Ergonomic challenges in healthcare: mapping physical load during patient transfers using electromyographic field measurements

医疗保健领域的人体工程学挑战:利用肌电场测量绘制患者转移过程中的身体负荷图

阅读:4

Abstract

PURPOSE: Work-related musculoskeletal disorders are prevalent among healthcare workers. These workers experience high rates of low-back pain; partly due to the high physical demands of patient transfers. Understanding the specific transfer scenarios that contribute to high physical loads is therefore crucial for developing strategies to improve working conditions. METHODS: This study utilized electromyography to measure muscle activity in the erector spinae muscles during patient transfers, performing measurements in real-life hospital settings to identify the physical load associated with different transfer scenarios. Using linear mixed models, the 95th percentile ranks of the normalized root mean square (nRMS) values were analyzed for a range of different patient transfers. RESULTS: The results revealed significant differences in physical load across various patient transfer scenarios. High-load activities included sitting to lying down or lying down to sitting (nRMS 32.7, 95% CI: 28.9-36.6) and lifting the upper body (32.4, 95% CI: 28.8-35.9), while low-load activities such as supporting patients while walking or standing (21.9, 95% CI: 18.6-25.1) and mobilizing in bed (19.9, 95% CI: 16.1-23.8) required less muscle activation. Moderate-load activities included bed to chair transfers (28.1, 95% CI: 24.9-31.3) and lifting the head (26.3, 95% CI: 22.7-29.9). CONCLUSION: Understanding the physical load associated with different patient transfer scenarios allows for better organization of work in healthcare settings. These novel findings emphasize the need for effective task allocation, rotational schedules, and the use of assistive devices to distribute physical load and reduce injury risk.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。