Development of the Real-time Lifting Assessment tool based on Computer Vision

基于计算机视觉的实时举升评估工具开发

• 批准号: 576741-2022
• 负责人: Kim, EunsikE
• 金额: $ 1.82万
• 依托单位: University of Windsor
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760471
• 关键词: Development; Real; time; Lifting; Assessment

NIOSH lifting equation (RNLE) is the most widely used observational tool to assess the risk of low back pain associated with lifting and lowering tasks in the workplace. Although the RNLE is cost effective, it is time consuming to process and analyze the resulting data. Moreover, it is impossible to detect the risk factors of low back pain via a single application of the RNLE due to the fact that today's manual material handling jobs have evolved from single tasks to multiple and varying tasks. Thus, the purpose of the proposed international collaboration is to develop a robust, non-intrusive, straightforward, computer vision based RNLE assessment tool in order to construct a lifting assessment that performs analyses over prolonged periods. We expect that the result of this project will play an increasingly important role in the improvement of living and working conditions in Canada and Korea.

NIOSH提升方程（RNLE）是评估与工作场所举起和降低任务相关的腰痛风险的最广泛使用的观察工具。尽管RNLE具有成本效益，但处理和分析所得数据很耗时。此外，由于当今的手动材料处理工作已经从单个任务转变为多个任务和不同任务，因此不可能通过单个RNLE的单一应用来检测下背痛的危险因素。因此，拟议的国际合作的目的是开发一种强大的，不受欢迎的，直接的，基于计算机的RNLE评估工具，以构建在长时间内进行分析的提升评估。我们预计该项目的结果将在改善加拿大和韩国的生活和工作条件中发挥越来越重要的作用。