Feature extraction of P300 signal using Bayesian delay time estimation

Author

Togashi, Ryo ; Washizawa, Yoshikazu

Author_Institution

Univ. of Electro-Commun., Chofu, Japan

fYear

2013

fDate

Oct. 29 2013-Nov. 1 2013

Firstpage

1

Lastpage

5

Abstract

Brain-computer interfaces (BCIs) based on event-related potentials (ERP) are communicating tools with severely disabled people. P300 which is observed after 300 mili seconds from stimuli is widely used for the operation principle of BCIs. However the response time to the stimuli depends on a subject, trial, and also a channel. Many existing approaches ignore this variation and extract only low frequency component. We propose a method to estimate the response time of P300 using Bayesian estimation. The proposed method exhibited higher performance in our auditory BCI.

Keywords

Bayes methods; auditory evoked potentials; brain; brain-computer interfaces; delays; feature extraction; handicapped aids; medical signal detection; medical signal processing; signal classification; visual evoked potentials; Bayesian delay time estimation; ERP; P300 response time estimate; P300 signal; auditory BCI; auditory stimulus; brain response; brain-computer interfaces; classification accuracy; event-related potentials; feature extraction; severely disabled people; visual stimulus; Accuracy; Bayes methods; Delays; Electrodes; Electroencephalography; Feature extraction; Time factors;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific

Conference_Location

Kaohsiung

Type

conf

DOI

10.1109/APSIPA.2013.6694191

Filename

6694191