Gamiz4Nuclear Engineering and Fluid Mechanics Department, University of the Basque Country UPV/EHU, 01006 Vitoria-Gasteiz, Araba, SpainAutomatic Control and System Engineering Department, University of the Basque Country, UPV/EHU, 01006 Vitoria-Gasteiz, SpainAutomatic Control and System Engineering Department, University of the Basque Country, UPV/EHU, 01006 Vitoria-Gasteiz, SpainAutomatic Control and System Engineering Department, University of the Basque Country, UPV/EHU, 01006 Vitoria-Gasteiz, SpainNuclear Engineering and Fluid Mechanics Department, University of the Basque Country UPV/EHU, 01006 Vitoria-Gasteiz, Araba, SpainOrthotic devices are defined as externally applied devices that are used to modify the structural and functional characteristics of the neuro-muscular and skeletal systems. The aim of the current study is to improve the control and movement of a robotic arm orthosis by means of an intelligent optimization system. Firstly, the control problem settlement is defined with the muscle, brain, and arm model. Subsequently, the optimization control, which based on a differential evolution algorithm, is developed to calculate the optimum gain values. Additionally, a cost function is defined in order to control and minimize the effort that is made by the subject and to assure that the algorithm follows as close as possible the defined setpoint value. The results show that, with the optimization algorithm, the necessary development force of the muscles is close to zero and the neural excitation level of biceps and triceps signal values are getting lower with a gain increase. Furthermore, the necessary development force of the biceps muscle to overcome a load added to the orthosis control system is practically the half of the one that is necessary without the optimization algorithm.https://www.mdpi.com/2076-3417/9/12/2453orthosis controlmuscle modelingarmHill muscleswarm optimization |
| spellingShingle | Iñigo Aramendia Ekaitz Zulueta Daniel Teso-Fz-Betoño Aitor Saenz-Aguirre Unai Fernandez-Gamiz Modeling of Motorized Orthosis Control Applied Sciences orthosis control muscle modeling arm Hill muscle swarm optimization |
| title | Modeling of Motorized Orthosis Control |
| title_full | Modeling of Motorized Orthosis Control |
| title_fullStr | Modeling of Motorized Orthosis Control |
| title_full_unstemmed | Modeling of Motorized Orthosis Control |
| title_short | Modeling of Motorized Orthosis Control |
| title_sort | modeling of motorized orthosis control |
| topic | orthosis control muscle modeling arm Hill muscle swarm optimization |
| url | https://www.mdpi.com/2076-3417/9/12/2453 |
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