54 research outputs found
Kevin-Mattheus-Moerman/NonlinearContinuumMechanics:
No full textSelected notebooks on non-linear continuum mechanic
GIBBON (Hylobates Lar)
No full text<p>The Geometry and Image-Based Bioengineering add-On for MATLAB http://www.gibboncode.org/</p>
SuperKogito/spafe: v0.3.0
No full textWhat's new?
Added type hinting.
Improved windowing by using window object.
Improved converters script.
Improved code and fixed documentation.
Documentation available at https://superkogito.github.io/spafe/v0.3.0/index.html
New contributors:
hadware https://github.com/hadware
Hervé BREDIN https://github.com/hbredin
Kevin Mattheus Moerman https://github.com/Kevin-Mattheus-Moerma
Course: GIBBON (The Geometry and Image-Based Bioengineering add-On)
No full textThe slides for the GIBBON lecture presented at the IEEE Boston chapter course on "Open Source Tools for Computational Biomechanics". http://ieeeboston.org/open-source-tools-computational-biomechanics/.
www.gibboncode.or
GIBBON: The Geometry and Image-Based Bioengineering add-On (Release: Hylobates albibarbis)
No full text<p>The Geometry and Image-Based Bioengineering add-On for MATLAB</p>
Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo
No full textThe mechanical properties of human soft tissue are crucial for impact
biomechanics, rehabilitation engineering and surgical simulation.
Validation of these constitutive models using human data remains
challenging and often requires the use of non-invasive imaging and inverse
finite element (FE) analysis. Post processing data from imaging methods
such as tagged magnetic resonance imaging (MRI) can be challenging. Digital
Image Correlation (DIC) however is a relatively straightforward imaging
method and thus the goal of this study was to assess the use of DIC in
combination with FE modelling to determine the bulk material properties of
human soft tissue. Indentation experiments were performed on a silicone gel
soft tissue phantom. A two camera DIC setup was then used to record the 3D
surface deformation. The experiment was then simulated using a FE model
An improved framework for the inverse analysis of skeletal muscle tissue in-vivo
No full textTHESIS 9682This thesis focusses on the development of an experimental and computational framework for the non-invasive analysis of the passive mechanical properties of living human skeletal muscle tissue. This is relevant to many areas of research including impact biomechanics and rehabilitation engineering. Although constitutive models have been proposed for muscle tissue these have been insufficiently validated for human tissue which requires non-invasive methods. Non-invasive analysis of the mechanical properties of soft tissue requires non-invasive mechanical exciting and inverse analysis of non-invasively measured experimental boundary conditions such as tissue deformation and applied load. Magnetic Resonance Imaging (MRI) provides excellent soft tissue contrast without ionizing radiation. In addition it allows for the measurement of soft tissue anatomy, architecture and deformation boundary conditions. Hence for mechanical excitation a novel MRI compatible and computer controllable soft tissue indentation device was developed and implemented with an accurate high acquisition rate (100Hz) optical force sensor capable of viscoelastic force registration. In order to measure the resultant deformation SPAtial Modulation of the Magnetisation (SPAMM) tagged MRI was used. Traditional SPAMM tagging methods require large numbers of repetitions of motion cycles causing repeatability difficulties and volunteer discomfort. However for this thesis a unique set of high speed SPAMM tagged MRI techniques, and fully automatic post-processing methods based on Gabor wavelet filtering, were developed allowing for the measurement of complex dynamic 3D deformation following the combination of just 3 motion cycles. The SPAMM tagged MRI techniques were validated using marker tracking in a silicone gel phantom and underwent in-vivo evaluation whereby sub-voxel accuracy and precision levels were reported. Constitutive models for passive skeletal muscle tissue were evaluated using inverse Finite Element (FE) Analysis (FEA) based fitting to experimental data from the literature. It was shown that current models do not allow appropriate modelling of anisotropy. A new constitutive law was proposed which formed a close match to the data and was based on Gaussian weighting of transverse and longitudinal direction contributions of a spherical fibre distribution model. This thesis focusses on the development of an experimental and computational framework for the non-invasive analysis of the passive mechanical properties of living human skeletal muscle tissue. This is relevant to many areas of research including impact biomechanics and rehabilitation engineering. Although constitutive models have been proposed for muscle tissue these have been insufficiently validated for human tissue which requires non-invasive methods. Non-invasive analysis of the mechanical properties of soft tissue requires non-invasive mechanical exciting and inverse analysis of non-invasively measured experimental boundary conditions such as tissue deformation and applied load. Magnetic Resonance Imaging (MRI) provides excellent soft tissue contrast without ionizing radiation. In addition it allows for the measurement of soft tissue anatomy, architecture and deformation boundary conditions. Hence for mechanical excitation a novel MRI compatible and computer controllable soft tissue indentation device was developed and implemented with an accurate high acquisition rate (100Hz) optical force sensor capable of viscoelastic force registration. In order to measure the resultant deformation SPAtial Modulation of the Magnetisation (SPAMM) tagged MRI was used. Traditional SPAMM tagging methods require large numbers of repetitions of motion cycles causing repeatability difficulties and volunteer discomfort. However for this thesis a unique set of high speed SPAMM tagged MRI techniques, and fully automatic post-processing methods based on Gabor wavelet filtering, were developed allowing for the measurement of complex dynamic 3D deformation following the combination of just 3 motion cycles. The SPAMM tagged MRI techniques were validated using marker tracking in a silicone gel phantom and underwent in-vivo evaluation whereby sub-voxel accuracy and precision levels were reported. Constitutive models for passive skeletal muscle tissue were evaluated using inverse Finite Element (FE) Analysis (FEA) based fitting to experimental data from the literature. It was shown that current models do not allow appropriate modelling of anisotropy. A new constitutive law was proposed which formed a close match to the data and was based on Gaussian weighting of transverse and longitudinal direction contributions of a spherical fibre distribution model
gibbonCode/GIBBON: GIBBON: The Geometry and Image-Based Bioengineering add-On (Release: Hylobates Klossii)
No full text<p>The main new features of this release (v3.5.0, Hylobates Klossii) are: new FEBio demos for the new febio_spec format, support for coding and running ABAQUS models from GIBBON, updated help and documentation.</p>
Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo
No full textThe mechanical properties of human soft tissue are crucial for impact
biomechanics, rehabilitation engineering and surgical simulation.
Validation of these constitutive models using human data remains
challenging and often requires the use of non-invasive imaging and inverse
finite element (FE) analysis. Post processing data from imaging methods
such as tagged magnetic resonance imaging (MRI) can be challenging. Digital
Image Correlation (DIC) however is a relatively straightforward imaging
method and thus the goal of this study was to assess the use of DIC in
combination with FE modelling to determine the bulk material properties of
human soft tissue. Indentation experiments were performed on a silicone gel
soft tissue phantom. A two camera DIC setup was then used to record the 3D
surface deformation. The experiment was then simulated using a FE model
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