心率变量可自动识别高压状态,考虑到呼吸系统组件
María Dolores Peláez-Coca1,2, Alberto Hernando2, María Teresa Lozano1,2
1Centro Universitario de la Defensa de Zaragoza, 50090 Zaragoza, Spain.
Sensors (Basel, Switzerland)
|January 23, 2024
概括
这项研究使用心率变化 (HRV) 来检测高压室中对大气压变化的生理反应. 一个机器学习模型识别了6个异常反应的个体,建议为潜水员提供个性化的安全协议.
科学领域:
- 生理监测是指对身体进行生理监测.
- 生物医学工程 生物医学工程
- 环境生理学环境生理学
背景情况:
- 了解对不同大气压的生理反应对于潜水和高压环境中的安全至关重要.
- 心率变化 (HRV) 分析提供了一种非侵入性方法来评估在压力下自主神经系统的功能.
研究的目的:
- 使用HRV识别具有独特的生理反应对高压条件的个体.
- 开发一个自动化系统来监测大气压暴露及其对生理参数的影响.
- 探索个体特征 (性别,经验) 和生理反应之间的潜在关联.
主要方法:
- 28名志愿者在一个干燥的高压室中暴露在1到5大气压下.
- 用九个参数分析心率变化 (HRV),包括呼吸和频率组成部分.
- 使用k-最近邻居分类器,根据HRV数据确定大气压水平.
主要成果:
- 该分类器在使用呼吸率,心率和交感响应频率参数来区分5ATM和3ATM压力时达到88.5%的准确性.
- 在28名受试者中,有6名在所有测试的压力水平上表现出异常的生理反应.
- 两名异常反应的受试者被认为是女性,潜水经验较少,尽管他们的沉浸反应正常.
结论:
- 自动化HRV监测可以有效地检测对大气压变化的生理反应.
- 一个子集的个体表现出明显的生理反应,对高压条件.
- 调查结果表明,根据性别和经验等个体因素,潜水员的安全协议可能需要量身定制.
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