Research And Application Of Adaptive Attention Regulation Method Based On Neurofeedback

Attention is the ability of people to focus on something,and it plays a vital role in our study and work.The reduced level of attention will not only affect the efficiency of study and work,but also cause people to produce negative emotions,such as anxiety,stress and depression.Therefore,an effective method of regulating attention can not only improve the efficiency of learning and work,but also help people reduce bad emotions.In recent years,with the development of EEG technology,neurofeedback therapy has gradually become an effective means for attention intervention training,and is widely used in intervention treatment for patients with attention deficit hyperactivity disorder(ADHD).It is precisely because of the characteristics of neurofeedback therapy that there are no side effects and stable curative effect,more and more researchers are gradually carrying out related research.Although neurofeedback has achieved certain results in attention intervention training,most of the current neurofeedback systems are expensive and complicated to operate,so their promotion in China is very slow.In addition,due to the differences in physiological signals between different individuals,the current neurofeedback system does not respond to 25% of the population,and cannot produce corresponding therapeutic effects for everyone.Therefore,this paper proposes an adaptive neurofeedback method,which realizes adaptive threshold and adaptive task difficulty algorithm according to the difference of different individual EEG signals.Based on this method,this paper developed a wearable,adaptive attention regulation system based on EEG feedback.The main contributions and research results of this paper are as follows:(1)A neurofeedback index for attention training is proposed.The EEG data of the subjects under the resting state and Stroop color word stimulation experiment were collected at the two electrodes FP1 and FP2,EEG features related to attention were extracted,and the differences of single features were analyzed.Based on the mean value of the sample entropy of the FP1 electrode and the FP2 electrode(SampEn),the power ratio of theta wave to the beta wave(TBR)of the FP2 electrode,and the power ratio of the alpha wave to the beta wave(ABR)of the FP1 electrode neurofeedback indicators.(2)Aiming at the differences of different individuals,an adaptive attention regulation method is proposed,and an adaptive attention regulation system is designed.In order to adapt to the differences in individual EEG signals,a personalized threshold selection method is proposed,which selects the neurofeedback thresholds of different individuals.For the differences in individual self-regulation capabilities,a proportional integral derivative(PID)controller is used to achieve adaptive Game difficulty algorithm,and proposed a method for determining PID parameters based on regression model.Finally,based on the above method,a portable three-lead EEG sensor is used to collect EEG data,and the feedback index is extracted through windowed fast Fourier transform.To reduce the time delay,3 different feedback training games were designed to meet the needs of different subjects,and an adaptive attention regulation system was developed.(3)Designed an adaptive neurofeedback experiment for attention intervention training,which verified the effectiveness of the adaptive attention regulation method and feedback system.After 5 feedback training experiments,the scale scores of the adaptive feedback training group showed significant changes.The scores of ASRS and Schulte grid scale decreased by 45.65% and 30.83%,respectively,and the score of MARS scale increased by 14.40%;its feedback The indicators have also changed significantly.ABR,TBR,and Samp En have decreased by 57.78%,77.90%,and 12.25%,respectively.Participants' attention level has been significantly improved,and the effect of adaptive neurofeedback training on improving attention exceeds that of standard neurofeedback training.