Multiclass Classification of Word Imagination Speech with Hybrid Connectivity Features

Muhammad Naveed Iqbal Qureshi; Beomjun Min; Hyeong-Jun Park; Dongrae Cho; Woosu Choi; Boreom Lee

doi:10.1109/TBME.2017.2786251

Multiclass Classification of Word Imagination Speech with Hybrid Connectivity Features

IEEE Trans Biomed Eng. 2018 Oct;65(10):2168-2177. doi: 10.1109/TBME.2017.2786251. Epub 2017 Dec 22.

Authors

Muhammad Naveed Iqbal Qureshi, Beomjun Min, Hyeong-Jun Park, Dongrae Cho, Woosu Choi, Boreom Lee

PMID: 29989953
DOI: 10.1109/TBME.2017.2786251

Abstract

In this study, electroencephalography data of imagined words were classified using four different feature extraction approaches. Eight subjects were recruited for the recording of imagination with five different words, namely; 'go', 'back', 'left', 'right', and 'stop'.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Algorithms
Broca Area / physiology
Electroencephalography / methods*
Female
Humans
Image Processing, Computer-Assisted
Imagination / classification*
Imagination / physiology*
Male
Signal Processing, Computer-Assisted*
Speech / physiology*
Wernicke Area / physiology
Young Adult