Improvement And Sensitivity Study Of Rapid Systemic Assessment Method (REBA) Based On Fuzzy Logi

As a large manufacturing country,our country has abundant labor force and perfect industrial system.However,workers suffer from work-related musculoskeletal disorders(WMSDs)due to long-term adverse factors such as working posture and repetitive operation,resulting in a decline in workers’ health status and great losses for enterprises.How to reduce workers’ working WMSDs has become a key issue concerned by all sectors of society.Rapid Entire Body Assessment(REBA),as one of the methods of job posture assessment,is often used to assess the MSD risk level of workers in various fields.However,as a discrete evaluation system,the sudden jump of the score often occurs when the boundary Angle is determined,which leads to a large error in the evaluation results.Based on the Rapid Entire Body Assessment(REBA)guidelines,this paper aims to further improve the accuracy of ergonomic assessment,study the sensitivity of Rapid Entire Body Assessment(REBA)and the identification of sensitive and insensitive postural areas,so that ergonomic practitioners can be aware of the sensitive and insensitive areas in postural assessment.The fuzzy logic method was used to optimize the boundary Angle determination of REBA evaluation system,and the trapezoidal function was used to blur the joint Angle,load and muscle use.The intermediate score and final score of REBA were fuzzy expressed by trigonometric function,and the center of gravity average method was used to deblur.In this paper,furniture manufacturing industry personnel are selected as the research object,and the REBA score is visualized by MATLAB to obtain the data of workers in the process of operation for analysis.Kinect was used to photograph the representative working posture of workers,and the coordinates and angles of key nodes were obtained through programming software such as Python and Visual Studio.Compared with the subjective scores of workers,Pearson correlation coefficient was used to verify the correlation.The results verified that the fuzzy logic-based REBA evaluation method had high accuracy,which could not only reflect the score changes caused by the changes of special joint angles,but also had a high correlation coefficient with the score of the Self-Rating Fatigue Symptom Scale(r=0.956),which could better reflect the real situation of the subjects.