Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA

Aung Aung Phyo Wai; Min Ho Lee; Seong Whan Lee; Cuntai Guan

doi:10.1109/NER.2019.8716985

Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA

Aung Aung Phyo Wai
, Min Ho Lee
, Seong Whan Lee
, Cuntai Guan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Steady State Visual Evoked Potentials (SSVEP) based Brain Computer Interface (BCI) provides high throughput in communication. In SSVEP-BCI, typically, higher accuracy can be achieved with a relatively longer response time. It is therefore a research topic to reduce the response time while keeping high accuracy. We propose a new method, temporal alignments enhanced Canonical Correlation Analysis (TACCA), followed by a decision fusion to improve classification accuracy with short response time. TACCA exploits linear correlation with non-linear similarity between steady-state responses and stimulus frequencies. We compare TACCA and three state-of-the-art methods using data from 54-subjects with response time ranging from 0.5 to 4 seconds. The evaluation results show that TACCA yields mean significant accuracy increase of 10-30% in all segment lengths, especially for the shorter time segment. One-way ANOVA tests show high significant differences between single and multiple phases in TACCA performance.

Original language	English
Title of host publication	9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Publisher	IEEE Computer Society
Pages	155-158
Number of pages	4
ISBN (Electronic)	9781538679210
DOIs	https://doi.org/10.1109/NER.2019.8716985
Publication status	Published - 2019 May 16
Externally published	Yes
Event	9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States Duration: 2019 Mar 20 → 2019 Mar 23

Publication series

Name	International IEEE/EMBS Conference on Neural Engineering, NER
Volume	2019-March
ISSN (Print)	1948-3546
ISSN (Electronic)	1948-3554

Conference

Conference	9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Country/Territory	United States
City	San Francisco
Period	19/3/20 → 19/3/23

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

ASJC Scopus subject areas

Artificial Intelligence
Mechanical Engineering

Access to Document

10.1109/NER.2019.8716985

Cite this

Phyo Wai, A. A., Lee, M. H., Lee, S. W., & Guan, C. (2019). Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. In 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 (pp. 155-158). Article 8716985 (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2019-March). IEEE Computer Society. https://doi.org/10.1109/NER.2019.8716985

Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. / Phyo Wai, Aung Aung; Lee, Min Ho; Lee, Seong Whan et al.
9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society, 2019. p. 155-158 8716985 (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2019-March).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Phyo Wai, AA, Lee, MH, Lee, SW & Guan, C 2019, Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. in 9th International IEEE EMBS Conference on Neural Engineering, NER 2019., 8716985, International IEEE/EMBS Conference on Neural Engineering, NER, vol. 2019-March, IEEE Computer Society, pp. 155-158, 9th International IEEE EMBS Conference on Neural Engineering, NER 2019, San Francisco, United States, 19/3/20. https://doi.org/10.1109/NER.2019.8716985

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title = "Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA",

abstract = "Steady State Visual Evoked Potentials (SSVEP) based Brain Computer Interface (BCI) provides high throughput in communication. In SSVEP-BCI, typically, higher accuracy can be achieved with a relatively longer response time. It is therefore a research topic to reduce the response time while keeping high accuracy. We propose a new method, temporal alignments enhanced Canonical Correlation Analysis (TACCA), followed by a decision fusion to improve classification accuracy with short response time. TACCA exploits linear correlation with non-linear similarity between steady-state responses and stimulus frequencies. We compare TACCA and three state-of-the-art methods using data from 54-subjects with response time ranging from 0.5 to 4 seconds. The evaluation results show that TACCA yields mean significant accuracy increase of 10-30\% in all segment lengths, especially for the shorter time segment. One-way ANOVA tests show high significant differences between single and multiple phases in TACCA performance.",

author = "\{Phyo Wai\}, \{Aung Aung\} and Lee, \{Min Ho\} and Lee, \{Seong Whan\} and Cuntai Guan",

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year = "2019",

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doi = "10.1109/NER.2019.8716985",

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AB - Steady State Visual Evoked Potentials (SSVEP) based Brain Computer Interface (BCI) provides high throughput in communication. In SSVEP-BCI, typically, higher accuracy can be achieved with a relatively longer response time. It is therefore a research topic to reduce the response time while keeping high accuracy. We propose a new method, temporal alignments enhanced Canonical Correlation Analysis (TACCA), followed by a decision fusion to improve classification accuracy with short response time. TACCA exploits linear correlation with non-linear similarity between steady-state responses and stimulus frequencies. We compare TACCA and three state-of-the-art methods using data from 54-subjects with response time ranging from 0.5 to 4 seconds. The evaluation results show that TACCA yields mean significant accuracy increase of 10-30% in all segment lengths, especially for the shorter time segment. One-way ANOVA tests show high significant differences between single and multiple phases in TACCA performance.

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Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA

Abstract

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Bibliographical note

ASJC Scopus subject areas

Access to Document

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