School of Safety & Environmental Engineering, Hunan Institute of Technology, Hengyang City, Hunan Province, China.
Department of Industrial Management, Chung Hua University, Hsin-Chu, Taiwan.
PLoS One. 2018 Nov 16;13(11):e0207283. doi: 10.1371/journal.pone.0207283. eCollection 2018.
Truck pulling is one of the common manual materials handling tasks which contribute to musculoskeletal disorders. The maximum endurance time (MET) for two-handed truck pulling tasks has been rarely discussed in the literature. The objectives of this study were to explore the development of muscular fatigue when performing two-handed pulling task and to establish models to predict the MET. A simulated pallet truck pulling experiment was conducted. Sixteen healthy adults including eight females and eight males participated. The participants pulled a handle simulating that of a pallet truck using two hands until they could not pull any longer under two postures. The forces applied for females and males were 139.65 N and 170.03 N, respectively. The maximum voluntary contractions (MVC) of the pulling strength both before and after the simulated pull were measured. After each trial, both the MET and subjective ratings of muscular fatigue on body segments were recorded. The results showed that posture significantly affected MVC of pull both before and after the trial. It was found that foot/shank of the front leg had higher subjective ratings of muscular fatigue than the other body segments. The MET equations employing both power and logarithmic functions were developed to predict the MET of the two-handed pulling tasks. Predictive models established in this study may be used to assess the MET for two-handed pulling tasks.
卡车装卸是常见的体力搬运作业之一,可能导致肌肉骨骼疾病。双手卡车装卸任务的最大耐力时间(MET)在文献中很少讨论。本研究的目的是探讨执行双手拉货任务时肌肉疲劳的发展,并建立预测 MET 的模型。进行了模拟托盘卡车装卸实验。 16 名健康成年人参与了研究,其中包括 8 名女性和 8 名男性。参与者使用双手拉动一个模拟托盘卡车的手柄,直到他们无法再继续拉动手柄为止,实验中使用了两种姿势。女性和男性的拉力分别为 139.65N 和 170.03N。在模拟拉动前后测量了拉货强度的最大自主收缩(MVC)。每次试验后,记录了 MET 和身体各部位肌肉疲劳的主观评分。结果表明,姿势显著影响了试验前后的 MVC。研究发现,前腿的脚/小腿比其他身体部位有更高的肌肉疲劳主观评分。使用功率和对数函数开发了预测双手拉货任务 MET 的方程。本研究中建立的预测模型可用于评估双手拉货任务的 MET。