通过人工智能增强机械通风管理:用于自动检测通风模式,参数和异步的计算机视觉
Diego de Carvalho1, Kleyton Hoffmann2, João Rogério Nunes Filho3
1Programa de Pós-Graduação em Biociências e Saúde (PPGBS), Universidade do Oeste de Santa Catarina, Joaçaba, SC, Brazil.
Journal of critical care
|August 23, 2025
概括
一个人工智能平台,NexoVent,通过屏幕图像准确检测呼吸器设置和患者呼吸器异步 (PVA). 这项技术为ICU的机械通风管理提供实时决策支持.
科学领域:
- 危急护理医学
- 生物医学工程
- 医疗保健中的人工智能
背景情况:
- 在重症监护室 (ICU) 中,机械呼吸非常重要.
- 患者-呼吸器异步 (PVA) 可能对患者的结果产生负面影响.
- 实时监测呼吸器参数和PVA对于最佳的患者护理至关重要.
研究的目的:
- 评估Nexovent人工智能平台的性能.
- 从呼吸机屏幕图像中评估其检测呼吸机模式,参数和PVA的能力.
- 为了确定人工智能驱动的,基于图像的实时数据提取的精度.
主要方法:
- 在第三级护理重症监护室进行观察研究.
- 在PCV模式下使用的Servo-i和Servo-s呼吸机.
- 通过移动设备对呼吸机屏幕图像进行计算机视觉,OCR和波形分析.
- 对六种PVA类型的AI检测与专家的共识进行比较.
主要成果:
- 在通风器参数方面,NexoVent的准确度为95. 4%,而在通风器模式方面则为94. 0%.
- 异步检测准确度在81. 6% (延迟周期) 到97. 8% (无效力) 之间.
- 所有分析都是以图像为基础的,不需要直接的呼吸机接口.
结论:
- NexoVent使用非侵入式计算机视觉精确检测呼吸系统数据和PVA.
- 该平台显示了改进机械通风管理的潜力.
- 它可以提供实时的临床决策支持,特别是在专业知识或设备互操作性有限的情况下.
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