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An optimal sampling approach to modelling whole-body vibration exposure in all-terrain vehicle driving

机译:在全地形车辆驾驶中模拟全身振动暴露的最佳采样方法

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摘要

Exposure to whole-body vibration (WBV) presents an occupational health risk and several safety standards obligate to measure WBV. The high cost of direct measurements in large epidemiological studies raises the question of the optimal sampling for estimating WBV exposures given by a large variation in exposure levels in real worksites. This paper presents a new approach to addressing this problem. A daily exposure to WBV was recorded for 9-24days among 48 all-terrain vehicle drivers. Four data-sets based on root mean squared recordings were obtained from the measurement. The data were modelled using semi-variogram with spectrum analysis and the optimal sampling scheme was derived. The optimum sampling period was 140min apart. The result was verified and validated in terms of its accuracy and statistical power. Recordings of two to three hours are probably needed to get a sufficiently unbiased daily WBV exposure estimate in real worksites. The developed model is general enough that is applicable to other cumulative exposures or biosignals.Practitioner Summary: Exposure to whole-body vibration (WBV) presents an occupational health risk and safety standards obligate to measure WBV. However, direct measurements can be expensive. This paper presents a new approach to addressing this problem. The developed model is general enough that is applicable to other cumulative exposures or biosignals.
机译:暴露于全身振动(WBV)中会产生职业健康风险,因此有几种安全标准必须测量WBV。大型流行病学研究中直接测量的高昂成本提出了一个问题,即在实际工地中暴露水平的巨大差异下,用于估计WBV暴露的最佳采样问题。本文提出了一种解决该问题的新方法。在48位全地形车辆驾驶员中,每天记录WBV暴露9-24天。从测量中获得了基于均方根记录的四个数据集。使用具有频谱分析的半变异函数对数据进行建模,并得出最佳采样方案。最佳采样间隔为140分钟。结果的准确性和统计功效得到了验证和验证。为了在实际工地中获得足够公正的每日WBV暴露估计,可能需要记录两到三个小时。开发的模型足够通用,适用于其他累积暴露量或生物信号。从业者摘要:暴露于全身振动(WBV)中存在职业健康风险和安全标准,必须测量WBV。但是,直接测量可能会很昂贵。本文提出了一种解决该问题的新方法。开发的模型足够通用,适用于其他累积暴露量或生物信号。

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