Musculoskeletal (MSK) models and simulations enable to get insights into the internal biomechanics of an individual performing any activity (e.g, walking, running, standing).

Most commonly, it is assumed that our brain adopts/favours an optimal control strategy, i.e. selects the set of muscle activations and forces to produce a certain movement so that the metabolic/energy consumption is minimized. However, this assumption is not always valid, especially when simulating maximal effort tasks or in the presence of neuromuscular disorders (e.g. cerebral palsy, Parkinson’s disease). Also very common daily activities can invalidate the assumption if for some reason the posture is not optimal.

Novel computational methods enable us to explore the (physiological) solution space that includes a wide range of possible muscle activations and forces a single person can produce to perform a given task, leveraging on a powerful stochastic approach (i.e., Metabolica).

The aim of this work is to use MSK modeling and simulations, with and without the use of Metabolica, to investigate the act of breathing and its influence over posture and stability, unveiling the contribution of all muscles involved.

The projects is part of a collaboration with the University of Bologna. The possibility of a secondment in Bologna can be discussed with students interested in completing the master in two years.

References:

Heino, J., Calvetti, D., Somersalo, E., 2010. Metabolica: A statistical research tool for analyzing metabolic networks. Comput. Methods Programs Biomed. 97, 151–167. https://doi.org/10.1016/j.cmpb.2009.07.007

Van Veen, B.C., Mazzà, C., Viceconti, M., 2020. The Uncontrolled Manifold Theory Could Explain Part of the Inter-Trial Variability of Knee Contact Force during Level Walking. IEEE Trans. Neural Syst. Rehabil. Eng. 28, 1800–1807. https://doi.org/10.1109/TNSRE.2020.3003559

Tassani, S., Font-Llagunes, J.M., González Ballester, M.Á., Noailly, J., 2019. Muscular tension significantly affects stability in standing posture. Gait Posture 68, 220–226. https://doi.org/10.1016/j.gaitpost.2018.11.034

Supervisors: Simone Tassani