Empirical Mode Decomposition in the Electroencephalogram
Empirical Mode Decomposition in the Electroencephalogram During General Anesthesia Between Generations
Study Overview
Status
Status
Conditions
Conditions
Detailed Description
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.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
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-
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Taipei, Taiwan, 100
- Feng-Fang Tsai
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- 20-40y/o or over 60y/o
- Scheduled for low risk general anesthesia
- Suitable for surgery after interviewed by anesthesiologist
Exclusion Criteria:
- Not suitable for general anesthesia
- High risk patient
- Allergic to the EEG sensor
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
|---|
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Younger
20-40 years old patients
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Elderly
over 60 years old patients
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
EEG power calculation
Time Frame: During the operation time.
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The investigator use root mean square energy to calculate EEG power.
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During the operation time.
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Study Chair: Feng-Fang Tsai, MD, National Taiwan University Hospital
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 201508007RIN
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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