Literature DB >> 24743165

An optimized ERP brain-computer interface based on facial expression changes.

Jing Jin1, Ian Daly, Yu Zhang, Xingyu Wang, Andrzej Cichocki.   

Abstract

OBJECTIVE: Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain-computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern. APPROACH: Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures. MAIN
RESULTS: The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05). SIGNIFICANCE: The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.

Entities:  

Mesh:

Year:  2014        PMID: 24743165     DOI: 10.1088/1741-2560/11/3/036004

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  21 in total

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Journal:  Med Biol Eng Comput       Date:  2017-06-28       Impact factor: 2.602

2.  An exploration of spatial auditory BCI paradigms with different sounds: music notes versus beeps.

Authors:  Minqiang Huang; Ian Daly; Jing Jin; Yu Zhang; Xingyu Wang; Andrzej Cichocki
Journal:  Cogn Neurodyn       Date:  2016-01-23       Impact factor: 5.082

3.  An ERP-based BCI with peripheral stimuli: validation with ALS patients.

Authors:  Yangyang Miao; Erwei Yin; Brendan Z Allison; Yu Zhang; Yan Chen; Yi Dong; Xingyu Wang; Dewen Hu; Andrzej Chchocki; Jing Jin
Journal:  Cogn Neurodyn       Date:  2019-06-11       Impact factor: 5.082

4.  Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction.

Authors:  B O Mainsah; G Reeves; L M Collins; C S Throckmorton
Journal:  J Neural Eng       Date:  2017-08       Impact factor: 5.379

5.  Evaluation of color modulation in visual P300-speller using new stimulus patterns.

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Journal:  Cogn Neurodyn       Date:  2021-02-21       Impact factor: 3.473

6.  Use of a Green Familiar Faces Paradigm Improves P300-Speller Brain-Computer Interface Performance.

Authors:  Qi Li; Shuai Liu; Jian Li; Ou Bai
Journal:  PLoS One       Date:  2015-06-18       Impact factor: 3.240

7.  Exploring Combinations of Different Color and Facial Expression Stimuli for Gaze-Independent BCIs.

Authors:  Long Chen; Jing Jin; Ian Daly; Yu Zhang; Xingyu Wang; Andrzej Cichocki
Journal:  Front Comput Neurosci       Date:  2016-01-29       Impact factor: 2.380

8.  Optimizing the Face Paradigm of BCI System by Modified Mismatch Negative Paradigm.

Authors:  Sijie Zhou; Jing Jin; Ian Daly; Xingyu Wang; Andrzej Cichocki
Journal:  Front Neurosci       Date:  2016-10-07       Impact factor: 4.677

9.  Effects of Background Music on Objective and Subjective Performance Measures in an Auditory BCI.

Authors:  Sijie Zhou; Brendan Z Allison; Andrea Kübler; Andrzej Cichocki; Xingyu Wang; Jing Jin
Journal:  Front Comput Neurosci       Date:  2016-10-13       Impact factor: 2.380

10.  Decoding of Motor Coordination Imagery Involving the Lower Limbs by the EEG-Based Brain Network.

Authors:  Yunfa Fu; Zhouzhou Zhou; Anmin Gong; Qian Qian; Lei Su; Lei Zhao
Journal:  Comput Intell Neurosci       Date:  2021-06-23
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