Integration of artificial intelligence and traditional methods for ergonomic risk assessment

Abstract

These approaches are susceptible to variations based on the evaluator's experience and criteria. The adoption of artificial intelligence (AI), through computer vision, inertial sensors, and motion capture systems, offers a tool capable of enhancing accuracy, consistency, and real-time continuous monitoring. This study examines the benefits and drawbacks of both methods in assessing Musculoskeletal Disorders (MSDs), proposing a hybrid model that combines AI with validated techniques like REBA, RULA, and NIOSH, ensuring scientific rigor and practical relevance in actual work settings. From a regulatory standpoint, the global context and the latest U.S. legal framework are reviewed. The European Union leads with Regulation (EU) 2024/1689, which sets binding requirements for high-risk systems, including human oversight, traceability, and data protection. In Asia, ASEAN and Singapore are progressing through ethical guidelines and non-binding national strategies aimed at responsible AI governance. In the U.S., the October 2023 Executive Order was revoked on January 20, 2025, and replaced by Executive Order 14179 – Removing Barriers to American Leadership in Artificial Intelligence, emphasizing innovation and instructing federal agencies to review existing regulations. However, there is currently no comprehensive federal AI law. The order warns that unregulated use of automated tools, without professional validation, can pose legal and technical risks to workers and employers. In conclusion, a hybrid approach remains the most efficient, scientifically sound, and legally justifiable option, as it couples the speed of AI with professional oversight, methodological traceability, and adherence to international standards.

Ähnliche Arbeiten