The closed kinetic chain is an essential movement method for humans in daily life, and is also important as a training method. However, there have been few studies focusing on the hip adductor muscles. We used electromyography to measure the muscle activity of the hip adductor muscles during walking and standing movements as part of daily living activities, as well as bicycle ergometer exercise and squats. Concerning the role of the adductor muscles, they are thought to stabilize the pelvis during the unilateral support phase when walking, and to act as hip extension and hip alignment adjustment during cycle ergometer exercise. By using electromyography and inertial sensors, the results of this study showed that wearable technologies can be used to quantify neuromuscular function during closed kinetic chain movements. The results serve as a reference for the development of rehabilitation devices, assistive technologies, and computational models that need the simulation of hip joint mechanics. Linking muscle activity data to engineering-based strategies enables precise musculoskeletal assessment and intervention beyond biological observation.

We investigated the effects of manipulating visual information on motor control indicators during the Waiter’s Bow Test. The results suggested that visual information occlusion reduced the maximum flexion angles of the lumbar spine and upper lumbar region. Furthermore, subjects who tested negative under the open-eye condition tested positive under the closed-eye condition. Regarding muscle activity in the rectus abdominis and erector spinae muscles, it was suggested that this activity was not affected by visual information. These findings indicate that visual sensory feedback is one factor influencing lumbar motor control. The integration of electromyography and accelerometer systems in this study highlights the role of wearable sensor technologies in quantifying neuromuscular function in Bioengineering. By restricting visual information, a model for sensory reweighting can be established for the design of biofeedback systems, rehabilitation robotics, and assistive devices. The results of this study demonstrate how sensor-based evaluation and sensory manipulation can inform the engineering of diagnostic and therapeutic technologies for motor control assessment.