upper extremity model (opensim model) Search Results


90
OpenSim Ltd upper limb model opensim version
Upper Limb Model Opensim Version, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/upper limb model opensim version/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
upper limb model opensim version - by Bioz Stars, 2026-05
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90
OpenSim Ltd upper extremity dynamic model
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Upper Extremity Dynamic Model, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/upper extremity dynamic model/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
upper extremity dynamic model - by Bioz Stars, 2026-05
90/100 stars
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90
OpenSim Ltd model of the macaque upper extremity
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Model Of The Macaque Upper Extremity, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/model of the macaque upper extremity/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
model of the macaque upper extremity - by Bioz Stars, 2026-05
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90
OpenSim Ltd upper extremity anatomical model 8
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Upper Extremity Anatomical Model 8, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/upper extremity anatomical model 8/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
upper extremity anatomical model 8 - by Bioz Stars, 2026-05
90/100 stars
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90
OpenSim Ltd mobl upper extremity dynamic model
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Mobl Upper Extremity Dynamic Model, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/mobl upper extremity dynamic model/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
mobl upper extremity dynamic model - by Bioz Stars, 2026-05
90/100 stars
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90
OpenSim Ltd customized unimanual upper extremity musculoskeletal model
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Customized Unimanual Upper Extremity Musculoskeletal Model, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/customized unimanual upper extremity musculoskeletal model/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
customized unimanual upper extremity musculoskeletal model - by Bioz Stars, 2026-05
90/100 stars
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90
OpenSim Ltd mobl arms dynamic musculoskeletal model of the upper extremity
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Mobl Arms Dynamic Musculoskeletal Model Of The Upper Extremity, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/mobl arms dynamic musculoskeletal model of the upper extremity/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
mobl arms dynamic musculoskeletal model of the upper extremity - by Bioz Stars, 2026-05
90/100 stars
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90
OpenSim Ltd modified upper-extremity wheelchair propulsion model
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Modified Upper Extremity Wheelchair Propulsion Model, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/modified upper-extremity wheelchair propulsion model/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
modified upper-extremity wheelchair propulsion model - by Bioz Stars, 2026-05
90/100 stars
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90
OpenSim Ltd upper extremity trunk model
Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical <t>upper</t> <t>extremity</t> <t>model</t> from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.
Upper Extremity Trunk Model, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/upper extremity trunk model/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
upper extremity trunk model - by Bioz Stars, 2026-05
90/100 stars
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Image Search Results


Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical upper extremity model from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.

Journal: Scientific Reports

Article Title: Reinforcement learning control of a biomechanical model of the upper extremity

doi: 10.1038/s41598-021-93760-1

Figure Lengend Snippet: Synthesized reaching movement. A policy implemented as a neural network computes motor control signals of simplified muscles at the joints of a biomechanical upper extremity model from observations of the current state of the upper body. We use Deep Reinforcement Learning to learn a policy that reaches random targets in minimal time, given signal-dependent and constant motor noise.

Article Snippet: Using OpenSim, we scaled the Upper Extremity Dynamic Model to this particular person.

Techniques: Synthesized, Control, Muscles