Classification of surfaces and inclinations during outdoor running using shoe-mounted inertial sensors

Embedded mobile systems for analysis and classification become more and more important in the field of sports and sports science. Small and lightweight sensors in sportswear offer the possibility to monitor the athletes in a realistic environment, e.g. during an outdoor run. During the activity, the sportswear can automatically adapt to the current environment and hence optimizes the performance of the athlete. A major need is a running shoe, which can automatically be adapted to the current ground. In this paper, a classification system was developed, which distinguished between different surfaces and inclinations based on inertial sensors. They were placed on the heel of a running shoe and acquired kinematic data of 21 subjects. For each subject, several rounds of an one hour outdoor run were available and were used for the evaluation of the system. The classification system reached a mean classification rate of more than 80 %.