A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology.

Greater understanding of differences in technique between runners may allow more beneficial feedback related to improving performance and decreasing injury risk. The purpose of this study was to develop and test a support vector machine classifier, which could automatically differentiate running technique between experienced and novice participants using only wearable sensor data. Three-dimensional linear accelerations and angular velocities were collected from six wearable sensors secured to current common smart device locations.

Skateboarding Injuries in Spain: A Web-Based Survey Approach.

Background: The inclusion of skateboarding in the Tokyo 2020 Olympic Games reinforces this activity as a sport. As the number of skateboarders around the world and the difficulty of skateboarding maneuvers continue to increase, the number of skateboarding injuries may also rise. Thus, there is a need for more comprehensive investigations into the practice habits and injuries of skateboarders.