Abstract
AbstractThe question how the brain controls locomotion is a highly treated one. This topic is taken up in this study by means of human computational models, simulating the human musculoskeletal system actuated by advanced Hill‐type muscle models. A forward dynamic approach is considered allowing to simulate human motion independently from pre‐measured trajectories and enabling to resemble the control of the central nervous system – the motor command selection. It is suggested that movement paths arise implicitly through optimisation [1,4]. Hence, stimulation patterns passing through activation dynamics are determined by means of constrained optimal control problems with physiologically motivated objective functions. One advantage concerning the implementation within Neweul‐M2 is the possibility to apply well‐elaborated and tested optimisation algorithms available with Matlab to solve optimal control problems, enabling to employ the novel non‐linear model predictive control (NMPC). The introduced framework is applied to treat different biomechanical movement scenarios including reaching scenarios of the arm which are validated against experimental data from [2–4]. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
