demoa

A biophysics simulator for muscle-driven motion

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

1 to 10 of 17 Results

allmin: A Reduced Human All-Body Model Jun 3, 2025 Walter, Johannes R.; Wochner, Isabell; Jacob, Marc; Stollenmaier, Katrin; Lerge, Patrick; Schmitt, Syn, 2022, "allmin: A Reduced Human All-Body Model", https://doi.org/10.18419/DARUS-2982, DaRUS, V3 A reduced all-body model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. This allmin model consists of a musculoskeletal model of the human body with 20 degrees of freedom actuated by 36 muscles. The model is prepared to run muscle-driven simulation. The file contain...
allmin-3.0.tgz Jun 3, 2025 - allmin: A Reduced Human All-Body Model TAR Archive - 71.1 KB - MD5: 6e0d484243db14d4bed0db1b5fd93d21
LICENSE Jun 3, 2025 - allmin: A Reduced Human All-Body Model Plain Text - 1.5 KB - MD5: 1cd608add5724e6f8e1cc9bb99cee225
README.md Jun 3, 2025 - allmin: A Reduced Human All-Body Model Markdown Text - 1.9 KB - MD5: a28d7b07e57e74c877b5d53513a07a7d
demoa-base: a biophysics simulator for muscle-driven motion May 28, 2025 Schmitt, Syn, 2022, "demoa-base: a biophysics simulator for muscle-driven motion", https://doi.org/10.18419/DARUS-2550, DaRUS, V6 For more information, such as installation, requirements and user guide, please see the demoa manual. The development of this package was supported by “Deutsche Forschungsgemeinschaft” (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2075 - 390740016.
demoa-base-3.1.tgz May 28, 2025 - demoa-base: a biophysics simulator for muscle-driven motion TAR Archive - 40.0 MB - MD5: e0b90618a77743b8024cec5580e7c49a Version 3.1
gspine: A Human Spine Model Built Using Literature Data Jan 13, 2025 Hammer, Maria; Riede, Julia Maria; Meszaros-Beller, Laura; Schmitt, Syn, 2022, "gspine: A Human Spine Model Built Using Literature Data", https://doi.org/10.18419/DARUS-2814, DaRUS, V4 A fully articulating human spine model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. The model is prepared to run muscle-driven simulations using a simple biological motor control model. The file contains an archive including all relevant data to run the simulation...
gspine1.2.tar Jan 13, 2025 - gspine: A Human Spine Model Built Using Literature Data TAR Archive - 3.9 MB - MD5: 7b4591d5a4478bca19270bce74f1341a Generic spine Model v1.2 compatible with demoa v3.0
demoa-manual-v3.pdf Jan 8, 2025 - demoa-base: a biophysics simulator for muscle-driven motion Adobe PDF - 855.5 KB - MD5: 46608738d337606086689492d4f07062 demoa version 3.0 manual
MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks Dec 16, 2022 Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/DARUS-3268, DaRUS, V1 This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt and Daniel F.B. Haeufle. Always cite the paper together with this datase...

allmin: A Reduced Human All-Body Model

Jun 3, 2025

Walter, Johannes R.; Wochner, Isabell; Jacob, Marc; Stollenmaier, Katrin; Lerge, Patrick; Schmitt, Syn, 2022, "allmin: A Reduced Human All-Body Model", https://doi.org/10.18419/DARUS-2982, DaRUS, V3

A reduced all-body model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. This allmin model consists of a musculoskeletal model of the human body with 20 degrees of freedom actuated by 36 muscles. The model is prepared to run muscle-driven simulation. The file contain...

allmin-3.0.tgz

Jun 3, 2025 - allmin: A Reduced Human All-Body Model

TAR Archive - 71.1 KB -

LICENSE

Jun 3, 2025 - allmin: A Reduced Human All-Body Model

Plain Text - 1.5 KB -

README.md

Jun 3, 2025 - allmin: A Reduced Human All-Body Model

Markdown Text - 1.9 KB -

demoa-base: a biophysics simulator for muscle-driven motion

May 28, 2025

Schmitt, Syn, 2022, "demoa-base: a biophysics simulator for muscle-driven motion", https://doi.org/10.18419/DARUS-2550, DaRUS, V6

For more information, such as installation, requirements and user guide, please see the demoa manual. The development of this package was supported by “Deutsche Forschungsgemeinschaft” (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2075 - 390740016.

demoa-base-3.1.tgz

May 28, 2025 - demoa-base: a biophysics simulator for muscle-driven motion

TAR Archive - 40.0 MB -

Version 3.1

gspine: A Human Spine Model Built Using Literature Data

Jan 13, 2025

Hammer, Maria; Riede, Julia Maria; Meszaros-Beller, Laura; Schmitt, Syn, 2022, "gspine: A Human Spine Model Built Using Literature Data", https://doi.org/10.18419/DARUS-2814, DaRUS, V4

A fully articulating human spine model parametrised using generic literature data for the geometry of the skeleton including attachment points for ligaments and muscles. The model is prepared to run muscle-driven simulations using a simple biological motor control model. The file contains an archive including all relevant data to run the simulation...

gspine1.2.tar

Jan 13, 2025 - gspine: A Human Spine Model Built Using Literature Data

TAR Archive - 3.9 MB -

Generic spine Model v1.2 compatible with demoa v3.0

demoa-manual-v3.pdf

Jan 8, 2025 - demoa-base: a biophysics simulator for muscle-driven motion

Adobe PDF - 855.5 KB -

demoa version 3.0 manual

MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks

Dec 16, 2022

Wochner, Isabell; Schmitt, Syn, 2022, "MPC/OC Code for: Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks", https://doi.org/10.18419/DARUS-3268, DaRUS, V1

This code allows you reproduce the optimal control and model predictive control results of the paper: "Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks" by Isabell Wochner, Pierre Schumacher, Georg Martius, Dieter Büchler, Syn Schmitt and Daniel F.B. Haeufle. Always cite the paper together with this datase...

Add Data

Share Dataverse

Link Dataverse

Reset Modifications