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临床试验/NCT03303443
NCT03303443已完成不适用

Empirical Mode Decomposition in the Electroencephalogram During General Anesthesia Between Generations

National Taiwan University Hospital1 个研究点 分布在 1 个国家目标入组 60 人开始时间: 2016年5月15日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
60
试验地点
1
主要终点
EEG power calculation

研究概览

简要总结

Bispectral index (BIS), a standard monitor for perioperative monitor of patient's conscious level, is a noninvasive medical technique for monitoring and recording the electrical activity of brain.

详细描述

The electroencephalogram and BIS data have lots of information. Fourier transformation to decompose EEG was first applied on the EEG signaling until now. The disadvantages of Fourier transformation is hard to deal with physical signals, which was modulated by autonomic system and factors. The Hilbert-Huang transform (HHT) was proposed to decompose EEG signal into intrinsic mode functions (IMF) since 2004. HHT can obtain instantaneous frequency data and work well for data that is nonstationary and nonlinear. HHT have been applied for wild ranges, not only in the analysis of arrhythmia for medical and public health fields, but also in the earthquake detection and earth physics detection...etc.

The relationship between frontal EEG patterns and general anesthesia remain poorly understood. It can only say that the increase in frontal EEG power and shift power to lower frequencies during general anesthesia from publications. The investigators are going to compare the EEG signal between generations, try to find the difference in aging using empirical mode decomposition method.

研究设计

研究类型
Observational
观察模型
Other
时间视角
Prospective

入排标准

年龄范围
20 Years 至 80 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 20-40y/o or over 60y/o
  • Scheduled for low risk general anesthesia
  • Suitable for surgery after interviewed by anesthesiologist

排除标准

  • Not suitable for general anesthesia
  • High risk patient
  • Allergic to the EEG sensor

结局指标

主要结局

EEG power calculation

时间窗: During the operation time.

The investigator use root mean square energy to calculate EEG power.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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