This PFI: AIR Technology Translation project focuses on translating fundamental research findings in computer vision-based posture classification and pose estimation to fill the need for rapid and easy postural ergonomic risk assessment. This is applicable for occupational workers involved in physically demanding labor with awkward working postures, and who consequently suffer from work-related musculoskeletal disorders (WMSDs). The translated technology is important because it enables practitioners to identify potential WMSD risks in advance of actual injury, thus minimizing the potential injury risks. Given the massive number of WMSD cases (e.g., over 360,000 cases per year) and huge associated workers' compensation costs (e.g., over $14.2 billion per year) in the U.S., this research contributes to the development and maintenance of a safe, healthy, and productive workforce, which will have an ameliorative impact on society. The project will result in a fully-functioning software prototype of vision-based ergonomic risk assessment, which has the following unique features: rapid (e.g., near real-time to process video frames), easy (e.g., no training to assess ergonomic risks is needed), and automated (e.g., no need for manual risk assessment). These features allow practitioners to save a significant amount of time and effort on ergonomic risk assessment, when compared to the current manual observation-based risk assessment in the ergonomic industry.
This project addresses the following technology gaps as it translates from research discovery toward commercial application. First, a tracking-based pose estimation, which is a fundamental component to estimate posture severity, provides fast processing of video frames but needs to be robust without target loss, which can happen due to frequent occlusions and environmental noises in real worksites. In this research, the tracking-based approach will be integrated with a detection-based pose estimation along with the adoptions of different features like spatial information and reference frames from just processed ones. Once the prototype is developed, it will be tested in diverse real worksites such as manufacturing assembly lines to ensure its robustness and usability. In addition, personnel involved in this project, including graduate and undergraduate students, will receive entrepreneurship experience through interaction with ergonomic and business experts and potential customers (e.g., customer interaction, market study, and field validation) as well as engagement in the activities offered from the University of Michigan Center for Entrepreneurship (e.g., entrepreneurship classes and workshops).
The project engages Humantech, the largest ergonomic consulting firm in North America, UAW (United Automobile, Aerospace and Agricultural Implement workers of America), and a venture capitalist, to provide real-world test environment and guide commercialization aspects in this technology translation effort from research findings toward commercial reality.
