Research Of Attention Detection System Based On Android Platform

Attention is the ability to direct and concentrate on a specific object at the beginning of the individual's perception of something.Since the 21 st century,the healthy growth of children and adolescents has attracted more and more attention from parents,but the attention deficit or unconcentration has become one of the important factors that restrict their healthy growth.Research has shown that more than 5% of children or adolescents have this phenomenon.Attention deficit often manifests as distraction,impulsivity,etc.For example,they are often unable to concentrate on learning because of distraction in the classroom so that their learning efficiency is poor;they are also difficult to communicate with others result in affecting the improvement of their sociality ability.At present,traditional methods of drug therapy,psychotherapy and behavioral interventions are beneficial to regulate and improve attention deficit,but their period is long and the effect is unstable.With the development of the cognitive neuroscience,a new treatment called EEG biofeedback rose into the sight of the public,but there are many problems such as training difficulties and high cost.Based on this situation,this paper intends to develop an attention monitoring system based on android platform to provide a more convenient and efficient way for children and adolescents to monitor their attention and improve or optimize attention-related psychological resources.This article briefly introduces physiological structure,physiological division and attention-related neural mechanisms of the brain.Then,the article also designs the attentionrelated EEG experiments.The acquisition and storage of the EEG data of the subjects were completed under standard experimental environment.At the same time,these EEG data collected were analyzed offline by using wavelet packet decomposition and sample entropy algorithm.This paper acquire the percentage ratio of betla wave energy to theta wave energy by using 7-layer db4 wavelet from the time-frequency perspective and acquire the sample entropy from the perspective of nonlinear dynamics.Experimental results show that both can represent the state of attention level to some extent,but the sample entropy is better for displaying multi-level attention.Finally,this paper develop an attention monitoring system based on android platform using java programming language.After testing,The system can not only realize the acquisition and storage of EEG signals,real-time display of attention level,but also provide the EEG biofeedback training to improve the attention of children and adolescents.This research not only realized a mobile attention detection method,but also actively promoted the popularization based on EEG biofeedback therapy.