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621 to 630 of 815 Results
MATLAB Data - 123.5 MB - MD5: 18612421180ad8f261e8547d71adfa07
Simulated high-density EMG and high-density MMG singal for a 30 second long voluntary isometric contraction.
MATLAB Data - 69.2 KB - MD5: aa1abe3cfb63ec2b94279428ad2759e0
Motor unit territories for the simulated motor unit pools (Dim 1: y-coordinate, Dim 2: z-coordinate, Dim 3: Motor unit index).
MATLAB Data - 1.2 MB - MD5: 59fcec0ebf340e6ca397ae3ad9e9fad0
Simulated motor unit electric potentials (MUEPs) and motor unit magnetic fields (MUMFs) measured from a virtual high-density EMG or MMG array (70 sampling points). Specifically, this data shocases the influecne of the MU depth. All MU territories are identical, however, shifted in depth.
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/
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).
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).
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).
Jun 29, 2023
This dataverse hosts all data aquired within the resreach project "qMOTION - Simulation-enhanced Highdensity Magneto-myographic Quantum Sensor Systems for Decoding Neuromuscular Control During Motion" funded by the European Reserach Council through ERC-AdG 2021 #101055186. Abstract: Being able to decode neural signals that control skeletal muscles...
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...
Comma Separated Values - 385 B - MD5: 8eb29484b74f4cc8b416e6dd985f5f0b
Material parameter set
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