Research And Implementation Of An Attention Monitoring System Based On Android Platform

Attention Deficit Hyperactivity Disorder(ADHD) is a mental disease common in childhood and adolescence, influencing the physiological and psychological development of children and adolescents seriously, in recent years, a new treatment for ADHD called EEG Biofeedback rose into the sight of the public. The curative effect of EEG Biofeedback is equivalent to central nervous system stimulant and without side-effect and drug dependence, so it is now attracting increasing attention of basic medical and clinical medical researchers. But the studies related are mostly limited to clinical trials and theoretical algorithm, equipment needed by the treatment is very expensive, and the data acquired can only be read by professional, making this excellent treatment hard to promote. So, the research and implementation of a cheap, small, portable and intuitive attention monitoring system is of great practical significance.This paper developed an attention monitoring system based on Android platform, possessing the functions of the recognition of attention-related EEG, the real-time monitoring and feedback of subject’s attention. Firstly, this paper elaborated the common designing of attention-related experiment and the common methods to analyze attention-related EEG, designed the EEG acquisition system based on ThinkGear AM and accomplished the UI designing, event responding designing and the programming of four functional modules including Bluetooth receiver, spectrum transform, BP neural network and real-time displaying in Android platform.Then, according to the solving process of the classification of attention-related EEG, an attention-related experiment was designed and conducted, the EEG signals were captured, preprocessed and feature extracted into five characteristic parameters in energy ratio form. Moreover, based on the structure and algorithm of BP neural network, a multi-feature parameter nonlinear analytical method was proposed and the eigenvector matrix extracted was used for the training of the network, after the testing, the recognition accuracy of attention-related EEG is 77.5%.The final result shows that the attention monitoring system based on Android platform is simple, portable, cheap, and intuitive, it has great practical meaning to the promotion of EEG Biofeedback and has certain innovation and practicability.In addition, this paper did some investigations and exploration to the meditation treatment for ADHD risen recent years. By collecting, filtrating and classifying several neuroimaging studies about meditation treatment and conducting an ALE meta-analysis based on corresponding activations, this paper elaborated the mechanism of meditation treatment and demonstrated its effect for ADHD.