Estimation of muscle forces in gait using a simulation of the electromyographic activity and numerical optimization

Abstract

Clinical gait analysis provides great contributions to the understanding of gait patterns. However, a complete distribution of muscle forces throughout the gait cycle is a current challenge for many researchers. Two techniques are often used to estimate muscle forces: inverse dynamics with static optimization and computer muscle control that uses forward dynamics to minimize tracking. The first method often involves limitations due to changing muscle dynamics and possible signal artefacts that depend on day-to-day variation in the position of electromyographic (EMG) electrodes. Nevertheless, in clinical gait analysis, the method of inverse dynamics is a fundamental and commonly used computational procedure to calculate the force and torque reactions at various body joints. Our aim was to develop a generic musculoskeletal model that could be able to be applied in the clinical setting. The musculoskeletal model of the lower limb presents a simulation for the EMG data to address the common limitations of these techniques. This model presents a new point of view from the inverse dynamics used on clinical gait analysis, including the EMG information, and shows a similar performance to another model available in the OpenSim software. The main problem of these methods to achieve a correct muscle coordination is the lack of complete EMG data for all muscles modelled. We present a technique that simulates the EMG activity and presents a good correlation with the muscle forces throughout the gait cycle. Also, this method showed great similarities whit the real EMG data recorded from the subjects doing the same movement.

Keywords::

• musculoskeletal model
• muscle forces
• clinical decision-making
• gait analysis
• electromyography

Acknowledgements

The authors thank the FLENI Institute for Neurological Research for providing data from healthy subjects and the National Council of Scientific and Technical Research (CONICET), PID 6125 (UNER) and PICTO 222-2009 (AGENCIA) for providing the funds needed for this research.

Conflict of interest statement

We do not have any financial or personal relationships with other people or organizations that could inappropriately influence our manuscript.

Notes

^1. E-mail:[email protected]

^2. E-mail:[email protected]