• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.117-122
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• 2022

This paper proposes a method for evaluating the work of manufacturing workers using MediaPipe as a risk factor for musculoskeletal diseases. Recently, musculoskeletal disorders (MSDs) caused by repeated working attitudes in industrial sites have emerged as one of the biggest problems in the industrial health field while increasing public interest. The Korea Occupational Safety and Health Agency presents tools such as NIOSH Lifting Equations (NIOSH), OWAS (Ovako Working-posture Analysis System), Rapid Upper Limb Assessment (RULA), and Rapid Entertainment Assessment (REBA) as ways to quantitatively calculate the risk of musculoskeletal diseases that can occur due to workers' repeated working attitudes. To compensate for these shortcomings, the system proposed in this study obtains the position of the joint by estimating the posture of the worker using the posture estimation learning model of MediaPipe. The position of the joint is calculated using inverse kinetics to obtain an angle and substitute it into the REBA equation to calculate the load level of the working posture. The calculated result was compared to the expert's image-based REBA evaluation result, and if there was a result with a large error, feedback was conducted with the expert again.

• Journal of Korean Society of Forest Science
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• v.110 no.2
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• pp.210-216
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• 2021

Musculoskeletal disorders affect workers' safety in most industries, and forest operations are classified as a musculoskeletal burden according to the Occupational Safety and Health Act in South Korea. In particular, felling and delimbing operations are mainly conducted by manpower, and then, it is necessary to evaluate ergonomic risk assessment for safety of felling and delimbing workers. Three ergonomic risk assessment methods, such as Ovako Working posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA), are available for assessing exposure to risk factors associated with timber harvesting operations. Here, three ergonomic risk assessment methods were applied to examine ergonomic risk assessments in chainsaw felling and delimbing operations. Additionally, exposure to risk factors in each method was analyzed to propose an optimal working posture in felling and delimbing operations. The risk levels of these operations were evaluated to be highest in the RULA method, followed by the OWAS and REBA methods, and most of the exposed working postures were examined with a low-risk level of two and three without requiring any immediate working posture changes. However, two significant working postures, including the bending posture of the waist and leg in felling operation and standing posture on the fallen trees in delimbing operation, were assessed as the high-risk level and needed immediate working posture changes. Low-risk work levels were examined in the squatting posture for felling operation and the straightened posture of the waist and leg for delimbing operation. Moreover, the slope in felling operation and the tree height in delimbing operation significantly affected risk level assessment of working posture. Therefore, our study supports that felling and delimbing workers must operate with low-risk working postures for safety.