| For a long time,the coal industry has been an important pillar of China’s energy production.In recent years,with the rapid development of the coal industry,China’s coal mine safety management has achieved significant results,however,serious accidents have not been eliminated,and larger accidents occur from time to time.Studies and surveys have shown that human unsafe behaviors and human errors are the main and direct causes of accidents,while situation awareness,such as executive functions,working memory,attention,and information processing speed are important protections for safety work.Therefore,from the perspective of brain science,it is of great theoretical significance and practical value to investigate the inner cognitive neural mechanism of situation awareness-unsafe behavior/human error of coal miners,to effectively reduce the error rate and injury rate of coal miners,to fully implement the precise screening of "human hazards",to achieve all-round risk pre-control,to shift the gate forward,and to effectively improve coal mine safety management.From the perspective of integrating safety science and cognitive neuroscience,this study built the full elements model of situation awareness of coal miners;took the brain functional connectivity of coal miners as the research object,based on the fNIRS brain imaging experimental platform,integrated safety science and cognitive neuroscience research methods,and two experiments were conducted on coal miners of Shaanxi Coal Group H CompanyExperiment 1:characterization of functional brain connectivity in coal miners with human error propensity;Experiment 2:effects of shift work on brain function connectivity in coal miners;a deep learning-based situation awareness classification recognition model for coal miners was constructed based on the brain functional connectivity feature data of coal miners collected in Experiment 1 and Experiment 2.The main findings are summarized as follows:(1)The full elements model of situation awareness of coal miners was constructed.Based on the dynamic decision-making situation awareness model,the SOR model of human behavior and the brain information processing theory,this model is divided into three modules:stimulus,organism and response.Environment factors belong to the stimulus module,which is the input layer of information.Situation awareness,cognitive function and individual factors together constitute the organism module.Among them,based on perception,situation awareness is the information receptor and cognitive function is the brain information processor.Cognitive function is the neurophysiological manifestation of situation awareness.Individual factors are important influences on situation awareness and cognitive function.The response module is the unsafe behavior/human factor output layer,which is the information effector.When there is an adverse change in any subfactor in environment factors or individual factors,the individual perceptual ability will be affected and the situation awareness will subsequently decline or fail,thus triggering a decline in individual cognitive function and leading to unsafe behavior/human factors failures.In addition,the individual’s unsafe behavior/human factor failures will also feedback to the environment factors.(2)The brain functional connectivity characteristics of coal miners with human error propensity were uncovered a fNIRS brain imaging experimental platform was utilized to collect the resting-state data of 106 coal miners.Pearson correlation coefficient analysis,brain network analysis and two-sample t-test were used to quantify the brain functional connectivity of coal miners with accident-prone tendencies or not.It was found that the brain functional connectivity of coal miners with human error propensity was characterized by significant differences between their frontal,orbitofrontal and Broca’s triangle brain functional connectivity and that of the general coal miners;and their brain networks in the dorsolateral prefrontal cortex were significantly different from those of the general coal miners in terms of clustering coefficient,local nodal efficiency and global nodal efficiency.The functional brain connectivity features described above indicate that the personal traits of coal miners with human error tendency are depression,impulsivity,high cognitive load and weak attentional control,reactivity,executive ability,emotional stability and working memory ability.The results of Experiment 1 show that the fNIRS resting-state functional connectivity research approach can reveal the neurophysiological characteristics of quantifying the brain functional connectivity of coal miners with human error propensity,which provides important technical support and data reference for modern coal enterprises to achieve scientific and accurate identification of coal miners with human error propensity.(3)The effects of shift work on the functional connectivity of coal miners were clarified.Based on the fNIRS brain imaging experimental platform,resting state data were collected from 54 coal miners in the morning,afternoon,and night shifts before and after work to evaluate their cognitive function status.The results showed that the cognitive functions of coal miners in all morning,afternoon,and night shifts were significantly different before and after work;among them,the difference in functional connectivity was the largest in the morning shift,followed by the afternoon shift,and the smallest in the night shift;compared with the pre-shift,the post-shift functional connectivity of coal miners in the morning and afternoon shifts was significantly lower;while the situation in the night shift was the opposite of the morning and afternoon shifts;all the pre-shift and post-shift functional connectivity in all three shifts state prefrontal cortex resting-state brain functional networks had small-world properties,with significant differences in betweenness centrality and local nodal efficiency in prefrontal cortex between morning and night shift coal miners.The functional brain connectivity features described above indicate that shift coal miners with lower levels of education had lower cognitive function;divorced or widowed shift coal miners had lower cognitive ability;morning and afternoon shift coal miners were more likely to have lower cognitive function at the end of work such as decreased attention,decreased multitasking,decreased emotional control,fatigue and sleepiness with a significant decrease in brain network information conversion efficiency;morning shift shift The multitasking ability of coal miners significantly decreased at the end of work;the emotional control ability of coal miners on night shift significantly decreased at the end of work.The results of Experiment 2 show that the fNIRS resting-state functional connectivity research approach can quantify the effects of working different shifts of morning,afternoon and night shifts on the neurophysiology of brain functional connectivity in coal miners from the perspective of cognitive neuroscience.It provides an important quantitative index and analytical basis for further improving the rationality of shift system and safeguarding the physical and mental health of coal miners.(4)A deep learning-based classification and recognition model for coal miners’ situation awareness was constructed.Based on the brain functional connectivity feature data collected from coal miners in Experiment 1 and Experiment 2,four SVM classification recognition models were constructed to detect the situation awareness of coal miners under different conditions by preferentially selecting brain functional network features.The results showed that the SVM classifier had an accuracy of 84.21%in recognizing the situation awareness of coal miners with human error tendency;97.06%in recognizing the situation awareness of coal miners before and after the morning shift;83.33%in recognizing the situation awareness of coal miners before and after the lunch shift;and 83.33%in recognizing the situation awareness of coal miners before and after the evening shift.The results provide important technical support and quantitative data reference for modern coal mining enterprises to achieve scientific and precise coal miners’ individual situation awareness ranking and detection and provide the government with new quantitative ideas for coal mine safety management and public safety management,and further promotes the precise and scientific development of China’s coal mine supervision and regulation.In conclusion,this study explored the intrinsic cognitive neural mechanisms of coal miners’situational awareness-unsafe behavior/human errors based on fNIRS brain imaging technology,further revealing the intrinsic mechanisms and characteristics of coal miners’ unsafe behaviors from the perspective of cross-fertilization between safety science and cognitive neuroscience,and providing an important data basis and decision reference for quantitative detection of coal miners’ accident-prone tendencies. |
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