ME-WARD: A multimodal ergonomic analysis tool for musculoskeletal risk assessment from inertial and video data in working plac
This study presents ME-WARD (Multimodal Ergonomic Workplace Assessment and Risk from Data), a novel system for ergonomic assessment and musculoskeletal risk evaluation that implements the Rapid Upper Limb Assessment (RULA) method. ME-WARD is designed to process joint angle data from motion capture systems, including inertial measurement unit (IMU)-based setups, and deep learning human body pose tracking models. The tool's flexibility enables ergonomic risk assessment using any system capable of reliably measuring joint angles, extending the applicability of RULA beyond proprietary setups. To validate its performance, the tool was tested in an industrial setting during the assembly of conveyor belts, which involved high-risk tasks such as inserting rods and pushing conveyor belt components. The experiments leveraged gold standard IMU systems alongside a state-of-the-art monocular 3D pose estimation system. The results confirmed that ME-WARD produces reliable RULA scores that closely align with IMU-derived metrics for flexion-dominated movements and comparable performance with the monocular system, despite limitations in tracking lateral and rotational motions. This work highlights the potential of integrating multiple motion capture technologies into a unified and accessible ergonomic assessment pipeline. By supporting diverse input sources, including low-cost video-based systems, the proposed multimodal approach offers a scalable, cost-effective solution for ergonomic assessments, paving the way for broader adoption in resource-constrained industrial environments.
Code (0)
등록된 구현이 없습니다.
Tasks
3D Pose EstimationPose TrackingSimilar Papers 제목 키워드 기반
Analysis of Ergonomic Risk in University Study Environments During Class Days
This study investigates the ergonomic impact of university seating on students’ musculoskeletal health, focusing on lumbar muscle fatigue during prolonged study sessions. Using surface electromyography (sEMG) with BiTali…
Analysis of Ergonomic Risk in University Study Environments During Class Days
This study investigates the ergonomic impact of university seating on students’ musculoskeletal health, focusing on lumbar muscle fatigue during prolonged study sessions. Using surface electromyography (sEMG) with BiTali…
Ergonomic Assessment of Work Activities for an Industrial-oriented Wrist Exoskeleton
Musculoskeletal disorders (MSD) are the most common cause of work-related injuries and lost production involving approximately 1.7 billion people worldwide and mainly affect low back (more than 50%) and upper limbs (more…
Privacy-Preserving Industrial Ergonomics: mmWave-Based Automated REBA Scoring and Pose Estimation
Work-related Musculoskeletal Disorders (WMSDs) require continuous ergonomic assessments. While Rapid Entire Body Assessment (REBA) is a gold-standard observation tool, manual monitoring is labor-intensive, and vision-bas…
Multi-Task LearningPose EstimationPoint CloudsEnabling Privacy-Aware AI-Based Ergonomic Analysis
Musculoskeletal disorders (MSDs) are a leading cause of injury and productivity loss in the manufacturing industry, incurring substantial economic costs. Ergonomic assessments can mitigate these risks by identifying work…
Keypoint DetectionPose Estimation