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基于物联网力与肌电传感器的工业环境下手推车推拉安全性的实验分析:与作业人员心理状态和疼痛综合征的关系。

Experimental Analysis of Handcart Pushing and Pulling Safety in an Industrial Environment by Using IoT Force and EMG Sensors: Relationship with Operators' Psychological Status and Pain Syndromes.

机构信息

School of Electrical Engineering, University of Belgrade, Bulevar kralja Aleksandra 73, 11000 Belgrade, Serbia.

Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, 34000 Kragujevac, Serbia.

出版信息

Sensors (Basel). 2022 Oct 1;22(19):7467. doi: 10.3390/s22197467.

Abstract

Non-ergonomic execution of repetitive physical tasks represents a major cause of work-related musculoskeletal disorders (WMSD). This study was focused on the pushing and pulling (P&P) of an industrial handcart (which is a generic physical task present across many industries), with the aim to investigate the dependence of P&P execution on the operators' psychological status and the presence of pain syndromes of the upper limbs and spine. The developed acquisition system integrated two three-axis force sensors (placed on the left and right arm) and six electromyography (EMG) electrodes (placed on the chest, back, and hand flexor muscles). The conducted experiment involved two groups of participants (with and without increased psychological scores and pain syndromes). Ten force parameters (for both left and right side), one EMG parameter (for three different muscles, both left and right side), and two time-domain parameters were extracted from the acquired signals. Data analysis showed intergroup differences in the examined parameters, especially in force integral values and EMG mean absolute values. To the best of our knowledge, this is the first study that evaluated the composite effects of pain syndromes, spine mobility, and psychological status of the participants on the execution of P&P tasks-concluding that they have a significant impact on the P&P task execution and potentially on the risk of WMSD. The future work will be directed towards the development of a personalized risk assessment system by considering more muscle groups, supplementary data derived from operators' poses (extracted with computer vision algorithms), and cognitive parameters (extracted with EEG sensors).

摘要

非人体工程学的重复性体力任务执行是与工作相关的肌肉骨骼疾病(WMSD)的主要原因。本研究专注于推动和拉动(P&P)工业手推车(这是许多行业中普遍存在的通用体力任务),旨在研究 P&P 执行情况对操作人员心理状态以及上肢和脊柱疼痛综合征的依赖性。开发的采集系统集成了两个三轴力传感器(放置在左臂和右臂上)和六个肌电图(EMG)电极(放置在胸部,背部和手部屈肌上)。进行的实验涉及两组参与者(心理评分和疼痛综合征增加的组和没有增加的组)。从获得的信号中提取了十个力参数(左右两侧),一个 EMG 参数(左右两侧的三个不同肌肉)和两个时域参数。数据分析显示,在检查的参数中存在组间差异,特别是在力积分值和 EMG 平均值方面。据我们所知,这是第一项评估疼痛综合征,脊柱活动度以及参与者心理状态对 P&P 任务执行的综合影响的研究,该研究表明它们对 P&P 任务的执行以及潜在的 WMSD 风险有重大影响。未来的工作将致力于通过考虑更多的肌肉群,从操作员姿势(通过计算机视觉算法提取)和认知参数(通过 EEG 传感器提取)得出的补充数据,开发个性化的风险评估系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b1/9572849/159638739d4a/sensors-22-07467-g001.jpg

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