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Project # 28
POSTURE: Posture Observation System for Task-based User Risk Evaluation
| Team Lead: | Md Muhtasim Sarker |
| Other Team Members: | Eshwara Prasad Sridhar | Ansal Mohammed Abdul Khalam Azad |
| Faculty Advisor(s): | Dr. Mahmudur Rahman |
| Department: | IMSE |
| Project Type: | Other Undergraduate |
| Title: | POSTURE: Posture Observation System for Task-based User Risk Evaluation |
| Abstract: | Work-related musculoskeletal injuries remain a major concern in industrial and service environments. Ergonomic risk is commonly assessed using tools such as REBA, RULA, and the NIOSH Lifting Equation. However, manual scoring is time-consuming, requires trained evaluators, and can vary between raters. This limits consistent screening and early intervention. This study presents a vision-based system that automates ergonomic risk assessment while preserving alignment with established scoring methods. Three synchronized cameras capture worker movement during lifting, overhead placement, and screwdriving tasks. Markerless pose estimation tracks body joints, and joint angles are mapped directly to standard ergonomic scoring rules. Task inputs, such as load weight, are entered as fixed parameters. The system records posture data and score components frame-by-frame to maintain traceability. In addition to numerical scores, a local large language model and a vision language model generate clear explanations that link to the factors driving the score. Preliminary results show consistent scoring patterns across tasks and strong agreement with expert evaluations. This approach improves repeatability, reduces evaluation time, and supports transparent documentation. It provides a practical tool for early risk detection and informed decision-making in workplace safety management. |
| Poster: | View Poster #28 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |