通过 3D 摄像系统估算人体总重量:急诊医学应用的潜在高科技解决方案?范围审查。

IF 1.6 Q2 EMERGENCY MEDICINE
Mike Wells MBBCh, PhD, Lara Nicole Goldstein MD, PhD, Terran Wells, Niloufar Ghazi MD, Abhijit Pandya PhD, Borifoje Furht PhD, Gabriella Engstrom PhD, Muhammad Tanveer Jan PhD, Richard Shih MD
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引用次数: 0

摘要

背景:在急救过程中,如果必须对成年患者施用基于体重的药物,则需要估算其体重,因为通常无法测量体重。不准确的估计可能导致药物剂量不准确,从而对患者造成伤害。由人工智能驱动的高科技 3D 摄像系统或许能解决这一问题。本综述旨在描述和评估已发表的有关三维摄像体重估算方法的文献:方法:对研究使用三维摄像系统估算成人体重的文章进行了系统的文献检索。结果:共纳入了 14 项研究,其中有 3 项研究的研究对象为成人,有 2 项研究的研究对象为儿童:结果:共纳入了 14 项研究,这些研究发表于 2012 年至 2024 年。大多数研究都使用了微软 Kinect 摄像头,并采用了不同的分析方法来估算体重。3D 摄像系统的 P10 通常达到 90%(90% 的估计值在实际重量的 10% 以内),所有系统的 P10 均超过 78%。这些研究凸显了三维摄像系统在急诊护理中应用的巨大潜力:结论:三维摄像系统为急诊环境中的体重估算提供了一种很有前景的方法,有可能提高药物剂量的准确性和患者的安全性。体重估算的准确性令人满意,往往超过现有体重估算方法的准确性。重要的是,三维摄像系统所具有的特性使其非常适合在急救护理中使用。未来的研究应侧重于在更大规模的研究中开发和验证这种方法,并进行真正的外部和临床验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Total body weight estimation by 3D camera systems: Potential high-tech solutions for emergency medicine applications? A scoping review

Total body weight estimation by 3D camera systems: Potential high-tech solutions for emergency medicine applications? A scoping review

Background

Weight estimation is required in adult patients when weight-based medication must be administered during emergency care, as measuring weight is often not possible. Inaccurate estimations may lead to inaccurate drug dosing, which may cause patient harm. High-tech 3D camera systems driven by artificial intelligence might be the solution to this problem. The aim of this review was to describe and evaluate the published literature on 3D camera weight estimation methods.

Methods

A systematic literature search was performed for articles that studied the use of 3D camera systems for weight estimation in adults. Data on the study characteristics, the quality of the studies, the 3D camera methods evaluated, and the accuracy of the systems were extracted and evaluated.

Results

A total of 14 studies were included, published from 2012 to 2024. Most studies used Microsoft Kinect cameras, with various analytical approaches to weight estimation. The 3D camera systems often achieved a P10 of 90% (90% of estimates within 10% of actual weight), with all systems exceeding a P10 of 78%. The studies highlighted a significant potential for 3D camera systems to be suitable for use in emergency care.

Conclusion

The 3D camera systems offer a promising method for weight estimation in emergency settings, potentially improving drug dosing accuracy and patient safety. Weight estimates were satisfactorily accurate, often exceeding the reported accuracy of existing weight estimation methods. Importantly, 3D camera systems possess characteristics that could make them very appropriate for use during emergency care. Future research should focus on developing and validating this methodology in larger studies with true external and clinical validation.

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