Predicting Sit-to-Stand Adaptations due to Muscle Strength Deficits and Assistance Trajectories to Complement Them - Kumar, Vinay; Yoshiike, Takahide; Shibata, Tomohiro (Frontiers in Bioengineering and Biotechnology, 2022)
Sit-to-stand (STS) transition is the most bio-mechanically challenging task necessary for performing activities of daily life. With muscle strength being the most dominant, many co-occurring factors influence how individuals perform STS. This study investigates the changes in STS caused by muscle strength deficits and how they might lead to unsuccessful STS. It also presents the external assistance trajectories that can complement strength deficits for successful STS transition. Towards these aims, first, the STS trajectories generated for musculoskeletal models with different strength deficits using single shooting optimization are presented. The muscle strength deficits were introduced by simultaneously scaling the maximum isometric strength of muscles in steps of 20%. The optimization could generate successful STS transition for the 0%, 20%, and 40% strength deficit models. The common activation patterns among these trajectories agree with the literature for all the muscles except the rectus femoris. Comparison of these trajectories shows that the STS duration increases with strength deficits while the peak vertical center of mass velocity and the peak gluteus maximus and vastus muscle forces decrease. Also, with strength deficits, the hamstring muscle activation reduces, which relieves the antagonistic vastus muscle but stresses the agnostic gluteus maximus muscle. Subsequently, the vastus muscle weakness is proposed to cause unsuccessful STS transition of the 60% strength deficit model using motion tracking results. Finally, the successful STS trajectory generated for the 60% strength deficit model assisted externally at the torso is presented. The trajectory features utilization of external assistance as and when needed to complement strength deficits for successful STS transition. Our results will help plan intervention and design novel STS assistance devices.