Automatic jump detection in skiing/snowboarding using head-mounted MEMS inertial and pressure sensors

Abstract

With advancing technology in the miniature microelectromechanical systems (MEMS) sensors, wearable devices are becoming increasingly popular, facilitating convenient activity detection. One particular application is in sports performance monitoring. This article presents a novel real-time jump detection algorithm in skiing and snowboarding using a microelectromechanical systems–based inertial measurement unit, which is integrated with a barometric pressure sensor. The key performance variables of the jump can be extracted and evaluated for training and/or entertainment purposes. In contrast to the existing jump detection algorithms based on acceleration signals, the proposed algorithm uses vertical velocity and air time in addition to acceleration in the vertical direction. The experimental results show that by incorporating the velocity and air time into the detection algorithm, the sensitivity and specificity increase dramatically to 92% and 93%, respectively.