modenaxe / awesome-biomechanics Goto Github PK

paper: https://mdpi.com/1424-8220/22/9/3259
code: https://github.com/GiacomoDR25
by @GiacomoDR25

Link to Awesome-List guidelines: https://github.com/sindresorhus/awesome/blob/main/create-list.md

https://www.hexalab.net/
https://www.meshlabjs.net/

description: extension for Slicer that is designed to serially calculate the second moment of area and other cross-sectional properties along the length of 3D structures.
paper: https://doi.org/10.1093/iob/obac009
code: https://github.com/jmhuie/Slicer-SegmentGeometry
by @jmhuie

code: https://github.com/cjhasson/simulink-virtual-arm
paper: https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-022-05994-5

paper: Lower-limb kinematics and kinetics during continuously varying human locomotion
description: new dataset that includes the lower-limb kinematics and kinetics of ten able-bodied participants walking at multiple inclines (±0°; 5° and 10°) and speeds (0.8 m/s; 1 m/s; 1.2 m/s), running at multiple speeds (1.8 m/s; 2 m/s; 2.2 m/s and 2.4 m/s), walking and running with constant acceleration (±0.2; 0.5), and stair ascent/descent with multiple stair inclines (20°; 25°; 30° and 35°).
dataset: https://springernature.figshare.com/collections/Lower-limb_Kinematics_and_Kinetics_During_Continuously_Varying_Human_Locomotion/5175254

Description: The Gutenberg Gait Database comprises data of 350 healthy individuals. The database contains ground reaction force (GRF) and center of pressure (COP) data of two consecutive steps measured - by two force plates embedded in the ground - during level overground walking at self-selected walking speed.

Paper: Horst, F., Slijepcevic, D., Simak, M. & Schöllhorn, W. I. Gutenberg Gait Database, a ground reaction force database of level overground walking in healthy individuals. Sci Data 8, 232 (2021). https://doi.org/10.1038/s41597-021-01014-6

Dataset: Horst, F., Slijepcevic, D., Simak, M. & Schöllhorn, W. I. Gutenberg Gait Database: A ground reaction force database of level overground walking in healthy individuals. figshare https://doi.org/10.6084/m9.figshare.c.5311538 (2021).

TimTrack: an automated algorithm for estimating geometric features from ultrasound images by @timvanderzee
paper: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265752
code: https://github.com/timvanderzee/ultrasound-automated-algorithm
dataset: https://zenodo.org/record/2598553#.YkKvoyhBxZU

an archive of many main stream mocap datasets under smpl body model formulation.
supports biomech and rendering tools.
project page: https://amass.is.tue.mpg.de/

https://cims.uci.edu/education-training/iomm/novel-muscle-models

There's a good list of emojiis here: https://gist.github.com/rxaviers/7360908

project: https://simtk.org/projects/biartprosthesis
paper: https://doi.org/10.1080/10255842.2022.2065630

paper: https://arxiv.org/pdf/1607.03827.pdf
dataset: https://motion-database.humanoids.kit.edu/list/motions/

paper: https://www.nature.com/articles/s41597-022-01483-3
data: https://figshare.com/articles/dataset/Dataset_of_gait_analysis_data_of_hip_osteoarthritis_patients_before_and_6_month_after_arthroplasty_and_asymptomatic_volunteers_Dataset_of_gait_analysis_data_of_hip_osteoarthritis_patients_before_and_6_month_after_arthroplasty_and_asymptomat/14420645

data2: https://figshare.com/articles/dataset/Dataset_of_gait_analysis_data_of_hip_osteoarthritis_patients_before_and_6_month_after_arthroplasty_and_asymptomatic_volunteers_Dataset_of_gait_analysis_data_of_hip_osteoarthritis_patients_before_and_6_month_after_arthroplasty_and_asymptomat/14420756

description: AMIDE is a competely free tool for viewing, analyzing, and registering volumetric medical imaging data sets. It's been written on top of GTK+, and runs on any system that supports this toolkit (Linux, Windows, Mac OS X, etc.).
website: http://amide.sourceforge.net/
software: https://sourceforge.net/projects/amide/
source: https://sourceforge.net/p/amide/code/ci/default/tree/

I suggest to add the following open source software for analysing diffusion tensor imaging data to the section "DTI and tractography::

• MRtrix: https://www.mrtrix.org/
• Tutorial: https://osf.io/fkyht/

Project: https://t.co/i0uavzx6Yo
Code: https://t.co/BS8bA7iw6Q
Paper: https://t.co/rGaDOsUk40
Data: see project page
Video: https://t.co/Z94mfJfzKn

http://www.pymunk.org/

website: https://darus.uni-stuttgart.de/dataverse/demoa

I found this one: https://ecotrust-canada.github.io/markdown-toc but it does not handle well spaces and colons in emoji :name:.

dataset: https://zenodo.org/record/5801928#.YhYu0ehBz4c
paper: https://arxiv.org/pdf/2202.06164.pdf
code: https://github.com/ManuelPalermo/HumanInertialPose
by @ManuelPalermo

Hi!
the link of "learning"-"Lectures on optimal control by Anil Rao (University of Florida)" is not working

http://www.anilvrao.com/Optimal-Control-Videos.html
https://github.com/modenaxe/awesome-biomechanics

Bye!
GianEng

website: https://simtk.org/projects/jmp
paper: Reinbolt 2005 (?)

add: https://github.com/alesantuz/musclesyneRgies by @alesantuz

https://anaconda.org/opensim-org/opensim

description: a collection of simple PyTorch implementations of neural networks and related algorithms
link: https://nn.labml.ai/

link: https://www.sim.informatik.tu-darmstadt.de/res/ds/humod

You Tube videos of lectures from an introductory survey undergraduate biomechanics course. https://www.youtube.com/user/yinglingv

author: Nicolas P. Rougier
title: Scientific Visualization: Python + Matplotlib
link: https://www.labri.fr/perso/nrougier/scientific-visualization.html

a mocap auto-solving deep learning based framework to turn raw mocap point clouds into SMPL-X bodies
project page: https://soma.is.tue.mpg.de/
code: https://github.com/nghorbani/soma

See procedure

• step1:

git branch -m master main
git push origin main

• step2: delete master branch (might require changing default branch)

git push origin --delete master

I would like to suggest adding ASLI, an open source tool for generating lattice infills.

• ASLI (A Simple Lattice Infiller) is a cross-platform command line open-source tool that gives users the ability to provide functionally graded lattice infills to 3D geometries.
  📄 paper | 💻 website | 💾 source

* [**ASLI (A Simple Lattice Infiller)**](http://www.biomech.ulg.ac.be/ASLI/) is a cross-platform command line open-source tool that gives users the ability to provide functionally graded lattice infills to 3D geometries.</br>
:page_facing_up: [paper](https://doi.org/10.1080/17452759.2022.2048956) | 
:computer: [website](http://www.biomech.ulg.ac.be/ASLI/) | 
:floppy_disk: [source](https://github.com/tpms-lattice/ASLI)

Description: an interactive computer program for decomposing EMG signals into their component motor-unit potential (MUP) trains and for averaging MUP waveforms. The program is able to handle single- or multi-channel signals recorded by needle or fine-wire electrodes during low and moderate levels of muscular contraction.
code: http://www.emglab.net/emglab/Software/Software.php
paper: https://doi.org/10.1016/j.jneumeth.2005.05.015

adrianrivadulla/FootNet
Motion capture running analyses are often performed on conventional (non-instrumented) treadmills. The absence of force plates can be problematic for the detection of foot strike and toe off, which are critical for the comprehensive biomechanical analysis of running kinematics. We introduce FootNet an algorithm for the detection of foot strike and toe off events on non-instrumented treadmills using segment and joint kinematics as input. The algorithm is based on an LSTM neural network architecture that has been trained, validated and tested using five datasets collected in three independent motion capture labs.

paper: https://www.frontiersin.org/articles/10.3389/fbioe.2021.745837/full
dataset: https://osf.io/a27py/
description: This database contains the vertebral angles that formed the basis of the dynamic spinal rhythms published in Breen et al. (2021)

A stair descent dataset from 101 unimpaired participants aged 18-35 on an unconstrained 13-step staircase collected using wearable sensors. The dataset consists of kinematics (full-body joint angle and position), kinetics (plantar normal forces, acceleration), and foot placement for 30,609 steps. This is the first quantitative observation of gait data from a large number (n = 101) of participants descending an unconstrained staircase outside of a laboratory. The dataset is a public resource for understanding typical stair descent.
paper: https://doi.org/10.1016/j.gaitpost.2021.10.039
dataset: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/SFZPOK

This needs to be done after I cleaned the sandbox.
Seee this action.

paper: Muscle coordination retraining inspired by musculoskeletal simulations reduces knee contact force
https://github.com/stanfordnmbl/MatlabStaticOptimization
https://github.com/stanfordnmbl/PassiveMuscleForceCalibration
https://simtk.org/projects/fbmodpassivecal
https://simtk.org/projects/coordretraining

• pose estimation
• LSTM/temporal signals
• ?inference?
• data augmentation
• marker labelling
• other (OSSO etc)

https://project-awesome.org/nschloe/awesome-scientific-computing

title: PolyCube Based Automatic Hex-Mesh Generation (UBC)
link: https://www.cs.ubc.ca/~sheffa/hexing/hexing.htm

weblink: https://www.dealii.org/

inferring the anatomic skeleton of a person from the body surface
project page: https://osso.is.tue.mpg.de/

paper: https://joss.theoj.org/papers/10.21105/joss.04279
repository: https://github.com/SolavLab/DuoDIC
by @danasolav

repository: https://gitlab.inria.fr/perfanalytics/pose2sim

Add "Tracking Weight Selection Algorithm (TWSA) Optimization for the OpenSim Residual Reduction Algorithm" by @RealSturdy

paper: https://doi.org/10.1101/2021.10.06.463431
code: https://github.com/FxnlBiomechLab/twsa-optimization-for-rra