Lift It Up Right
A Recommender System for Safer Lifting Postures
Gaetano Dibenedetto (Università degli Studi di Bari Aldo Moro)
Pasquale Lops (Università degli Studi di Bari Aldo Moro)
Marco Polignano (Università degli Studi di Bari Aldo Moro)
H. Torkamaan (TU Delft - System Engineering)
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Abstract
Work-related musculoskeletal disorders, often caused by poor lifting posture and unsafe manual handling, continue to pose a significant threat to worker health and safety. This paper presents a health recommender system designed to prevent injury by assessing and correcting posture for lifting techniques. Leveraging monocular video input, our method estimates key ergonomic parameters to compute the Lifting Index based on the Revised NIOSH Lifting Equation. When the computed Lifting Index exceeds a predefined safety threshold, the system automatically generates graphical and textual recommendations to guide the worker towards safer postural strategies. This safety-aware recommender system provides interpretable and actionable feedback without requiring wearable sensors or multi-camera setups, making it suitable for deployment in real-world workplace environments. By integrating ergonomics with recommender system design, we contribute to a new class of context-aware, safety-oriented recommendation technologies tailored for occupational health.
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File under embargo until 07-03-2026