The BioMotionBot: a robotic device for applications in human motor learning and rehabilitation.
Identifieur interne : 002412 ( Ncbi/Curation ); précédent : 002411; suivant : 002413The BioMotionBot: a robotic device for applications in human motor learning and rehabilitation.
Auteurs : V. Bartenbach [Allemagne] ; C. Sander ; M. Pöschl ; K. Wilging ; T. Nelius ; F. Doll ; W. Burger ; C. Stockinger ; A. Focke ; T. SteinSource :
- Journal of neuroscience methods [ 1872-678X ] ; 2013.
English descriptors
- KwdEn :
- MESH :
- instrumentation : Rehabilitation, Robotics.
- methods : Rehabilitation, Robotics.
- physiology : Motor Skills.
- Biomechanical Phenomena, Humans, Software.
Abstract
Robotic manipulanda are an established tool for the investigation of human motor control and learning. Potentially, robotic manipulanda could also be valuable in the investigation of skill learning in more natural movement tasks. Most current designs have been developed for studying dynamic learning and rehabilitation and are restricted to 2D space. However, natural upper limb movements take place in 3D space, sometimes with high underlying forces. In this paper, we introduce a robotic device, the BioMotionBot, that can be used in established applications of dynamic learning and rehabilitation but also enables the investigation of skill learning in more natural 3D movement tasks with large dynamic perturbations. The design of the BioMotionBot is based on a mechanism with hybrid serial and parallel kinematics. We first describe the BioMotionBot's mechanical design, the electronic components, the software structure and the control system. To investigate the performance of the BioMotionBot, its stiffness, endpoint mass, endpoint viscosity, haptic resolution, force depth and impedance ratio are evaluated. Additionally, we develop a detailed multi-body simulation model to validate aspects of the structure and behavior of the BioMotionBot. Finally, we present experimental data from a dynamic learning task in 2D and test a 3D scenario with virtual walls. Our results demonstrate that the BioMotionBot can be used for research in human motor learning and rehabilitation and also has potential for the investigation of skill learning in more natural 3D movement tasks.
DOI: 10.1016/j.jneumeth.2012.12.006
PubMed: 23276545
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<front><div type="abstract" xml:lang="en">Robotic manipulanda are an established tool for the investigation of human motor control and learning. Potentially, robotic manipulanda could also be valuable in the investigation of skill learning in more natural movement tasks. Most current designs have been developed for studying dynamic learning and rehabilitation and are restricted to 2D space. However, natural upper limb movements take place in 3D space, sometimes with high underlying forces. In this paper, we introduce a robotic device, the BioMotionBot, that can be used in established applications of dynamic learning and rehabilitation but also enables the investigation of skill learning in more natural 3D movement tasks with large dynamic perturbations. The design of the BioMotionBot is based on a mechanism with hybrid serial and parallel kinematics. We first describe the BioMotionBot's mechanical design, the electronic components, the software structure and the control system. To investigate the performance of the BioMotionBot, its stiffness, endpoint mass, endpoint viscosity, haptic resolution, force depth and impedance ratio are evaluated. Additionally, we develop a detailed multi-body simulation model to validate aspects of the structure and behavior of the BioMotionBot. Finally, we present experimental data from a dynamic learning task in 2D and test a 3D scenario with virtual walls. Our results demonstrate that the BioMotionBot can be used for research in human motor learning and rehabilitation and also has potential for the investigation of skill learning in more natural 3D movement tasks.</div>
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