Empirical Mode Decomposition in the Electroencephalogram

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.

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