An Electromyography-Assisted Musculoskeletal Simulation With Concurrent Optimization of Muscle Excitations and Knee...

Area of Science:

• Biomechanics
• Musculoskeletal modeling
• Computational simulation

Background:

• Accurate musculoskeletal (MSK) simulation is vital for understanding joint mechanics.
• Electromyography (EMG) data can improve the accuracy of MSK models.
• Previous models often simplify knee joint complexity.

Purpose of the Study:

• To develop and validate an EMG-assisted MSK simulation method for knee biomechanics.
• To optimize knee kinematics and muscle excitations concurrently.
• To compare the performance of a 12-DoF model against simpler models and static optimization.

Main Methods:

• Developed a 12-degree-of-freedom (DoF) knee MSK model with personalized articulating surfaces.
• Calibrated muscle parameters and performed EMG-assisted analysis.
• Compared the model against 1-DoF and 12-DoF models using static optimization (SO) and uncalibrated EMG-assisted methods, validated against in vivo data.

Main Results:

• EMG-assisted models outperformed SO solutions for muscle excitations and joint contact force (JCF).
• The 12-DoF EMG-assisted model improved estimation of muscle excitations, joint moments, and transverse JCF compared to the 1-DoF EMG-assisted model.
• A 1-DoF EMG-assisted model may suffice for estimating compressive JCF during walking.

Conclusions:

• The EMG-assisted 12-DoF knee model is recommended for accurate estimation of joint moments, muscle forces, and JCF, particularly in cases of musculoskeletal disorders.
• The developed simulation method offers a viable approach for estimating knee biomechanics with personalized muscle excitation and joint geometry.
• This method enhances the understanding of knee function and informs clinical applications.