Safe pre-operative traction applied and maintained to the fractured site in fracture reduction surgery is crucial. However, existing traction techniques performed by clinicians or manual traction devices are not elaborate and have no traction force information considering differences in patients’ bodies. The purpose of this study was to evaluate joint loads of fractured sites as pre-operative traction forces considering body mass index (BMI) during fracture reduction surgeries using a robotassisted device. We developed a lower-extremity dummy model to measure joint loads at hip, knee, ankle, and fractured sites. In 240 cases, four BMI types, six traction forces and two fractured sites were used. Results showed that joint load on major joints decreased as BMI increased. Additionally, joint load increased proportionally in the fractured tibia, but showed inverse tendency in the fractured femur. Control errors of up to 20% in repetitive control and approximately 30% in random control were measured, in comparison to estimated joint loads. Control error increased as traction force decreased. It is possible that applicability of robot systems to safe and precise surgical assistance can be validated. More precise traction control and real-time traction load monitoring technology will enable replacement of traction techniques in the near future.

In soccer, sports science aims to prevent injuries and improve performance by biomechanically analyzing a series of the kick processes. In order to understand the kick processes biomechanically, studies on kinematic, kinetic, and EMG have been conducted. However, these studies have limitations due to absence of integrated theory defining interactions between the segments. In the present work, we propose a model to understand dynamic characteristics of the kicking leg based on the biomechanical features of the instep kick. Five healthy men participated in an experiment to perform four-level instep kick. We collected kinematic and kinetic information of the hip and knee joints. Based on the passive dominance of the knee joint, we devised the knee joint torque model proportional to angle and angular velocity. RMSE between simulated and real torque was 4.17%, and exhibited a tendency to decrease linearly with the kick speed. Henceforth, it is apparent that the faster the kick, the greater the load on the hip; and the slower the kick, the greater the load on the knee joint. We anticipate that this model will be applied to the kick monitoring equipment and for the prevention of injuries by measuring the load.