生理噪音:复杂的生物医学信号中的定义,估计和表征
IEEE transactions on bio-medical engineering
|July 3, 2023
概括
这项研究引入了一种新的,无模型的方法来量化复杂生物系统中的生理噪声. 该技术成功地估计了心率变化和脑电图 (EEG) 数据中的噪声水平,揭示了其对整体信号功率的贡献.
科学领域:
- 身体生理学 身体生理学
- 动态系统理论 动态系统理论
- 生物医学信号处理
背景情况:
- 非线性生理系统具有由固有的动态噪声影响的复杂动态.
- 估计这种噪音是具有挑战性的,如果没有先前的系统动态知识,特别是在生物环境中.
研究的目的:
- 引入一种正式的,封闭形式的方法来估计生理噪声功率.
- 为了实现噪声估计,而不需要对底层系统动态的特定知识.
主要方法:
- 模拟生理噪声作为独立的,相同分布的 (IID) 随机变量.
- 使用非线性概况来估计噪声.
- 在合成系统 (自行回归,物流,Pomeau-Manneville) 和真实生物医学数据 (心率变化,电脑图) 上验证方法.
主要成果:
- 无模型方法有效地区分不同生理信号的不同噪声水平.
- 生理噪声约占EEG信号功率的11%和心跳动态功率的32-65%.
- 在病理条件下观察到心血管噪声增加,在认知任务期间观察到大脑噪声增加.
结论:
- 生理学噪音是神经生物学动态的一个组成部分.
- 开发的框架允许在各种生物医学系列中测量生理噪声.
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