Suppr超能文献

可穿戴心率感应和基于关键功率的全身疲劳现场监测。

Wearable heart rate sensing and critical power-based whole-body fatigue monitoring in the field.

机构信息

Hole School of Construction Engineering and Management, Dept. of Civil and Environmental Engineering, Univ. of Alberta, 9211-116 St., Donadeo Innovation Centre for Engineering, Edmonton, AB, T6G2H5, Canada.

Tishman Construction Management Program, Dept. of Civil and Environmental Engineering, Univ. of Michigan, 2350 Hayward St., G.G Brown Bldg., Ann Arbor, MI, 48109, USA.

出版信息

Appl Ergon. 2024 Nov;121:104358. doi: 10.1016/j.apergo.2024.104358. Epub 2024 Aug 3.

Abstract

Whole-body fatigue (WBF) presents a concerning risk to construction workers, which can impact function and ultimately lead to accidents and diminished productivity. This study proposes a new WBF monitoring technique by applying the Critical Power (CP) model, a bioenergetic model, with a wrist-worn heart rate sensor. The authors modified the CP model to calculate WBF from the percentage of heart rate reserve (%HRR) and generated a personalized model via WBF perception surveys. Data were collected for two days from 33 workers at four construction sites. The results showed that the proposed technique can monitor field workers' perceived WBF with a mean absolute error of 12.8% and Spearman correlation coefficient of 0.83. This study, therefore, demonstrates the viability of wearable WBF monitoring on construction sites to support programs aimed at improving workplace safety and productivity.

摘要

全身疲劳(WBF)对建筑工人构成了严重的风险,可能影响其功能,最终导致事故和生产力下降。本研究提出了一种新的 WBF 监测技术,通过应用关键功率(CP)模型,一种生物能量模型,结合腕戴式心率传感器。作者对 CP 模型进行了修改,以计算 WBF 与心率储备百分比(%HRR),并通过 WBF 感知调查生成个性化模型。从四个建筑工地的 33 名工人那里收集了两天的数据。结果表明,该技术可以用 12.8%的平均绝对误差和 0.83 的斯皮尔曼相关系数来监测现场工人的感知 WBF。因此,本研究证明了在建筑工地使用可穿戴式 WBF 监测的可行性,以支持旨在提高工作场所安全性和生产力的计划。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验