The invisible force? Opportunities in Sensors, Computer Vision, and Artificial Intelligence for Determining Worker Exertions

Overexertion in manual material handling (MMH) tasks is one of the leading causes of occupational injuries. However, load weight remains one of the most difficult for ergonomics practitioners to measure in the field as it varies greatly across different objects and is often unknown. This talk will provide a brief background on existing techniques before introducing the emerging capabilities of glove sensors, computer vision, and machine learning algorithms for discovering key features that predict worker force exertions. These techniques provide potential tools for ergonomists to overcome the challenge of measuring load weight objectively, an often-critical input for injury risk assessments.

Presenting Speaker

Denny Yu, PhD, CPE is an Associate Professor of Industrial Engineering at Purdue University. He was also a Fulbright Scholar and a 2017-2023 Summer Faculty Fellow at the Air Force Research Laboratory’s 711th Human Performance Wing.

He is a Certified Professional Ergonomist (CPE) and serves on the Board of Directors for the Board of Certification of Professional Ergonomics (BCPE), Foundation for Professional Ergonomics, and the IISE Work Systems Board.

Dr. Yu’s expertise is in applied ergonomics research, specifically in quantitative sensing techniques to assess individual and team behaviors in high workload-dynamic environments. In conducting this work, his team has received the Human Factors Prize (by the Human Factors and Ergonomics Society), National Safety Council Rising Stars of Safety, International Ergonomics Association (IEA)/Tsinghua Award for Collaborative Human Factors and Ergonomics Education, IEA Triennial Outstanding Educators Award, and the Applied Ergonomics Conference/Texas A&M Ergo Center Young Investigator Award