An EMG-to-force processing approach for determining ankle muscle forces during normal human gait

Area of Science:

• Biomechanics
• Human Movement Analysis
• Musculoskeletal Modeling

Background:

• Estimating in vivo muscle forces is essential for understanding limb movement.
• Direct measurement of muscle forces is often impractical or impossible.
• Electromyography (EMG) provides indirect information about muscle activity.

Purpose of the Study:

• To develop and validate an electromyography (EMG)-to-force processing technique.
• To calculate ankle joint moments and muscle forces during gait.
• To compare EMG-derived forces with inverse dynamics and direct measurements.

Main Methods:

• Developed an electromyography (EMG)-to-force processing model.
• Calculated ankle joint moments using inverse dynamics during free-speed gait in ten adults.
• Determined ankle muscle forces, specifically peak Achilles tendon force.

Main Results:

• A strong correlation was found between inverse dynamics ankle moments and EMG-to-force derived moments.
• Peak Achilles tendon force during gait was accurately predicted (2.9 kN).
• The predicted force closely matched in vivo measurements obtained with force transducers (2.6 kN).

Conclusions:

• The developed EMG-to-force processing model is a practical and accurate method for estimating in vivo muscle forces.
• This technique offers a viable alternative to direct force measurements in biomechanical studies.
• The findings have implications for gait analysis and understanding muscle function during locomotion.