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. Practitioner summary: 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.
Keywords: Validation study; accelerometry; human activity recognition; occupational health and safety; physical exposure.