ABSTRACT

The global construction industry suffers from poor health and safety records, with workers facing high risks of fatigue, injury, and even death. Musculoskeletal disorders (MSDs) are a significant concern, exacerbated by an aging workforce in regions like Hong Kong. Effective management of MSD risks is essential for maintaining a healthy and productive workforce. While many studies have focused on monitoring awkward postures, major risk factors like heavy material handling and repetitive tasks remain under-assessed. This study aims to evaluate MSD risks from these factors using computer vision and wearable insole technology to monitor loads and repetitions. By employing a multi-modal learning approach, this project seeks to enhance the accuracy of MSD risk assessments in real construction environments, facilitating data-driven strategies for prevention.

SPEAKER

Dr. Yantao Yu is an Assistant Professor in the Department of Civil and Environmental Engineering at The Hong Kong University of Science and Technology (HKUST) and serves as the director of the Human-Centered Intelligent Construction Lab. Her research focuses on advancing information technologies and robotics in construction management. Her areas of interest include construction robots, construction safety, and digital twin techniques.

Highlights