Techniques in Pattern Recognition for School Bullying Prevention: Review and Outlook

Abstract

School bullying is a serious problem among teenagers. With the development of sensor technology and pattern recognition algorithms, several approaches for detecting school bullying have been developed, namely speech emotion recognition, mental stress recognition, and activity recognition. This paper reviews some related work and makes some comparisons among these three aspects. The paper analyzes commonly used features and classifiers, and describes some examples. The Gaussian Mixture Model and the Double Threshold classifiers provided high accuracies in many experiments. By using a combined architecture of classifiers, the results could be further improved. According to the results of the experiments, the six basic emotions, high mental stress and irregular movements can be recognized with high accuracies. So the three types of pattern recognition can be used for school bullying detection effectively. And these techniques can be used on consumer devices such as smartphones to protect teenagers.

Physical Violence Detection with Movement Sensors

“…In 2014, Alasaarela [4] argued that activity recognition with movement sensors can also be used for school violence detection, i.e. with wearable movement sensors such as smartphones embedded with accelerometers and gyroscopes, one can detect school violence events.…”

Bullying incidences identification within an immersive environment using HD EEG-based analysis: A Swarm Decomposition and Deep Learning approach

“…Consequently, these approaches fail to reproduce the environment in which the event took place and, therefore, the results that occur from such research are not always so conclusive. With the development of technology, many different techniques of detecting school bullying have been developed, such as speech emotion recognition, mental stress recognition, and activity recognition 9 , 10 . Moreover, there is relative research around the study of EEG signals during relaxation and mental stress condition 11 , along with EEG-based emotion recognition 12 .…”