Dr Luca Modenese has wide interests in the field of computational biomechanics, ranging from developing methods to generate computational models of the musculoskeletal anatomy to using advanced dynamic analyses to understand the principles underlying human motion and motor control. These research topics of computational nature are always strictly connected to clinical applications, thanks to the collaboration with clinical figures such as gait analysis laboratories and surgeons.

Education and background
Luca Modenese was awarded a degree (summa cum laude) in Mechanical Engineering from the University of Padua in 2008 (Department of Industrial Engineering). After a brief period as Research Assistant, Luca started his doctoral training at Imperial College London, based in the Structural Biomechanics group. Luca received his PhD in 2013 and moved to Griffith University for a postdoc in the Centre for Musculoskeletal Research (now part of Menzie Health Institute Queensland), under the supervision of Prof. David Lloyd. During this period, he was awarded a visiting scholar fellowship to visit the Neuromuscular Biomechanics Lab at Stanford University. He also spent time as visiting researcher at the Auckland Bioengineering Institute and University of Padua. In 2015, Dr Modenese moved to the Deparment of Mechanical Engineering of Sheffield University (INSIGNEO Institute for in silico Medicine). During this appointment, he was involved in the European Project MD-Paedigree and the EPSRC project MultiSim, developing methods to generate patient-specific musculoskeletal models.

In 2017 Luca was awarded a prestigious Imperial College Research Fellowship for a project aiming to optimize the outcome of surgical interventions using a combination of advanced computational methods including patient-specific neuro-musculoskeletal modelling, finite element analysis and predictive simulations.

Computational and Modelling resources

OPENSIM PLUGIN TO EXTRACT MUSCLE LINES OF ACTION
During my PhD I implemented a plugin to extend the capabilities of OpenSim and extract the lines of action of musculotendon actuators. This information is useful if you have the intention of using forces computed by musculoskeletal models in finite element analysis. The compiled library is available through the website: , while the source code is available contacting me directly. The plugin has been used in the following open access publications:

van Arkel, R. J., Modenese, L., Phillips, A. T. M. and Jeffers, J. R., 2013. Hip Abduction Can Prevent Posterior Edge Loading of Hip Replacements. Journal of Orthopaedic Research 31, 1172-1179.
Phillips, A. T. M., Villette C. and Modenese, L. 2015. Femoral Bone Mesoscale Structural Architecture Prediction using Musculoskeletal and Finite Element Modelling, International Biomechanics 2, 43-61.
Please cite the paper by van Arkel et al. if you are using the plugin for your own research.
OPENSIM PLUGIN TO OPTIMIZE MUSCLE CONTRACTION PARAMETERS
The majority of the generic musculoskeletal models are based on cadaveric dissection datasets including bone geometries, joint parameters, muscle attachments, and muscle architectural parameters defining muscle contraction. When building subject-specific musculoskeletal models, for example using medical images, these muscle architectural parameters are not available and can be difficult to estimate unless measurements of muscle function, such as isometric or isokinetic maximum contractions, are available. Together with colleagues from Griffith University and University of Padua we generalized a previously published algorithm by Winby et al. to allow estimation of musculotendon parameters in personalized models (both linearly scaled and created from medical images) and implemented the algorithm in an OpenSim plugin. The source code of the plugin can be downloaded from . The algorithm is also available as a tool for OpenSim, via Java integration.

The paper associated with this work is:

Modenese, L., Ceseracciu, E., Reggiani M. and D. G. Lloyd (2016). "Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique." Journal of Biomechanics 49, 141-148
Please note that for this paper, MATLAB code that can be used to reproduce exactly the results and figures presented in the manuscript is available from https://simtk.org/projects/opt_muscle_par.

opensim model of the lower limb
As part of my doctoral work I implemented a lower limb model using the anatomical dataset published by Klein Horsman et al.(2007), which is currently available for download from and it is associated with publication:

Modenese, L., Phillips, A. T. M. and Bull, A. M. J. (2011). An open source lower limb model: Hip joint validation. Journal of Biomechanics 44, 2185-2193