Phase Synchronization Analysis and Support Vector Machine for Recognition of Mental Tasks

Author

Aihua, Zhang ; Yuhan, Zhao

Author_Institution

Lanzhou Univ. of Technol.

fYear

2006

Firstpage

5373

Lastpage

5376

Abstract

A measuring method of phase synchronization is presented for analyzing event-related electroencephalogram (EEG) recordings. The mean phase coherence (MPC) of EEG recordings during imagination of hand movement is calculated. Furthermore, the support vector machine is used for classification of the mental tasks. The preliminary results suggest that MPC could be promising method for brain-computer interfaces. Dynamic MPC measurement provides a new idea for recognition of mental tasks

Keywords

electroencephalography; handicapped aids; medical signal processing; signal classification; support vector machines; EEG; brain-computer interfaces; event-related electroencephalogram; hand movement imagination; mean phase coherence; mental task classification; mental task recognition; phase synchronization analysis; support vector machine; Biomedical measurements; Brain computer interfaces; Brain modeling; Electroencephalography; Feature extraction; Frequency estimation; Frequency synchronization; Phase measurement; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

Conference_Location

Shanghai

Print_ISBN

0-7803-8741-4

Type

conf

DOI

10.1109/IEMBS.2005.1615696

Filename

1615696