实施生命体征检测算法,监督有特殊需求的个人撤离
Krzysztof Konopko1, Dariusz Janczak1, Wojciech Walendziuk1
1Faculty of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland.
Sensors (Basel, Switzerland)
|December 11, 2025
概括
这项研究提出了一种新的系统,用于在疏散期间监测生命体征. 它准确地检测脉冲,验证腕带接触,并分析运动,达到超过94%的准确性可靠的个人评估.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 可穿戴技术可穿戴技术
背景情况:
- 在紧急疏散期间,对重要参数的有效监测至关重要.
- 现有的系统可能缺乏强度来处理动态条件,如运动和可变接触.
- 准确的实时评估生理数据对于及时干预至关重要.
研究的目的:
- 开发和验证一个全面的系统来监测疏散人员的重要参数.
- 将脉冲检测,腕带-皮肤接触验证和运动识别集成到一个系统中.
- 确保在疏散场景中实时可靠的生命体征评估.
主要方法:
- 利用MAX30102光学传感器进行脉冲检测,使用快速富里埃转换 (FFT) 和内核密度估计 (KDE) 进行信号处理.
- 通过测量反散光的亮度和手腕温度,验证了腕带接触.
- 使用MPU-9250惯性模块实现运动检测,以区分休息和活动.
主要成果:
- 开发的实时算法可靠地评估了关键参数,显示出高准确度.
- 在一个代表性群体上的实验研究证实了算法的正确性.
- 该系统实现了近95%的准确性和F1得分为0.9465,表明了高性能.
结论:
- 集成系统在疏散期间可靠地监测重要参数.
- 结合精确的脉冲检测,皮肤接触验证和运动分析,提高了监测的有效性.
- 该系统的高精度和F1分数使其适用于关键疏散监控应用.
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