opensim-based musculoskeletal model Search Results


90
OpenSim Ltd musculoskeletal model incorporating the static optimization method based on muscle parameter calibration (so)
Musculoskeletal Model Incorporating The Static Optimization Method Based On Muscle Parameter Calibration (So), 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/musculoskeletal model incorporating the static optimization method based on muscle parameter calibration (so)/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
musculoskeletal model incorporating the static optimization method based on muscle parameter calibration (so) - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

90
OpenSim Ltd 3d lower-extremity physics-based human musculoskeletal model
The proposed DRL method for the dynamic optimization of the forward dynamics of a human <t>musculoskeletal</t> model during stairs or ramp ascent.
3d Lower Extremity Physics Based Human 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/3d lower-extremity physics-based human musculoskeletal model/product/OpenSim Ltd
Average 90 stars, based on 1 article reviews
3d lower-extremity physics-based human musculoskeletal model - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

Image Search Results


The proposed DRL method for the dynamic optimization of the forward dynamics of a human musculoskeletal model during stairs or ramp ascent.

Journal: Sensors (Basel, Switzerland)

Article Title: Learning to Ascend Stairs and Ramps: Deep Reinforcement Learning for a Physics-Based Human Musculoskeletal Model

doi: 10.3390/s22218479

Figure Lengend Snippet: The proposed DRL method for the dynamic optimization of the forward dynamics of a human musculoskeletal model during stairs or ramp ascent.

Article Snippet: The 3D lower-extremity physics-based human musculoskeletal model used in this study was developed in OpenSim 3.3 (model version number 3000) as an .osim file.

Techniques:

The physics-based human musculoskeletal model developed in this study. Figures from left to right: side view facing the right leg, front view, side view facing the left leg, and back view.

Journal: Sensors (Basel, Switzerland)

Article Title: Learning to Ascend Stairs and Ramps: Deep Reinforcement Learning for a Physics-Based Human Musculoskeletal Model

doi: 10.3390/s22218479

Figure Lengend Snippet: The physics-based human musculoskeletal model developed in this study. Figures from left to right: side view facing the right leg, front view, side view facing the left leg, and back view.

Article Snippet: The 3D lower-extremity physics-based human musculoskeletal model used in this study was developed in OpenSim 3.3 (model version number 3000) as an .osim file.

Techniques:

The state variables of the human  musculoskeletal model.

Journal: Sensors (Basel, Switzerland)

Article Title: Learning to Ascend Stairs and Ramps: Deep Reinforcement Learning for a Physics-Based Human Musculoskeletal Model

doi: 10.3390/s22218479

Figure Lengend Snippet: The state variables of the human musculoskeletal model.

Article Snippet: The 3D lower-extremity physics-based human musculoskeletal model used in this study was developed in OpenSim 3.3 (model version number 3000) as an .osim file.

Techniques: Plasmid Preparation

The reward obtained during the learning process of the human musculoskeletal model to ascend the stairs.

Journal: Sensors (Basel, Switzerland)

Article Title: Learning to Ascend Stairs and Ramps: Deep Reinforcement Learning for a Physics-Based Human Musculoskeletal Model

doi: 10.3390/s22218479

Figure Lengend Snippet: The reward obtained during the learning process of the human musculoskeletal model to ascend the stairs.

Article Snippet: The 3D lower-extremity physics-based human musculoskeletal model used in this study was developed in OpenSim 3.3 (model version number 3000) as an .osim file.

Techniques:

The reward obtained during the learning process of the human musculoskeletal model to ascend the ramp.

Journal: Sensors (Basel, Switzerland)

Article Title: Learning to Ascend Stairs and Ramps: Deep Reinforcement Learning for a Physics-Based Human Musculoskeletal Model

doi: 10.3390/s22218479

Figure Lengend Snippet: The reward obtained during the learning process of the human musculoskeletal model to ascend the ramp.

Article Snippet: The 3D lower-extremity physics-based human musculoskeletal model used in this study was developed in OpenSim 3.3 (model version number 3000) as an .osim file.

Techniques: