Distributed loads alter internal load predictions in the hands and forearm

Area of Science:

• Biomechanics
• Human-Computer Interaction
• Robotics

Background:

• Accurate modeling of hand forces is crucial for understanding human movement and designing effective robotic interfaces.
• Previous models often simplified external force application, potentially limiting biofidelity.

Purpose of the Study:

• To investigate the influence of distributed external hand forces on joint moments and muscle activation.
• To compare the biomechanical outputs of different external force input models in OpenSim.

Main Methods:

• Collected kinematic and force data during multi-finger tasks.
• Measured surface pressure to develop three force input models in OpenSim: center of mass (CM), center of pressure (CP), and single point force (SP).

Main Results:

• Center of mass (CM) and center of pressure (CP) models produced equivalent joint moments and muscle activations.
• Distributed loading (CM and CP) resulted in significantly lower moments and muscle activation compared to the single point force (SP) model.
• Internal loads were sensitive to the distribution of external forces.

Conclusions:

• The distribution of external forces significantly impacts internal loads, joint moments, and muscle activation.
• Distributed force models (CM and CP) offer improved biofidelity in hand modeling compared to simplified single point force models.
• Complex external force inputs enhance the accuracy of hand biomechanical models.