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升降方程（RNLE）是最广泛使用的观察工具，用于评估与工作场所升降任务相关的腰痛风险。虽然RNLE具有成本效益，但处理和分析结果数据非常耗时。此外，不可能通过RNLE的单一应用检测下背痛的风险因素，因为当今的手动材料处理工作已经从单一任务发展到多个不同的任务。因此，拟议的国际合作的目的是开发一个强大的，非侵入性的，简单的，基于计算机视觉的RNLE评估工具，以构建一个提升评估，在很长一段时间内进行分析。我们期待该项目的成果将在改善加拿大和韩国的生活和工作条件方面发挥越来越重要的作用。