Incorporating the length-dependent passive-force generating muscle properties of the extrinsic finger muscles into a wrist and finger biomechanical musculoskeletal model

Abstract

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 27smallmass segments. Because of the influence of the extrinsic finger muscles, the passive torques about each finger joint become 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.

Keywords: Extrinsic finger muscles; Finger; Hand; Musculoskeletal modeling; Passive torque; Wrist.

Figure 1

To enable simulation of combined wrist and finger motions, (a) the kinematic tree of the dynamic model described in Saul et al. (2015) was augmented to (b) include the degrees of freedom and kinematics of the fingers, thumb, and carpal-metacarpal joints. Location of the colored spheres represent the location of center of mass of each individual segment in the distal upper limb within the original model (Saul et al., 2015) and the adapted model; the diameter of each sphere indicates the mass of the modeled segment (see Table 1). Red lines represent simulated muscle-tendon paths within the model; for the purposes of this study, we only included the extrinsic muscles of the index finger.

Figure 2

Moment arm data about the metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints of the current model (solid black), Buford et al. (blue line), An et al. (red line), and Fowler (grey diamonds) of the flexor digitorum superficialis indices (FDSI), flexor digitorum profundus indices (FDPI), extensor digitorum communis indices (EDCI), and extensor digitorum proprius (EIP) muscles. Shaded area indicates two standard deviations when data was available.

Figure 3

Wrist and index finger joint postures as a function of time in a pronated (black lines) and supinated (grey lines) forearm position; optimized model results on the left, model without the length-dependent passive properties on the right. (a) Wrist posture was prescribed identically in both sets of simulations, (b) metacarpophalangeal (MCP), (c) proximal interphalangeal (PIP), and (d) distal interphalangeal (DIP) joints postures were simulated. The dotted line indicates start of wrist motion.