Boosting the Information Transfer Rate of an SSVEP-BCI System Using Maximal-Phase-Locking Value and Minimal-Distance Spatial Filter Banks

Ke Lin; Shangkai Gao; Xiaorong Gao

doi:10.26599/TST.2018.9010010

Tsinghua Science and Technology 2019, 24(3): 262-270 https://doi.org/10.26599/TST.2018.9010010

Open Access | Issue | Published: 24 January 2019

Boosting the Information Transfer Rate of an SSVEP-BCI System Using Maximal-Phase-Locking Value and Minimal-Distance Spatial Filter Banks

Show Author's Information Hide Author's Information Ke Lin, Shangkai Gao, Xiaorong Gao(

)

Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.

Keywords:

SSVEP-BCI, Information Transfer Rate (ITR), spatial filter, distance, Phase-Locking Value (PLV)

Cite this article:

Lin K, Gao S, Gao X. Boosting the Information Transfer Rate of an SSVEP-BCI System Using Maximal-Phase-Locking Value and Minimal-Distance Spatial Filter Banks. Tsinghua Science and Technology, 2019, 24(3): 262-270. https://doi.org/10.26599/TST.2018.9010010

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Abstract

For Brain-Computer Interface (BCI) systems, improving the Information Transfer Rate (ITR) is a very critical issue. This study focuses on a Steady-State Visually Evoked Potential (SSVEP)-based BCI because of its advantage of high ITR. Unsupervised Canonical Correlation Analysis (CCA)-based method has been widely employed because of its high efficiency and easy implementation. In a recent study, an ensemble-CCA method based on individual training data was proposed and achieved an excellent performance with ITR of 267 bit/min. A 40-target SSVEP-BCI speller was investigated in this study, using an integration of Minimal-Distance (MD) and Maximal-Phase-locking value (MP) approaches. In the MD approach, a spatial filter is developed to minimize the distance between the training data and the reference sine signal, and in this study, two different types of distance were compared. In the MP approach, a spatial filter is developed to maximize the Phase-Locking Value (PLV) between the training calibration data and the reference sine signal. In addition to the fundamental frequency of stimulation, the harmonics were used to train MD and MP spatial filters, which formed spatial filter banks. The test data epoch was multiplied by the MP and MD spatial filter banks, and the distances and PLVs were extracted as features for recognition. Across 12 subjects with a 0.4 s-data length, the proposed method realized an average classification accuracy and ITR of 93% and 307 bit/min, respectively, which is significantly higher than the current state-of-the-art method. To the best of our knowledge, these results suggest that the proposed method has achieved the highest ITR in SSVEP-BCI studies.

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Boosting the Information Transfer Rate of an SSVEP-BCI System Using Maximal-Phase-Locking Value and Minimal-Distance Spatial Filter Banks

Show Author's information Hide Author's Information Ke Lin, Shangkai Gao, Xiaorong Gao(

)

Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China.

Abstract

Keywords: SSVEP-BCI, Information Transfer Rate (ITR), spatial filter, distance, Phase-Locking Value (PLV)

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Publication history

Received: 27 June 2017

Revised: 12 August 2017

Accepted: 24 August 2017

Published: 24 January 2019

Issue date: June 2019

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (Nos. 61431007 and 91320202).