Research ExplorerPublicationsA Brain-Computer Interface Based on Multi-Modal Attention

A Brain-Computer Interface Based on Multi-Modal Attention

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A Brain-Computer Interface Based on Multi-Modal Attention. / Zhang, D.; Wang, Y.; Maye, A.; Engel, A.K.; Gao, X.; Hong, B.; Gao, S.

Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on. 2007. p. 414-417.

Research output: SCORING: Contribution to book/anthology › SCORING: Contribution to collected editions/anthologies › Research › peer-review

Harvard

Zhang, D, Wang, Y, Maye, A, Engel, AK, Gao, X, Hong, B & Gao, S 2007, A Brain-Computer Interface Based on Multi-Modal Attention. in Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on. pp. 414-417. https://doi.org/10.1109/CNE.2007.369697

APA

Zhang, D., Wang, Y., Maye, A., Engel, A. K., Gao, X., Hong, B., & Gao, S. (2007). A Brain-Computer Interface Based on Multi-Modal Attention. In Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on (pp. 414-417) https://doi.org/10.1109/CNE.2007.369697

Vancouver

Zhang D, Wang Y, Maye A, Engel AK, Gao X, Hong B et al. A Brain-Computer Interface Based on Multi-Modal Attention. In Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on. 2007. p. 414-417 https://doi.org/10.1109/CNE.2007.369697

Bibtex

@inbook{4c3513caec3643148300f41a965f9bc5,
title = "A Brain-Computer Interface Based on Multi-Modal Attention",
abstract = "The amplitude of steady-state evoked potentials (SSEP) can be modulated by switching spatial attention within one modality. In this article, we show that switching attention between different sensory modalities also modulates SSEP amplitude. This could be used to combine classifications in each modality into a multi-modal brain-computer interface (BCI) system. We present the result of combining visual and tactile stimulation. Our investigation also revealed an attention-related power change of the mu-rhythm. Taking this as an additional feature into account results in a three-class BCI system with the same accuracy like an SSSEP-based system with only two classes",
keywords = "biology computing, human computer interaction, brain-computer interface, multimodal attention, sensory modalities, steady-state evoked potentials, Aging, Amplitude modulation, Biomedical engineering, Brain computer interfaces, Frequency, Neural engineering, Performance analysis, Pins, Steady-state, USA Councils",
author = "D. Zhang and Y. Wang and A. Maye and A.K. Engel and X. Gao and B. Hong and S. Gao",
year = "2007",
doi = "10.1109/CNE.2007.369697",
language = "English",
pages = "414--417",
booktitle = "Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on",

}

RIS

TY - CHAP

T1 - A Brain-Computer Interface Based on Multi-Modal Attention

AU - Zhang, D.

AU - Wang, Y.

AU - Maye, A.

AU - Engel, A.K.

AU - Gao, X.

AU - Hong, B.

AU - Gao, S.

PY - 2007

Y1 - 2007

N2 - The amplitude of steady-state evoked potentials (SSEP) can be modulated by switching spatial attention within one modality. In this article, we show that switching attention between different sensory modalities also modulates SSEP amplitude. This could be used to combine classifications in each modality into a multi-modal brain-computer interface (BCI) system. We present the result of combining visual and tactile stimulation. Our investigation also revealed an attention-related power change of the mu-rhythm. Taking this as an additional feature into account results in a three-class BCI system with the same accuracy like an SSSEP-based system with only two classes

AB - The amplitude of steady-state evoked potentials (SSEP) can be modulated by switching spatial attention within one modality. In this article, we show that switching attention between different sensory modalities also modulates SSEP amplitude. This could be used to combine classifications in each modality into a multi-modal brain-computer interface (BCI) system. We present the result of combining visual and tactile stimulation. Our investigation also revealed an attention-related power change of the mu-rhythm. Taking this as an additional feature into account results in a three-class BCI system with the same accuracy like an SSSEP-based system with only two classes

KW - biology computing

KW - human computer interaction

KW - brain-computer interface

KW - multimodal attention

KW - sensory modalities

KW - steady-state evoked potentials

KW - Aging

KW - Amplitude modulation

KW - Biomedical engineering

KW - Brain computer interfaces

KW - Frequency

KW - Neural engineering

KW - Performance analysis

KW - Pins

KW - Steady-state

KW - USA Councils

U2 - 10.1109/CNE.2007.369697

DO - 10.1109/CNE.2007.369697

M3 - SCORING: Contribution to collected editions/anthologies

SP - 414

EP - 417

BT - Neural Engineering, 2007. CNE '07. 3rd International IEEE/EMBS Conference on

ER -