Real-Time Ergonomic Assessment with Fuzzy Logic and RGB-D Sensors

The integration of the Rapid Entire Body Assessment (REBA) method with fuzzy logic and RGB-D sensing technology (Kinect v1) enables greater precision and objectivity in identifying postural risks within occupational environments. This study demonstrates the effectiveness of a fuzzy system for ergonomic risk assessment in a sample of 24 workers engaged in the assembly of denim trousers. The average age of the participants from the textile sector was 27.4 years (SD ± 12.4). The proposed methodology combined the traditional REBA framework with fuzzy inference systems and real-time postural tracking via Kinect v1. Among the 24 cases assessed, 38% of workers reported no musculoskeletal discomfort, 25% reported dorsal pain, 13% experienced lower back pain, 13% reported discomfort in the neck, upper and lower limbs, and 13% also reported hand discomfort. Although statistically significant differences (p < 0.05) were found between the manual REBA scores and those generated by the fuzzy system, the proposed method is considered a complementary tool rather than a replacement for manual assessment. The use of Kinect as a non-invasive motion tracking device allowed for real-time data acquisition without interfering with task performance, offering a significant advantage over manual goniometric measurements, which are prone to parallax error, evaluator variability, and limitations in dynamic tasks.