Using EMG data to constrain optimization procedure improves finger tendon tension estimations during static fingertip...

Area of Science:

• Biomechanics
• Musculoskeletal modeling
• Human hand function

Background:

• Accurate estimation of finger muscle tendon tensions is essential for understanding and treating hand pathologies.
• Direct measurement of tendon forces is often impractical, necessitating biomechanical modeling.
• A key challenge in modeling is the under-determined nature of the system due to more muscles than joint degrees of freedom.

Purpose of the Study:

• To develop and validate a novel method for estimating middle finger tendon tensions during static force production.
• To compare the proposed method with classical numerical optimization and EMG-only approaches.
• To assess the influence of integrating electromyography (EMG) data as inequality constraints.

Main Methods:

• A numerical optimization procedure utilizing the muscle stress squared criterion was employed.
• Intra-muscular electromyography (EMG) data from three extrinsic hand muscles were incorporated as inequality constraints.
• The results were benchmarked against traditional optimization and EMG-based methods.

Main Results:

• The proposed method yielded tendon tension estimations that respected mechanical equilibrium.
• The results demonstrated concordance with the distribution patterns of subject EMG data.
• Neither classical optimization nor the EMG-only method achieved comparable results.

Conclusions:

• Integrating EMG data as inequality constraints into an optimization process provides relevant tendon tension estimations.
• This approach accurately reflects individual muscle activation patterns, including antagonist muscles.
• The developed method offers a more reliable tool for analyzing finger muscle forces in biomechanical studies and clinical applications.