Our vision at the Institute for Modelling and Simulation of Biomechanical Systems (IMSB) is to use computational and experimental methods to enhance our knowledge about biomechanical systems with a particular focus on the Human System. For more information please also visit our institute's website.
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621 to 630 of 809 Results
simulate_motor_unit_response_library.m
Jul 14, 2023 - Replication Data for: "High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study"
MATLAB Source Code - 7.7 KB - MD5: 2acbb8a9811ebacc2169b0d653b577c6
Input file to simulate the motor unit response libraries with the multi-domain simulation framework. Executing this script requires to download a freely available software package: https://bitbucket.org/klotz_t/multi_domain_fd_code/
spiketrains_high_mvc.mat
Jul 14, 2023 - Replication Data for: "High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study"
MATLAB Data - 174.4 KB - MD5: 840f717e3ae15bd67577eb3124db03f0
Binary spike train that is used as input for generating interference signals (Dim 1: Motor unit index, Dim 2: Time Sample).
spiketrains_low_mvc.mat
Jul 14, 2023 - Replication Data for: "High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study"
MATLAB Data - 59.2 KB - MD5: e505c7a453471ecd3bafe1fd38e25293
Binary spike train that is used as input for generating interference signals (Dim 1: Motor unit index, Dim 2: Time Sample).
spiketrains_medium_mvc.mat
Jul 14, 2023 - Replication Data for: "High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study"
MATLAB Data - 107.2 KB - MD5: eb865075da56043cae599f0db757d372
Binary spike train that is used as input for generating interference signals (Dim 1: Motor unit index, Dim 2: Time Sample).
User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
Sep 28, 2022
Saini, Harnoor, 2022, "User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"", https://doi.org/10.18419/DARUS-2229, DaRUS, V1
Background and Objective: Many biomedical, clinical, and industrial applications may benefit from musculoskeletal simulations. Three-dimensional macroscopic muscle models (3D models) can more accurately represent muscle architecture than their 1D (line-segment) counterparts. Nevertheless, 3D models remain underutilised in academic, clinical, and co...
P1-TK_A1-GD.csv
Sep 28, 2022 - User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
Comma Separated Values - 385 B - MD5: 8eb29484b74f4cc8b416e6dd985f5f0b
Material parameter set
P1_TK-A2-HB.csv
Sep 28, 2022 - User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
Comma Separated Values - 385 B - MD5: 0bd6d84ac6120c5cecede4c438c680ca
Material parameter set
P2_MK-A1-GD.csv
Sep 28, 2022 - User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
Comma Separated Values - 385 B - MD5: 0d1e0db0339661887aafcd75c6d8e531
Material parameter set
P3_HB-A2-HB.csv
Sep 28, 2022 - User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
Comma Separated Values - 384 B - MD5: 3a50c5475825fe30146b84d607522962
Material parameter set
readme.pdf
readme.pdf
Sep 28, 2022 - User-material for: "A biophysically guided constitutive law of the musculotendon-complex: modelling and numerical implementation in Abaqus"
Adobe PDF - 71.7 KB - MD5: ca0d4745ac65059f1f05aaead87dca6e
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