Scataglini Sofia, Fontinovo Eugenia, Khafaga Nouran, Khan Muhammad Ubaidullah, Faizan Khan Muhammad, Truijen Steven
4D4ALL Lab, Department of Rehabilitation Sciences and Physiotherapy, Center for Health and Technology (CHaT), Faculty of Medicine and Health Sciences, MOVANT, University of Antwerp, 2000 Antwerpen, Belgium.
Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy.
Sensors (Basel). 2025 Sep 4;25(17):5513. doi: 10.3390/s25175513.
Ergonomic risk assessment is crucial for preventing work-related musculoskeletal disorders (WMSDs), which often arise from repetitive tasks, prolonged sitting, and load handling, leading to absenteeism and increased healthcare costs. Biomechanical risk assessment, such as RULA/REBA, is increasingly being enhanced by camera-based motion capture systems, either marker-based (MBSs) or markerless systems (MCBSs). This systematic review compared MBSs and MCBSs regarding accuracy, validity, and reliability for industrial ergonomic risk analysis. A comprehensive search of PubMed, WoS, ScienceDirect, IEEE Xplore, and PEDro (31 May 2025) identified 898 records; after screening with PICO-based eligibility criteria, 20 quantitative studies were included. Methodological quality was assessed with the COSMIN Risk of Bias tool, synthesized using PRISMA 2020, and graded with EBRO criteria. MBSs showed the highest precision (0.5-1.5 mm error) and reliability (ICC > 0.90) but were limited by cost and laboratory constraints. MCBSs demonstrated moderate-to-high accuracy (5-20 mm error; mean joint-angle error: 2.31° ± 4.00°) and good reliability (ICC > 0.80), with greater practicality in field settings. Several studies reported strong validity for RULA/REBA prediction (accuracy up to 89%, κ = 0.71). In conclusion, MCBSs provide a feasible, scalable alternative to traditional ergonomic assessment, combining reliability with usability and supporting integration into occupational risk prevention.
工效学风险评估对于预防与工作相关的肌肉骨骼疾病(WMSDs)至关重要,这些疾病通常源于重复性任务、长时间坐着和负荷搬运,会导致旷工和医疗成本增加。基于摄像头的运动捕捉系统,无论是基于标记的系统(MBSs)还是无标记系统(MCBSs),都在越来越多地增强生物力学风险评估,如RULA/REBA。本系统综述比较了MBSs和MCBSs在工业工效学风险分析中的准确性、有效性和可靠性。对PubMed、WoS、ScienceDirect、IEEE Xplore和PEDro(截至2025年5月31日)进行全面检索,共识别出898条记录;根据基于PICO的纳入标准进行筛选后,纳入了20项定量研究。使用COSMIN偏倚风险工具评估方法学质量,采用PRISMA 2020进行综合分析,并根据EBRO标准进行分级。MBSs显示出最高的精度(误差为0.5 - 1.5毫米)和可靠性(组内相关系数ICC > 0.90),但受到成本和实验室限制。MCBSs表现出中等至高的准确性(误差为5 - 20毫米;平均关节角度误差:2.31° ± 4.00°)和良好的可靠性(ICC > 0.80),在现场环境中具有更大的实用性。几项研究报告了RULA/REBA预测的强有效性(准确率高达89%,κ = 0.71)。总之,MCBSs为传统工效学评估提供了一种可行、可扩展的替代方案,将可靠性与可用性相结合,并支持融入职业风险预防。