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来自过去的回音:为潜水研究中的大数据构建多普勒资料库。

An echo from the past: Building a Doppler repository for big data in diving research.

机构信息

Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill and North Carolina State University, North Carolina U.S.

Department of Emergency Medicine, School of Medicine, University of California, San Diego, La Jolla, California, U.S.S.

出版信息

Undersea Hyperb Med. 2021 First Quarter;48(1):57-58. doi: 10.22462/01.03.2021.7.

Abstract

Decompression sickness (DCS) remains a major operational concern for diving operations, submarine escape and high-altitude jumps. Aside from DCS symptoms, venous gas emboli (VGE) detected with ultrasound post-dive are often used as a marker of decompression stress in humans, with a specificity of 100% even though the sensitivity is poor [1]. Being non-invasive, portable and non-ionizing, ultrasound is particularly suited to regular and repeated monitoring. It could help elucidate inter- and intra-subject variability in VGE and DCS susceptibility, but analyzing these recordings remains a cumbersome task [2].

摘要

减压病(DCS)仍然是潜水作业、潜艇逃生和高空跳伞的主要作业关注点。除了减压病症状外,潜水后通过超声检测到的静脉气体栓塞(VGE)也常被用作人体减压应激的标志物,其特异性为 100%,尽管敏感性较差[1]。由于超声具有非侵入性、便携性和非电离性,因此特别适合于定期和重复监测。它可以帮助阐明 VGE 和 DCS 易感性的个体间和个体内变异性,但分析这些记录仍然是一项繁琐的任务[2]。

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