Dynamics of carving runs in alpine skiing. II.Centrifugal pendulum with a retractable leg

Relationship between Lower Extremity Fitness Levels and Injury Risk among Recreational Alpine Skiers: A Prospective Cohort Study

Background: Although the importance of physical fitness for injury prevention is recognized in sports medicine and rehabilitation, few studies have investigated this factor among recreational alpine skiers. Objective: To determine the effect of lower extremity fitness on the risk and severity of injury among recreational alpine skiers. Method: This prospective cohort study involved 117 recreational skiers at two alpine resorts during the 2021−2022 winter season. Anthropometric characteristics, skiing skills, and lower extremity agility (hexagon test), balance (Y-Balance Test), and endurance (60-s squat test) were assessed before the winter season. All of the participants were divided into an injured group and an uninjured group, based on whether an injury was recorded throughout the season. Results: In binary logistic regression, the hexagon test duration and composite Y-Balance Test score were significant injury risk factors (p < 0.05). Ordinal polytomous logistic regression revealed no significant factors for injury severity (p > 0.05). Conclusions: Recreational alpine skiers with inferior lower extremity agility or balance may have a higher injury risk and this must be considered when assessing individual risk. In the context of injury prevention, regular neuromuscular training and testing, including agility and balance aspects should be recommended to skiers.

Carved Turn Control with Gate Vision Recognition of a Humanoid Robot for Giant Slalom Skiing on Ski Slopes

The performance of humanoid robots is improving, owing in part to their participation in robot games such as the DARPA Robotics Challenge. Along with the 2018 Winter Olympics in Pyeongchang, a Skiing Robot Competition was held in which humanoid robots participated autonomously in a giant slalom alpine skiing competition. The robots were required to transit through many red or blue gates on the ski slope to reach the finish line. The course was relatively short at 100 m long and had an intermediate-level rating. A 1.23 m tall humanoid ski robot, ‘DIANA’, was developed for this skiing competition. As a humanoid robot that mimics humans, the goal was to descend the slope as fast as possible, so the robot was developed to perform a carved turn motion. The carved turn was difficult to balance compared to other turn methods. Therefore, ZMP control, which could secure the posture stability of the biped robot, was applied. Since skiing takes place outdoors, it was necessary to ensure recognition of the flags in various weather conditions. This was ensured using deep learning-based vision recognition. Thus, the performance of the humanoid robot DIANA was established using the carved turn in an experiment on an actual ski slope. The ultimate vision for humanoid robots is for them to naturally blend into human society and provide necessary services to people. Previously, there was no way for a full-sized humanoid robot to move on a snowy mountain. In this study, a humanoid robot that transcends this limitation was realized.