Tjosvoll Svein O, Seeberg Trine M, Fimland Marius S, Wiggen Øystein, Jahren Silje E
Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, NTNU Norwegian University of Science and Technology, Trondheim, Norway.
Smart Sensor Systems, SINTEF Digital, SINTEF AS, Oslo, Norway.
Ergonomics. 2022 Oct;65(10):1410-1420. doi: 10.1080/00140139.2022.2039410. Epub 2022 Feb 25.
Several professions in industries, such as petroleum, manufacturing, construction, mining, and forestry require prolonged work tasks in awkward postures, increasing workers' risks for musculoskeletal pain and injury. Therefore, we developed and validated a rule-based model for classifying unilateral and bilateral kneeling and squatting based on 15 individuals wearing personal protective equipment and using three wireless triaxial accelerometers. The model provided both high sensitivity and specificity for classifying kneeling (0.98; 0.98) and squatting (0.96; 0.91). Hence, this model has the potential to contribute to increased knowledge of physical work demands and exposure thresholds in working populations with strict occupational safety regulations. Our results indicate that this rule-based model can be applied in a human-factors perspective enabling high-quality quantitative information in the classification of occupational kneeling and squatting, known risk factors for musculoskeletal pain, and sick leave. This study is adapted for working populations wearing personal protective equipment and aimed for long-term measurements in the workplace.
石油、制造、建筑、采矿和林业等行业中的几个职业需要长时间以别扭的姿势工作，这增加了工人患肌肉骨骼疼痛和损伤的风险。因此，我们基于15名穿戴个人防护装备并使用三个无线三轴加速度计的个体，开发并验证了一种基于规则的模型，用于对单侧和双侧跪姿和蹲姿进行分类。该模型在对跪姿（0.98；0.98）和蹲姿（0.96；0.91）进行分类时具有高灵敏度和特异性。因此，该模型有可能有助于增加对有严格职业安全法规的工作人群中体力工作需求和暴露阈值的了解。我们的结果表明，这种基于规则的模型可以从人因学角度应用，在职业跪姿和蹲姿（已知的肌肉骨骼疼痛风险因素）以及病假的分类中提供高质量的定量信息。本研究适用于穿戴个人防护装备的工作人群，并旨在在工作场所进行长期测量。
