Application of the Hilbert_Huang transform and wavelet transform in the EEG processing

Gui Xin Zhang, Ping Dong Wu, Jie Huang, Man Ling Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Brain-Machine Interface (BMI) could make people control machine through EEG which is produced by the brain activity, and it provide a new communication method between human and machine. The research for BMI will extend the ability of communication and control the environment and machine. The key point of the BMI is how to abstract and distinguish different EEG characters. Therefore, EEG signal processing method is the emphasis of BMI. Wavelet Transform and Hilbert-Huang Transform are used to analyze the EEG signal in this paper. The results indicate that these two methods could abstract the main characters of the EEG, but the Hilbert-Huang Transform could express the distributing status in the time and frequency aspect of the EEG more accurately, because it produces the self-adaptive basis according the data, and obtain the local and instantaneous frequency of the EEG.

Original languageEnglish
Title of host publicationInformation Technology Applications in Industry, Computer Engineering and Materials Science
Pages1753-1757
Number of pages5
DOIs
Publication statusPublished - 2013
Event3rd International Conference on Materials Science and Information Technology, MSIT 2013 - Nanjing, Jiangsu, China
Duration: 14 Sept 201315 Sept 2013

Publication series

NameAdvanced Materials Research
Volume756-759
ISSN (Print)1022-6680

Conference

Conference3rd International Conference on Materials Science and Information Technology, MSIT 2013
Country/TerritoryChina
CityNanjing, Jiangsu
Period14/09/1315/09/13

Keywords

  • Brain-machine interface
  • EEG
  • Hilbert-huang transform
  • Wavelet transform

Fingerprint

Dive into the research topics of 'Application of the Hilbert_Huang transform and wavelet transform in the EEG processing'. Together they form a unique fingerprint.

Cite this