Title
How Muscle Stiffness affects Neural Control Parameters: Short-Range Stiffness Improves Stability and Feedback Robustness of Musculoskeletal Models
Author
Gründemann, Axel (TU Delft Mechanical, Maritime and Materials Engineering)
Contributor
Mugge, W. (mentor)
Negrello, Mario (mentor)
van der Helm, F.C.T. (mentor)
Fernandez Santoro, E.M. (mentor)
Degree granting institution
Delft University of Technology
Programme
Biomedical Engineering | Neuromusculoskeletal Biomechanics
Date
2023-04-05
Abstract
This paper investigates the effect of intrinsic muscle stiffness on neural control parameters in biological musculoskeletal control of stabilisation or reaching tasks. Current model implementations of intrinsic muscle properties are highly simplified, limiting their accuracy in replicating experimental short-range stiffness (SRS) behaviour, which appears to be important for stabilisation tasks. The Hill model, often used in musculoskeletal simulations, cannot account for SRS, while the Huxley model, which can account for non-linear muscle phenomena such as SRS , has a higher computational burden. The study compares a simplified Huxley-type model to two Hill-type models and determines the effect of intrinsic SRS on the control parameters of stabilizing 1- and 2-Degree of Freedom musculoskeletal models over various positive and negative stiffness positions in the force-length curve. Furthermore, the effect of the intrinsic muscle stiffness on the robustness of the feedback parameters of simple individual muscle feedback systems is determined in reaching experiments similar to classic experiments.
The study finds that the Huxley model shows positive SRS in the negative flank of the force-length curve, achieves stabilisation through only co-contraction using a lower level of required muscle excitation than both Hill-type models and stabilises both musculoskeletal systems at a larger muscle range than the Hill-type models, including in the negative stiffness flank. The feedback parameters dominantly responsible for muscle activation patterns are also more robust to change in the Huxley model. These findings suggest that intrinsic muscle stiffness impacts neural control parameters in stabilisation and reaching tasks, and further musculoskeletal modelling should consider using more complex muscle stiffness calculations for improved accuracy.
Subject
Huxley
Hill
Short-range stiffness
Muscle stiffness
Stabilisation
Reaching
Force-length
negative stiffness
negative flank
cross-bridge
Huxley-type
Hill-type
CE
PE
SE
force-velocity
self-stabilising
stabilising
self-stabilisation
neuromechanics
biomechanics
biomechanical
Intrinsic feedback
Intrinsic stiffness
Intrinsic muscle stiffness
muscle viscocity
reflex
reflex pathway
intrinsic pathway
intrinsic feedback pathway
To reference this document use:
http://resolver.tudelft.nl/uuid:cdd34e5b-2e84-4a79-9e8c-ad9718d5ae01
Embargo date
2024-09-24
Coordinates
52.00107845708114, 4.371212070976078
Part of collection
Student theses
Document type
master thesis
Rights
© 2023 Axel Gründemann