Passive mechanical properties of whole skeletal muscle are not as well understood as active mechanical properties. Both the structural basis for passive mechanical properties and the properties themselves are challenging to determine because it is not clear which structures within skeletal muscle actually bear passive loads and there are not established standards by which to make mechanical measurements. Evidence suggests that titin bears the majority of the passive load within the single muscle cell. However, at larger scales, such as fascicles and muscles, there is emerging evidence that the extracellular matrix bears the major part of the load. Complicating the ability to quantify and compare across size scales, muscles and species, definitions of muscle passive properties such as stress, strain, modulus and stiffness can be made relative to many reference parameters. These uncertainties make a full understanding of whole muscle passive mechanical properties and modelling these properties very difficult. Future studies defining the specific load bearing structures and their composition and organization are required to fully understand passive mechanics of the whole muscle and develop therapies to treat disorders in which passive muscle properties are altered such as muscular dystrophy, traumatic laceration, and contracture due to upper motor neuron lesion as seen in spinal cord injury, stroke and cerebral palsy.

Dynamic movement trajectories of low mass systems have been shown to be predominantly influenced by passive viscoelastic joint forces and torques compared to momentum and inertia. The hand is comprised of 27 small mass segments. Because of the influence of the extrinsic finger muscles the passive torques about each finger joint becomes a complex function dependent on the posture of multiple joints of the distal upper limb. However, biomechanical models implemented for the dynamic simulation of hand movements generally don’t extend proximally to include the wrist and distal upper limb. Thus, they cannot accurately represent these complex passive torques. The purpose of this short communication is to both describe a method to incorporate the length-dependent passive properties of the extrinsic index finger muscles into a biomechanical model of the upper limb and to demonstrate their influence on combined movement of the wrist and fingers. Leveraging a unique set of experimental data, that describes the net passive torque contributed by the extrinsic finger muscles about the metacarpophalangeal joint of the index finger as a function of both metacarpophalangeal and wrist postures, we simulated the length-dependent passive properties of the extrinsic finger muscles. Dynamic forward simulations demonstrate that a model including these properties passively exhibits coordinated movement between the wrist and finger joints, mimicking tenodesis, a behavior that is absent when the length-dependent properties are removed. This work emphasizes the importance of incorporating the length-dependent properties of the extrinsic finger muscles into biomechanical models to study healthy and impaired hand movements.

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