Suppr超能文献

基于惯性测量单元传感器的高空预坠检测。

Detection of Pre-Impact Falls from Heights Using an Inertial Measurement Unit Sensor.

机构信息

Department of Biomedical Engineering, Yonsei University, Wonju 26493, Korea.

出版信息

Sensors (Basel). 2020 Sep 20;20(18):5388. doi: 10.3390/s20185388.

Abstract

Many safety accidents can occur in industrial sites. Among them, falls from heights (FFHs) are the most frequent accidents and have the highest fatality rate. Therefore, some existing studies have developed personal wearable airbags to mitigate the damage caused by FFHs. To utilize these airbags effectively, it is essential to detect FFHs before collision with the floor. In this study, an inertial measurement unit (IMU) sensor attached to the seventh thoracic vertebrae (T7) was used to develop an FFH detection algorithm. The vertical angle and vertical velocity were calculated using the inertial data obtained from the IMU sensor. Forty young and healthy males were recruited to perform non-FFH and FFH motions. In addition, experiments using a human mannequin and dynamics simulations were performed to obtain FFH data at heights above 2 m. The developed algorithm achieved 100% FFH detection accuracy and provided sufficient lead time such that the airbags could be inflated completely before collision with the floor.

摘要

许多安全事故都可能发生在工业现场。其中,高处坠落(FFH)是最常见的事故,死亡率最高。因此,一些现有研究已经开发了个人穿戴式气囊,以减轻 FFH 造成的伤害。为了有效地利用这些气囊,在与地面碰撞之前检测到 FFH 是至关重要的。在这项研究中,使用附着在第七胸椎(T7)的惯性测量单元(IMU)传感器来开发 FFH 检测算法。通过从 IMU 传感器获得的惯性数据计算垂直角度和垂直速度。招募了 40 名年轻健康的男性来进行非 FFH 和 FFH 运动。此外,还进行了人体模型实验和动力学模拟,以获得超过 2 米高度的 FFH 数据。所开发的算法实现了 100%的 FFH 检测准确性,并提供了足够的前置时间,以便在与地面碰撞之前完全充气。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/543d/7570923/7da4c9c28006/sensors-20-05388-g001.jpg

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