Study On The Difference Of Miners’ Alertness Under Different Emotions Based On EEG

In coal mine accidents,there are many cases of unsafe behavior and operational errors caused by the reduction of coal mine workers’ alertness.Previous studies have found that the instability of emotional state is more likely to lead to the decline of miners’ attention and other abilities.Therefore,it is of great significance to study the impact of different emotional states of coal mine workers on alertness.Electroencephalogram(EEG)signals show different frequency bands under different alert levels,and the corresponding ’signals of each frequency band have different physiological significance,which provides a new method and idea for studying the influence of different emotional states on the change of miners’ alertness.In recent years,the research on miners’ alertness and miners’ emotion has also made some preliminary achievements,but there is little research on the regulation and influence of emotion on miners’ alertness.In this’ study,EEG acquisition system,subjective scale and PVT task experiment were used to study the influence of different emotional states on miners’alertness and the difference of different emotional states in regulating alertness level.Firstly,with the help of Citespace software,this paper makes keyword and cluster analysis on the research status of the impact of emotion and alertness on miners,combs and expounds the research progress and relevant theoretical basis,which establishes a scientific basis and lays a foundation for subsequent experimental design and data analysis.Then,by designing the effectiveness detection experiment of emotion inducing materials and the PVT experiment based on EEG signals,the subjects were asked to fill in the subjective scale,verify the emotion inducing effect with the help of SPSS statistical analysis software,collect and record the behavior data and EEG data of the subjects under different emotion inducing conditions by using EEG signal acquisition system and prime software,and preprocess the EEG data to collect analysis indicators for subsequent analysis and research.Finally,the data results in the experiment are analyzed.From the dimensions of time stage,emotion type,emotion intensity,experimental time,emotion and the interaction of experimental stage,the results of self-assessment scale and behavior data are analyzed and compared through statistical methods such as two factor repeated measurement analysis of variance and simple effect test.The preprocessed EEG signals are segmented with the help of MATLAB to draw the relative power topographic map,The EEG data of each frequency band are compared and analyzed,and the paired sample t-test is carried out for the power spectral density of each channel.The differences of the effects of different emotions on alertness,the differences of the regulatory effects of different emotions on alertness,and the characteristic laws of the effects of different emotions on alertness in the channels of each frequency band are compared.The results show that different types and intensities of emotions have significant differences in the degree of alertness.Negative emotions are more likely to affect the degree of alertness and reduce the level of alertness than positive emotions;Among the emotions of the same type with different degrees,those with positive factors such as "interested,energetic and energetic"have a better effect on maintaining regulatory vigilance than those with "enthusiastic and firm will",Emotions with "restless,fearful and restless" negative factors can exacerbate the decline of vigilance level more than those with "upset,hostile and irritable" negative factors.Through the comparison of EEG frequency bands and the paired sample t-test of channels,it is found that most of the channels with no significant difference in each frequency band are FP1,FPZ,FP2,AF3 and AF4.In the group comparison of different degrees of positive emotion and negative emotion,it is found that the most significant difference is in the occipital region.This study verified the influence and difference of miners’ different emotional states on alertness,and further revealed the influence degree and regular characteristics of emotion on alertness from the characteristics of brain activity.At the same time,it provides a new idea for the channel selection of wearable EEG devices.