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利用非侵入式传感器对恶劣环境下工人的姿势监测和矫正练习:算法开发与验证。

Posture Monitoring and Correction Exercises for Workers in Hostile Environments Utilizing Non-Invasive Sensors: Algorithm Development and Validation.

机构信息

School of Electrical Engineering, Computing, and Mathematical Sciences, Curtin University, Bentley, WA 6102, Australia.

School of Allied Health, Curtin University, Bentley, WA 6102, Australia.

出版信息

Sensors (Basel). 2022 Dec 8;22(24):9618. doi: 10.3390/s22249618.

DOI:10.3390/s22249618
PMID:36559987
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9781722/
Abstract

Personal protective equipment (PPE) is an essential key factor in standardizing safety within the workplace. Harsh working environments with long working hours can cause stress on the human body that may lead to musculoskeletal disorder (MSD). MSD refers to injuries that impact the muscles, nerves, joints, and many other human body areas. Most work-related MSD results from hazardous manual tasks involving repetitive, sustained force, or repetitive movements in awkward postures. This paper presents collaborative research from the School of Electrical Engineering and School of Allied Health at Curtin University. The main objective was to develop a framework for posture correction exercises for workers in hostile environments, utilizing inertial measurement units (IMU). The developed system uses IMUs to record the head, back, and pelvis movements of a healthy participant without MSD and determine the range of motion of each joint. A simulation was developed to analyze the participant's posture to determine whether the posture present would pose an increased risk of MSD with limits to a range of movement set based on the literature. When compared to measurements made by a goniometer, the body movement recorded 94% accuracy and the wrist movement recorded 96% accuracy.

摘要

个人防护设备 (PPE) 是标准化工作场所安全的关键因素。恶劣的工作环境和长时间的工作会给人体带来压力,从而导致肌肉骨骼疾病 (MSD)。MSD 是指影响肌肉、神经、关节和许多其他人体部位的伤害。大多数与工作相关的 MSD 是由于涉及重复性、持续力或在不自然姿势下重复运动的危险手动任务引起的。本文介绍了科廷大学电气工程学院和联合健康学院的合作研究。主要目标是利用惯性测量单元 (IMU) 为恶劣环境中的工人开发一种姿势矫正练习框架。该系统使用 IMU 记录无 MSD 的健康参与者的头部、背部和骨盆运动,并确定每个关节的运动范围。开发了一个模拟来分析参与者的姿势,以确定当前的姿势是否会增加 MSD 的风险,并根据文献将运动范围限制在设定的范围内。与角度计的测量结果相比,身体运动的记录准确率为 94%,手腕运动的记录准确率为 96%。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/c9fa4ef86c7d/sensors-22-09618-g020.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/23b5c20c134d/sensors-22-09618-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/ba43709831cb/sensors-22-09618-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/87818ecf0277/sensors-22-09618-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/36295728111f/sensors-22-09618-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/f69058661c4c/sensors-22-09618-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/38237e1bfa7d/sensors-22-09618-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/84ca/9781722/7e1a2e1b48cd/sensors-22-09618-g018.jpg
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