Literature DB >> 25570867

Hybrid frequency and phase coding for a high-speed SSVEP-based BCI speller.

Xiaogang Chen, Yijun Wang, Masaki Nakanishi, Tzyy-Ping Jung, Xiaorong Gao.   

Abstract

Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize high-speed communication between the human brain and the external environment. Recently, multiple access (MA) methods in telecommunications have been introduced into the system design of BCIs and showed their potential in improving BCI performance. This study investigated the feasibility of hybrid frequency and phase coding methods in multi-target SSVEP-based BCIs. Specifically, this study compared two hybrid target-coding strategies: (1) mixed frequency and phase coding, and (2) joint frequency and phase coding. In a simulated online BCI experiment using a 40-target BCI speller, BCI performance for both coding approaches were tested with a group of six subjects. At a spelling speed of 40 characters per minute (1.5 seconds per character), both approaches obtained high information transfer rates (ITR) (mixed coding: 172.37±28.67 bits/min, joint coding: 170.94±28.32 bits/min) across subjects. There was no statistically significant difference between the two approaches (p>0.05). These results suggest that the hybrid frequency and phase coding methods are highly efficient for multi-target coding in SSVEP BCIs with a large number of classes, providing a practical solution to implement a high-speed BCI speller.

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Year:  2014        PMID: 25570867     DOI: 10.1109/EMBC.2014.6944499

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  13 in total

1.  High-speed spelling with a noninvasive brain-computer interface.

Authors:  Xiaogang Chen; Yijun Wang; Masaki Nakanishi; Xiaorong Gao; Tzyy-Ping Jung; Shangkai Gao
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-19       Impact factor: 11.205

2.  Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis.

Authors:  Masaki Nakanishi; Yijun Wang; Xiaogang Chen; Yu-Te Wang; Xiaorong Gao; Tzyy-Ping Jung
Journal:  IEEE Trans Biomed Eng       Date:  2017-04-19       Impact factor: 4.538

3.  A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials.

Authors:  Masaki Nakanishi; Yijun Wang; Yu-Te Wang; Tzyy-Ping Jung
Journal:  PLoS One       Date:  2015-10-19       Impact factor: 3.240

4.  Frequency- and Phase Encoded SSVEP Using Spatiotemporal Beamforming.

Authors:  Benjamin Wittevrongel; Marc M Van Hulle
Journal:  PLoS One       Date:  2016-08-03       Impact factor: 3.240

5.  A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI.

Authors:  Piotr Stawicki; Felix Gembler; Aya Rezeika; Ivan Volosyak
Journal:  Brain Sci       Date:  2017-04-05

6.  Accurate Decoding of Short, Phase-Encoded SSVEPs.

Authors:  Ahmed Youssef Ali Amer; Benjamin Wittevrongel; Marc M Van Hulle
Journal:  Sensors (Basel)       Date:  2018-03-06       Impact factor: 3.576

7.  Spatiotemporal Beamforming: A Transparent and Unified Decoding Approach to Synchronous Visual Brain-Computer Interfacing.

Authors:  Benjamin Wittevrongel; Marc M Van Hulle
Journal:  Front Neurosci       Date:  2017-11-15       Impact factor: 4.677

8.  Decoding Steady-State Visual Evoked Potentials From Electrocorticography.

Authors:  Benjamin Wittevrongel; Elvira Khachatryan; Mansoureh Fahimi Hnazaee; Flavio Camarrone; Evelien Carrette; Leen De Taeye; Alfred Meurs; Paul Boon; Dirk Van Roost; Marc M Van Hulle
Journal:  Front Neuroinform       Date:  2018-09-26       Impact factor: 4.081

9.  Enhancing performance of subject-specific models via subject-independent information for SSVEP-based BCIs.

Authors:  Mohammad Hadi Mehdizavareh; Sobhan Hemati; Hamid Soltanian-Zadeh
Journal:  PLoS One       Date:  2020-01-14       Impact factor: 3.240

10.  Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard.

Authors:  Felix Gembler; Piotr Stawicki; Ivan Volosyak
Journal:  Front Neurosci       Date:  2015-12-22       Impact factor: 4.677

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