A Work-Related Musculoskeletal Disorders (WMSDs) Risk-Assessment System Using a Single-View Pose Estimation Model

We present a camera‐based human body parameters measurement approach and develop a human postural assessment system. The approach combines the conventional contact measurement method and the non‐contact measurement method to overcome some shortcomings in terms of time, expense, and professionalism in early methods. The entire measurement system consists of a computer, a high‐definition camera, and the sticky points that are applied to the participant's body before the measurement. The camera captures the triple view image of human body. Then the human body outline and the joint points of the human skeleton ere extracted to locate the bone feature points. Finally, measurements and extractions of the human parameters are made. Experimental results demonstrate that the global postural assessment system provides quantitative guidance for human postural evaluation, and it completely changing how human postural is evaluated. The postural assessment system is significance for early diagnosis of diseases and medical rehabilitation treatment.This article is protected by copyright. All rights reserved.

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“…proposed an assessment of head and neck postural. Kown et al [17]. proposed a work postural assessment of workers to discriminate disease risk.…”

Section: Image Processing Image Processingmentioning

confidence: 99%

Measurement of human body parameters for human postural assessment via single camera

Yan

Zhou

Chen

et al. 2023

Journal of Biophotonics

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“…Human key point recognition Proposing a semiautomatic RULA evaluation software based on Microsoft Kinect v2 depth camera [15] Kinect v2 Depth image acquisition and segmentation A skeleton less holistic pose analysis system is proposed to accurately predict operational pose limb angles from a single depth image [16] RGB-D camera 2D pose estimation based on CEPARA A PAS-oriented holistic pose acquisition and ergonomic risk analysis model is proposed for developing a smartphone-based and workplace-based WMSDs risk assessment system [17] RGB-D camera 2D pose estimation A proposed vision-based real-time RULA method for scoring RULA levels of individual images captured by ordinary RGB cameras [18] RGB-D camera 3D pose estimation based on 3DMPPE Te body angle reliability decision making (BARD) method is proposed to calculate the most reliable body bending angle [2] vision method has a wider application value. Using a single RGB camera for image recognition in human-machine risk assessment has become a current research trend [21][22][23]. Li et al [18] proposed a real-time estimation method of RULA based on a deep neural network for two-dimensional joint pose, which frst uses 2D action recognition to identify the skeleton points of the human body before using a 3D neural network to identify the positions and vectors of each joint.…”

Section: Kinect V2mentioning

confidence: 99%

Posture Risk Assessment and Workload Estimation for Material Handling by Computer Vision

Wang,

Chen

et al. 2023

International Journal of Intelligent Systems

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Workers in material handling tasks often suffer from work-related musculoskeletal disorders (WMSDs) caused by inaccurate work postures or the lifting of excessively heavy loads. Therefore, effective ergonomic assessment of workers is needed to improve worker productivity while reducing the risk of musculoskeletal disorders. This paper proposes a noninvasive method for evaluating posture risks and load analysis in manual material handling tasks. The study focuses on three main aspects: first, using 3D pose recognition technology to extract the 3D coordinates and joint angles of the human body. Second, the REBA method was improved by using fuzzy logic theory to more effectively capture the slow transition features of continuous movement by humans without abruptly altering risk scores, as well as to increase the accuracy and consistency of posture risk evaluation. Third, joint torque and workloads were estimated using biomechanical calculations by integrating pressure insoles and 3D joint coordinate data. Experiments show that this method can effectively evaluate posture risks and workloads in manual material handling tasks, with a correlation coefficient of 0.817 ( p < 0.01 ) between fuzzy logic REBA and REBA and an error rate of 15% in estimating workloads of eight joints. This method can help reduce occupational health risks for workers and industries and improve work efficiency.

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“…Such a lack has the potential to reduce the product/machinery quality and its safety during usage [13,14]. Moreover, damages due to exposure to awkward work environments negatively impact the workers' employment, causing a significant social problem [15,16].…”

Section: Introductionmentioning

confidence: 99%

Development of a New Procedure for Evaluating Working Postures: An Application in a Manufacturing Company

Gattamelata

Fargnoli

2022

IJERPH

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Musculoskeletal diseases represent a constant phenomenon in occupational health and safety (OHS) despite the large effort at governmental and technical levels. In the industrial context, numerous studies have dealt with the evaluation of the physical demand of workers. Moreover, numerous studies have investigated the problem, providing tools for ergonomics analysis. However, practical approaches aimed at integrating ergonomics issues in risk assessment activities are still scarce. To reduce such a gap, the current study proposes a procedure for the evaluation of the static working postures of workers to be included in the risk assessment activities. Such an approach is based on the ISO 11226 standard, providing a practical checklist that can be used both at the workstation’s design stage and during risk assessment activities. Its effectiveness was verified through a case study at a manufacturing company. The results achieved showed that as well as the non-conformity of the workstations’ design, the lack of training of the operators on how to maintain a neutral posture while working can also lead to awkward postures of the trunk and head. Additionally, the proposed methodology allowed us to verify the correctness of each workstation based on the physical characteristics of the workers, providing a useful guideline for the company managers on how to properly assign working tasks.

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A Work-Related Musculoskeletal Disorders (WMSDs) Risk-Assessment System Using a Single-View Pose Estimation Model

Cited by 6 publications

References 45 publications

Measurement of human body parameters for human postural assessment via single camera

Measurement of human body parameters for human postural assessment via single camera

Posture Risk Assessment and Workload Estimation for Material Handling by Computer Vision

Development of a New Procedure for Evaluating Working Postures: An Application in a Manufacturing Company

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