Automatic Removal of Ocular Artifacts from Electroencephalogram using Hilbert-Huang Transform
Hilbert-Huang transform (HHT) is a time-frequency analysis method, which extract intrinsic mode functions (IMFs) that admit well-behaved Hilbert transforms from the analyzed signals using empirical mode decomposition. With the Hilbert transform, the IMF yields meaningful instantaneous frequencies as functions of time. This paper presents a signal processing technique for automatic removal of ocular artifacts from Electroencephalogram (EEG) based on HHT. First, EEG contaminated by ocular artifacts was decomposed IMFs. Then the instantaneous frequencies of each IMF were computed respectively. If all instantaneous frequencies of an IMF are less than 3Hz, then the value of the IMF is set to zero. If all instantaneous frequencies of an IMF are less than 16Hz, then the value of IMF, which is greater than a threshold, is set to zero. Computing the sum of all IMFs having been processed, we can obtain corrected EEG. The experimental results show that this method, which remove most ocular artifacts in EEG and distort EEG slightly, is effective.
Empirical Mode Decomposition Intrinsic mode function Instantaneous Frequency threshold value ocular artifacts removal
Yan Long Wang Jin Hua Liu Yuan Chun Liu Yan Long Wang
Dept. of Electrical and Information Engineering Zhe Jiang Institute of Communication and Media Hang Dept. of Electronic Engineering and Information Science University of Science and Technology of Chin
国际会议
上海
英文
2138-2141
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）