评估非接触式呼吸速率检测在事故后护理应用中的有效性
Jacob T Valente1, Sparsh Jain1, Arush Amin2
1Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, USA; Virginia Tech Transportation Institute, Virginia Tech, Blacksburg, USA.
Accident; analysis and prevention
|September 28, 2023
概括
在机动车碰撞 (MVC) 患者中检测呼吸速率的非接触式传感器显示出有前途. 与其他方法相比,基于压力的传感器表现出最好的准确性和精度,有助于紧急医疗服务 (EMS) 选.
科学领域:
- 生物医学工程 生物医学工程
- 紧急医疗服务 技术 技术
- 生理监测 生理监测
背景情况:
- 机动车碰撞事故 (MVCs) 的有效事故后护理依赖于紧急医疗服务 (EMS) 人员了解受伤风险并进行准确的患者分拣.
- 目前的分拣方法可以通过提供实时生理数据的技术来增强,改善患者评估和资源分配.
- 开发基于简单选和快速治疗 (START) 协议的交互式车载选系统是改善MVC护理的关键目标.
研究的目的:
- 评估汽车内集成的非接触式呼吸速率检测技术作为车载分类系统组件的有效性.
- 为了比较超声波,热和基于压力的呼吸检测方法与标准呼吸带的准确性和精度.
主要方法:
- 三种非接触式呼吸检测技术 (超声波,热,基于压力) 已集成到2015年福特Taurus.
- 测试包括使用这些传感器和呼吸带在各种条件下收集呼吸速率数据:乘客体重,机温度,服装重量和环境声音.
- 使用30秒的滑动窗口计算呼吸速率,分析平均值和标准偏差以评估传感器的准确性和精度.
主要成果:
- 传感器类型,机温度和声音水平显著影响了平均呼吸速率.
- 传感器类型,声音水平和乘客服装重量显著影响了呼吸速率的标准偏差.
- 基于压力的传感器系统表现出最高的准确性和精度,与呼吸带的性能密切匹配.
结论:
- 基于非接触式压力传感器显示出在车辆环境中用于MVC分类的准确和精确的呼吸率监测的巨大潜力.
- 环境因素,如温度和声音,以及乘客特征,如衣服重量,影响传感器性能.
- 这项概念验证研究支持将基于压力的非接触式呼吸监测集成到未来车载EMS分选系统中.
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