An instance-based physical violence detection algorithm for school bullying prevention

School bullying is a common social problem around the world which affects teenagers, and physical violence is considered to be the most harmful. This paper proposed an automatic physical bullying detection method with movement sensors to protect teenagers. Four features were extracted from acceleration and gyro data, and an Instance-Based classifier was applied upon them. Altogether eight kinds of activities, including three bullying kinds and five daily-life kinds, were acted by role playing. Simulations were performed on these data, and the results showed that the proposed algorithm could recognize physical bullying events and distinguish them from daily-life ones at an average accuracy of 80%. This showed a promise in automatic school bullying prevention with activity recognition techniques.