Real-time muscle force estimation

Abstract

Human body consists of bones and muscles. Especially, since muscles and tendons control body movement by developing forces and exerting moments about joints, information about muscle forces help us to understand human movements more completely. Also, since insufficient muscle forces mean that the activities related to roles of the muscles cannot be performed properly, measurements of muscle forces are considered to be very useful in clinic to judge a patient’s potential for function. For these reasons, many biomechanists have been interested in determining muscle forces.Muscle force can be acquired directly or indirectly, however an important aspect of biomechanical research has been directed toward developing accurate indirect techniques because the direct methods are difficult to use widely in clinic. One of the indirect methods is a muscle dynamics, and it becomes available for estimating muscle forces by combining musculoskeletal model and motion data. Recently, study on estimating muscle force in real-time have been directed forward, however previous studies have some limitations in terms of using three-dimensional motion analysis system to obtain human movements.In this study, a real-time muscle force estimation system was developed by using electrogoniometers. To validate the developed system, heel-rise and sit-to-stand experiments were performed for ten subjects with 3D motion analysis. The results from the developed system were compared with those from widely used commercially available software, SIMM, including musculoskeletal model. As the results, the estimation of tendon slack length from tibia length was statistically significant method, and values of musculotendon length from the developed system were similar to those from SIMM. The RMS differences of musculotendon length were less than 6 mm in most. The relationship between the values of muscle

force from the developed system and those from SIMM had a low correlation compared to the values of musculotendon length. Therefore, further studies would be required to improve the developed system in terms of designing real-time filter and using high resolution electrogoniometers.Interests for a real-time muscle force estimation system are increased gradually. If the accuracy of the real-time muscle force estimation system developed in the present study is more improved, it will be expected to be applied to a clinically meaningful tool.