Literature DB >> 32149645

Emotion-Inducing Imagery Versus Motor Imagery for a Brain-Computer Interface.

A D Bigirimana, N Siddique, D Coyle.   

Abstract

Neural correlates of intentionally induced human emotions may offer alternative imagery strategies to control brain-computer interface (BCI) applications. In this paper, a novel BCI control strategy i.e., imagining fictional or recalling mnemonic sad and happy events, emotion-inducing imagery (EII), is compared to motor imagery (MI) in a study involving multiple sessions using a two-class electroencephalogram (EEG)-based BCI paradigm with 12 participants. The BCI setup enabled online continuous visual feedback presentation in a game involving one-dimensional control of a game character. MI and EII are compared across different signal-processing frameworks which are based on neural-time-series-prediction-preprocessing (NTSPP), filter bank common spatial patterns (FBCSP) and hemispheric asymmetry (ASYM). Online single-trial classification accuracies (CA) results indicate that MI performance across all participants is 77.54% compared to EII performance of 68.78% ( ). The results show that an ensemble of the NTSPP, FBCSP and ASYM frameworks maximizes performance for EII with average CA of 71.64% across all participants. Furthermore, the participants' subjective responses indicate that they preferred MI over emotion-inducing imagery (EII) in controlling the game character, and MI was perceived to offer most control over the game character. The results suggest that EII is not a viable alternative to MI for the majority of participants in this study but may be an alternative imagery for a subset of BCI users based on acceptable EII performance (CA >70%) observed for some participants.

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Year:  2020        PMID: 32149645     DOI: 10.1109/TNSRE.2020.2978951

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  3 in total

1.  LEDPatNet19: Automated Emotion Recognition Model based on Nonlinear LED Pattern Feature Extraction Function using EEG Signals.

Authors:  Turker Tuncer; Sengul Dogan; Abdulhamit Subasi
Journal:  Cogn Neurodyn       Date:  2021-11-25       Impact factor: 3.473

2.  Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain-computer interface training of a cybathlete who has tetraplegia.

Authors:  Attila Korik; Karl McCreadie; Niall McShane; Naomi Du Bois; Massoud Khodadadzadeh; Jacqui Stow; Jacinta McElligott; Áine Carroll; Damien Coyle
Journal:  J Neuroeng Rehabil       Date:  2022-09-06       Impact factor: 5.208

3.  Deep learning-based self-induced emotion recognition using EEG.

Authors:  Yerim Ji; Suh-Yeon Dong
Journal:  Front Neurosci       Date:  2022-09-16       Impact factor: 5.152

  3 in total

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