An EMG-to-Force Processing Approach to Estimating Knee Muscle Forces during Adult, Self-Selected Speed Gait

Area of Science:

• Biomechanics
• Kinetics
• Muscle Physiology

Background:

• Estimating individual knee muscle forces during gait is challenging without invasive methods.
• An EMG-to-force processing (EFP) model was developed to estimate muscle-tendon unit (MTU) force output based on gait electromyography (EMG).

Purpose of the Study:

• To determine knee muscle-tendon unit force production during self-selected speed normal gait.
• To validate a non-invasive EMG-to-force processing (EFP) model for estimating knee muscle forces.

Main Methods:

• Developed an EMG-to-force processing (EFP) model to scale muscle-tendon unit (MTU) force output to gait EMG.
• Calculated net knee moments using the EFP model and validated against inverse dynamics (KIN).
• Assessed model validity by comparing moment power curves from both methods during active muscle forces.

Main Results:

• The correlation between the EFP and KIN methods was sufficiently close.
• This close fit suggests the EFP model provides reasonable estimates of knee muscle forces.

Conclusions:

• The EMG-to-force processing approach offers a viable non-invasive method for estimating individual knee muscle forces.
• This model is applicable to self-selected speed walking in neurologically intact adults.