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从可穿戴的呼吸道口罩中对白天和夜晚的呼吸参数进行测量波动分析
Alessandra Angelucci1, Andrea Aliverti1
1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.
对可穿戴呼吸系统数据的测定波动分析 (DFA) 显示了明确的昼夜呼吸模式. 这种方法揭示了呼吸控制的生理差异,特别是在睡眠期间.
科学领域:
- 生理学 生理学 生理学
- 生物医学工程 生物医学工程
- 数据分析 数据分析
背景情况:
- 可穿戴式传感器为收集生理数据提供了新的方法.
- 了解呼吸系统的变化对于评估健康至关重要.
- 确定波动分析 (DFA) 是一种分析时间序列数据相关性质的方法.
研究的目的:
- 从可穿戴设备对呼吸参数时间序列应用测定波动分析 (DFA).
- 了解这些呼吸信号的可变性和相关性质.
- 为健康志愿者提供DFA缩放因子的初步规范数据.
主要方法:
- 采集了使用AirgoTM频段 (采样频率为10 Hz) 的18名健康志愿者的呼吸数据.
- 应用DFA到6小时的呼吸参数记录.
- 利用线性和二次性缩方法来分析数据.
主要成果:
- 在DFA缩放因子 (α值) 中,在日夜记录的潮体积,分钟通风,平均吸入流量,平均呼气流量和工作周期之间发现了显著的差异 (p < 0.001).
- 二次减速揭示了额外的差异,特别是吸入和呼出时间,线性减速无法检测到.
- 研究结果表明,与白天相比,睡眠期间有不同的呼吸调节模式.
结论:
- DFA对可穿戴呼吸系统数据的分析强调了白天和夜晚之间不同的监管模式.
- 该研究表明,DFA有潜力揭示呼吸控制中的生理差异,特别是在睡眠期间.
- 未来的研究应该扩大样本规模,包括患有呼吸系统疾病的个体,以实现临床应用.
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