Assistance Systems and Medical Device Technology, Carl Von Ossietzky University of Oldenburg, Ammerländer Heerstraße 140, 26129, Oldenburg, Germany.
Geriatric Medicine, Carl Von Ossietzky University of Oldenburg, 26129, Oldenburg, Germany.
Sci Rep. 2022 May 23;12(1):8644. doi: 10.1038/s41598-022-12632-4.
Manual patient handling is one of the most significant challenges leading to musculoskeletal burden among healthcare workers. Traditional working techniques could be enhanced by innovations that can be individually adapted to the physical capacity of nurses. We evaluated the use of a robotic system providing physical relief by collaboratively assisting nurses in manual patient handling tasks. By quantifying kinetic and muscle activity data, it was possible to distinguish two kinds of movement patterns. Highly asymmetric postures and movements corresponded to distinct extremes in lower limb and spine muscle activity data. The use of collaborative robotics significantly reduced maximum force exertion in the caregiving process by up to 51%. Lateral flexion and torsion of the trunk were reduced by up to 54% and 87%, respectively, leading to a significant reduction in mean spine muscle activity of up to 55%. These findings indicate the feasibility of collaborative robot-assisted patient handling and emphasize the need for future individual intervention programs to prevent physical burden in care.
手动搬运患者是导致医护人员肌肉骨骼负担的最主要挑战之一。通过创新,可以将传统的工作技术提升到可以根据护士的身体能力进行个性化调整的水平。我们评估了使用机器人系统通过协作协助护士进行手动搬运患者任务来提供身体缓解的效果。通过量化运动学和肌肉活动数据,我们可以区分两种运动模式。高度不对称的姿势和运动对应于下肢和脊柱肌肉活动数据的明显极值。使用协作机器人可以使护理过程中的最大力施加减少高达 51%。躯干的侧向弯曲和扭转分别减少了高达 54%和 87%,从而导致脊柱肌肉活动的平均水平显著降低了高达 55%。这些发现表明协作机器人辅助患者搬运的可行性,并强调需要未来的个性化干预计划来预防护理中的身体负担。