Modeling Human Suboptimal Control: A Review.

Area of Science:

• Biomechanics
• Neuroscience
• Motor Control

Background:

• Neuromuscular control modeling is crucial for understanding movement.
• Identifying nonoptimal strategies is key for populations with neuromuscular disorders or children.
• Existing models have limitations in fully capturing neuromuscular control.

Purpose of the Study:

• To review and compare different approaches for modeling neuromuscular control.
• To highlight the evolution and limitations of various modeling techniques.
• To discuss methods for modeling the nervous and musculoskeletal system interaction.

Main Methods:

• Review of reductionist approaches (static/dynamic optimization, electromyography-based methods).
• Exploration of the stochastic approach and uncontrolled manifold theory.
• Examination of explicit modeling of nervous and musculoskeletal system coupling.

Main Results:

• Reductionist methods offer simplified views but have limitations.
• Stochastic approaches allow for adaptability and energy efficiency exploration.
• Coupled models aim to overcome the limitations of the reductionist approach.

Conclusions:

• Modeling neuromuscular control requires diverse approaches.
• Understanding nonoptimal strategies can inform interventions for specific populations.
• Future models should integrate nervous and musculoskeletal system interactions more effectively.