earticle

영어

This study represents research on falls while riding bicycles. We present an algorithm that detects the occurrence and direction of falls during bicycle riding through the use of a sensor module installed on the helmet. The sensor module is equipped with a tri-axial accelerometer, tri-axial gyroscope, and tri-axial magnetometer to record acceleration and tilt signals. We determine the threshold of the algorithm for fall detection based on experiments of riding over speed bumps and performing warm-up exercise motions prior to riding a bicycle. The algorithm we developed achieved 98% accuracy in fall detection and 98.5% accuracy in detection of fall direction. This study performed simulations indoors for the sake of subjects’ safety; however, we expect to produce the research in an environment more similar to real-life situations. In future, it is also possible that the developed system will be applied to an emergency reporting system for bicycle falls.