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Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:

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Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

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在全身麻醉下对EEG信号的基于波形变换的模式分解.

Shoko Yamochi¹, Tomomi Yamada¹, Yurie Obata²

¹Department of Anesthesiology, Kyoto Prefectural University of Medicine, Kyoto, Japan.

|November 19, 2024

概括

此摘要是机器生成的。

波形模式分解 (WMD) 有效地提取了在sevoflurane麻醉期间微妙的电脑电图 (EEG) 频率变化. 这种方法提供了与实证波形变换 (EWT) 和变化模式分解 (VMD) 相比,改善了监测麻醉深度的参数.

关键词:

电脑脑电图 (EEG) 是一种电脑电图.经验波量变换是经验波量变换.内在模式功能内在模式功能变化模式分解的变化模式分解波形模式分解波形模式分解

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科学领域:

信号处理和生物医学工程.
分析用于麻醉监测的电脑电图 (EEG) 信号.

背景情况:

模式分解方法对于从复杂的时间序列数据中提取内在模式函数 (IMF) 是至关重要的.
脑电图 (EEG) 信号被分析以了解在全身麻醉期间的大脑活动.

研究的目的:

为了比较经验波波变换 (EWT) 和波波模式分解 (WMD) 与变化模式分解 (VMD) 的有效性,用于分析在sevoflurane麻醉期间的EEG信号.
确定最合适的模式分解方法,以跟踪麻醉后出现的双光谱指数 (BIS) 变化.

主要方法:

使用连接到双光谱指数 (BIS) 监控器的EEG分析软件获取原始EEG数据.
为实证模式分解 (EMD),VMD,EWT和WMD开发定制软件.
使用EWT和WMD分析了EEG信号,并将结果与VMD进行比较.

主要成果:

经验波形变换 (EWT) 在高频带 (≥10 Hz) 中显示出广泛的分散.
波形模式分解 (WMD) 提供了狭带分离,患者之间的差异最小,优于VMD和EWT.
多重线性回归证实,大规模杀伤性武器衍生的IMF与麻醉出现期间的BIS变化最好相关.

结论:

波形模式分解 (WMD) 有效地捕捉了总麻醉引起的微妙EEG频率变化.
大规模杀伤器提供了一种有希望的方法,用于开发增强的参数来评估麻醉深度.