Biomedical Engineering Reference
In-Depth Information
Considering the geometric model, the number of embedded 1D FE meshes within
the 3D FE geometry cannot reach a physiological-realistic muscle fiber number.
This is due to the computational load involved in solving the cellular model, which
is an integral part of modeling the action potential propagation by means of the
bidomain equations. Further, the assignment of muscle fibers to particular motor
units has been based on physiological data published in the literature. Although
much physiological information and knowledge has been included in constructing
the geometrical model, there is still a considerable amount of uncertainty present.
This stems mainly from the fact that muscle fibers associated with a motor unit can
only be experimentally determined for one motor unit per muscle. This is due to the
destructive nature of the experimental setup. Moreover, there exists a great inter-
subject variability in muscle fiber distribution. Nevertheless, the model can be used
to test different hypothesis and investigate the influence of different muscle fiber
types in different regions of the muscle.
From a continuum-mechanical material modeling point of view, the constitutive
equations presented in Eqs. (
8.1
), and (
8.2
) in case of modeling the electromechan-
ical behavior of skeletal muscle, have been designed to describe the characteristic
properties of skeletal muscle tissue in a phenomenological way. However, thorough
validation of the active and passive behavior in conjunction with experiments is still
missing. On the upside, the continuum-mechanical modeling framework of the mus-
culoskeletal system provides the ability to include further mechanical features that
cannot be included in multi-body dynamics simulations. For example, the mechan-
ical behavior of skeletal muscles can now be easily subjected to other constraints
and restrictions arising from the contact with neighboring structures such as adja-
cent muscles, bones, and skin. To realistically simulate the mechanical behavior of
skeletal muscle in vivo, the influence of these structures has to be considered.
Both described models, e.g., the electromechanical single muscle model and the
musculoskeletal system model of the upper arm, have not been validated against
experimental data yet. Like for most biomechanical models, developing suitable
experimental setups for validation is challenging. Here, however, there exist several
different possibilities to validate the musculoskeletal system model of the upper
arm through combined measurements of muscular activity (EMG) and motion (via
motion capture). Further, other measuring modalities can be added to EMG and
motion measurements. For example, pressure sensors or ultrasound devices, which
have recently been used to investigate muscular contractions through the change in
fiber angle, can significantly augment the EMG and motion measurements.
Although the electromechanical model is subject to restrictions, it provides a
new basis to study motor unit recruitment principles and to simulate EMG-driven
forward dynamics simulations of the musculoskeletal systems. By using multi-body
simulations to cheaply describe overall characteristics and FE simulations to take
into account local and structural information, the 3D forward-dynamics simulation
framework will give rise to many new opportunities in investigating the muscu-
loskeletal system and many biomechanical applications. For example, determining
the dynamic loading conditions of joints during normal movement will play a crucial
