School bullying is a serious problem among teenagers, causing depression, dropping out of school, or even suicide. It is thus\nimportant to develop antibullying methods. This paper proposes a physical bullying detection method based on activity recognition.\nThe architecture of the physical violence detection system is described, and a Fuzzy Multi thres hold classifier is developed to\ndetect physical bullying behaviour, including pushing, hitting, and shaking. Importantly, the application has the capability of\ndistinguishing these types of behaviour from such everyday activities as running, walking, falling, or doing push-ups. To accomplish\nthis, the method uses acceleration and gyro signals. Experimental data were gathered by role playing school bullying scenarios and\nby doing daily-life activities. The simulations achieved an average classification accuracy of 92%, which is a promising result for\nsmartphone-based detection of physical bullying.
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