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

Mike Wells, Lara Nicole Goldstein, Terran Wells, Niloufar Ghazi, Abhijit Pandya, Borifoje Furht, Gabriella Engstrom, Muhammad Tanveer Jan, Richard Shih
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Abstract

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 extremely accurate. 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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三维摄像系统估算人体总重量:急诊医学应用中潜在的高科技解决方案?范围审查
背景由于通常无法测量体重,因此在急救过程中必须对成人患者施用基于体重的药物时,需要对其体重进行估计。不准确的估计可能会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。提取并评估了有关研究特点、研究质量、所评估的三维摄像方法以及系统准确性的数据。结果 共纳入了 14 项研究,这些研究发表于 2012 年至 2024 年。大多数研究使用了微软 Kinect 摄像头,并采用了各种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%。这些研究强调了三维摄像系统适用于急诊护理的巨大潜力。结论三维摄像系统为急诊环境中的体重估算提供了一种前景广阔的方法,有可能提高药物剂量的准确性和患者的安全性。体重估计非常准确。重要的是,三维摄像系统具有非常适合在急救护理中使用的特性。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。
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