Synthesis of Subject-Specific Human Balance Responses Using a Task-Level Neuromuscular Control Platform

Area of Science:

• Biomechanics and Robotics
• Human Movement Science
• Neuromuscular Control

Background:

• Activities of daily living demand significant neuromuscular coordination and balance control to prevent falls.
• Complex musculoskeletal models and neuromuscular simulations are crucial for understanding coordinated and uncoordinated human movements.

Purpose of the Study:

• To develop a closed-loop forward dynamic simulation framework for synthesizing human balance responses.
• To validate the framework using experimental kinematic data from healthy subjects.
• To explore the reconstruction of complex, subject-specific movements through sequenced task-level commands.

Main Methods:

• Creation of a closed-loop forward dynamic simulation framework with a 19-degree-of-freedom, 92-muscle musculoskeletal model.
• Integration of surrogate response models of experimental kinematics to inform the task-level controller.
• Simulation of human balance responses to support-surface perturbations.

Main Results:

• Predicted muscle activations and synthesized joint angles closely matched experimental trial averages.
• Simulated whole-body center of mass displacements were within 7 mm (anterior) and 13 mm (posterior) of experimental data.
• Demonstrated successful reconstruction of complex subject-specific movements via prioritized task-level commands.

Conclusions:

• The simulation framework accurately reconstructs human balance responses and complex movements.
• The platform effectively combines robotics and biomechanics for studying human movement control.
• Offers significant potential for subject-specific outcome prediction in movement studies.