Presentation
72. Computer Vision Embedded Post-Processing Algorithm on Lifting Risks
SessionPoster Session 2
DescriptionThe primary objective of this research is to refine the application ergonomic assessment by integrating a computer vision algorithm, which outputs the positions of 17 body joint points. We propose a post-processing algorithm designed to calculate the NIOSH lifting index parameters (HM, VM, DM, AM, CM). The NIOSH lifting index is a widely recognized tool for evaluating the potential risk of lifting-related injuries, but current methodologies for obtaining the required data are often manual, subjective, and not conducive to real-time analysis. The pilot project aims to leverage computer vision to capture the dynamics of lifting tasks, automating the evaluation process through computer vision. Utilizing coordinates of 17 body joint points, the algorithm achieved a 90% accuracy rate in classifying the NIOSH lifting index when compared with traditional manual methods. Thereby enhancing the precision, objectivity, and timeliness of ergonomic evaluations.
Event Type
Poster
TimeThursday, September 12th5:30pm - 6:30pm MST
LocationMcArthur Ballroom
Aging
Augmented Cognition
Children's Issues
Communications
Cybersecurity
Education
Environmental Design
General Sessions
Human AI Robot Teaming (AI)
Macroergonomics
Occupational Ergonomics
Student Forum
Surface Transportation
Sustainability
System Development