Research On Influencing Factors Of Visual Display Terminal(VDT) Work Fatigue

VDT(Visual Display Terminal,referred to as VDT)operation is a general term for the processing and analysis of data,words,pictures and other information by using computers,electronic instruments,display screens and other visual display terminals.VDT operation has changed the traditional office mode,improved the office efficiency,and has become one of the mainstream office methods.With the popularity of VDT work,some new health problems have gradually emerged,such as visual fatigue,local skeletal muscle fatigue and psychological fatigue.In this paper,Bayesian network is used to study the factors affecting VDT fatigue,with literature statistics,questionnaire survey and Bayesian network research as the core,Bayesian network modeling to analyze the causes of VDT fatigue as the research idea,the following work has been carried out:First of all,this paper summarizes and combs the literature on VDT fatigue and its influencing factors at home and abroad,sums up the causes and mechanisms of fatigue caused by different factors,and makes a systematic review of it.Secondly,the domestic and foreign literatures on the influencing factors of VDT fatigue were statistically analyzed.According to the frequency of influencing factors in the literature,26 influencing factors of VDT fatigue were identified.The 26 factors affecting VDT fatigue were classified into six categories:individual factors,work organization factors,work environment factors,physical properties of VDT desk layout and display,ergonomic factors and psychosocial factors.In view of the above six factors,a questionnaire was designed to investigate the fatigue status of VDT workers,and the sample data were obtained.The reliability and validity of the questionnaire are tested,and the reliability and structural effect of the questionnaire reached a good level.The comprehensive scores of visual fatigue,skeletal muscle fatigue and psychological fatigue were calculated by the method of factor analysis.The non-parametric test was carried out on the sample data,and 20 factors that really affected the fatigue of VDT work in this study were determined.In order to meet the data type requirements of Bayesian networks,the ChiMerge-x~2 algorithm is used to discretize the three fatigue factors.Then the Bayesian network of VDT fatigue is established by using structure learning and parameter learning in the Bayesian modeling software Ge NIe 2.1.In this paper,the 10-fold cross-verification method is used to verify the reliability and accuracy of the Bayesian network model,and the accuracy of the model is up to 85%.Finally,the prediction,diagnosis and sensitivity analysis of VDT fatigue Bayesian network are carried out in Ge NIe 2.1.In the prediction part,taking the workload and daily working time as an example,it is found that when they are in a disadvantageous state respectively,the changes of psychological fatigue and visual fatigue are the greatest.At the same time,it is also found that when two or more factors are in a disadvantageous state,the probability of overall fatigue of VDT work will be greatly improved.Through the diagnosis of Bayesian network,it is found that visual fatigue is the source of skeletal muscle fatigue and psychological fatigue.Reducing visual fatigue can reduce the overall fatigue of VDT work.Through sensitivity analysis,the sensitive factors of VDT work fatigue are obtained,and it is found that when the sensitive factors change to unfavorable state,the probability of fatigue will increase,and the maximum increase is more than 100%.The results of diagnosis and sensitivity analysis showed that the factor of work organization was an important factor affecting the occurrence of VDT work fatigue.Finally,according to the diagnosis and sensitivity analysis,the paper puts forward some suggestions to prevent and improve the fatigue of VDT work.