Wavelet transform for the identification of P300 | Zendy

Vladimir Bulanov | Zendy; Alexander Zakharov | Zendy; Elena Khivintseva | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Wavelet transform for the identification of P300

Author(s) -

Vladimir Bulanov,

Alexander Zakharov,

Elena Khivintseva

Publication year - 2020

Publication title -

iop conference series materials science and engineering

Language(s) - English

Resource type - Journals

eISSN - 1757-899X

pISSN - 1757-8981

DOI - 10.1088/1757-899x/862/5/052049

Subject(s) - pattern recognition (psychology) , wavelet transform , wavelet , artificial intelligence , event related potential , computer science , electroencephalography , identification (biology) , signal processing , speech recognition , psychology , digital signal processing , botany , psychiatry , computer hardware , biology

The reliability of a newly developed algorithm for the identification of the P300 component of event-related potentials based on a continuous wavelet transform was investigated. The electroencephalogram records of one participant made by using a three-stimulus paradigm (a kind of the odd-ball paradigm) were analyzed. The accuracy of identification of certain wavelet types for the detection of P300 was from 76.32 to 86.84%. Thus, relatively simple algorithms for processing and classifying the electroencephalogram record signal show acceptable results in terms of the accuracy of identification of the P300 component of event-related potentials based on randomly selected data.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research