Sit-to-Stand Motion Analysis Using Multiobjective Genetic Algorithm Based on Musculoskeletal Model Simulation

One of the most vital skills of daily life is the ability to stand from a sitting position. This study aims to use musculoskeletal model simulation to create an optimal sit-to-stand motion without causing stress to the knee joints while activating the weak muscles. Numerical optimization was performed using the musculoskeletal model by applying the multiobjective genetic algorithm. The numerical optimization results indicate that by placing the feet under the chair prior to standing (not bending the upper body visibly forward) during the sit-to-stand movement, it is possible to reduce stress on the knee joints and muscles. To validate this optimized sit-to-stand motion, we performed two experiments. First, we calculated a correlation value between simulation and experimental results relative to muscle activity, and verified that there is a significant correlation. Next, two types of sit-to-stand movements performed by five healthy male subjects were analyzed: spontaneous sitting-to-standing and imitated sitting-to-standing using the optimized motion. The experimental results confirm that the imitated movement reduces the knee joint’s maximum torque.