A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG
Hybrid brain-computer interface (hBCI) systems that combine steady-state visual evoked potential (SSVEP) and surface electromyography (sEMG) signals have attracted attention of researchers due to the advantage of exhibiting significantly improved system performance. However, almost all existing stud...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10230298/ |
| _version_ | 1827824941642285056 |
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| author | Ruoqing Zhang Guoya Dong Meng Li Zhihua Tang Xiaogang Chen Hongyan Cui |
| author_facet | Ruoqing Zhang Guoya Dong Meng Li Zhihua Tang Xiaogang Chen Hongyan Cui |
| author_sort | Ruoqing Zhang |
| collection | DOAJ |
| description | Hybrid brain-computer interface (hBCI) systems that combine steady-state visual evoked potential (SSVEP) and surface electromyography (sEMG) signals have attracted attention of researchers due to the advantage of exhibiting significantly improved system performance. However, almost all existing studies adopt low-frequency SSVEP to build hBCI. It produces much more visual fatigue than high-frequency SSVEP. Therefore, the current study attempts to build a hBCI based on high-frequency SSVEP and sEMG. With these two signals, this study designed and realized a 32-target hBCI speller system. Thirty-two targets were separated from the middle into two groups. Each side contained 16 sets of targets with different high-frequency visual stimuli (i.e., 31-34.75 Hz with an interval of 0.25 Hz). sEMG was utilized to choose the group and SSVEP was adopted to identify intra-group targets. The filter bank canonical correlation analysis (FBCCA) and the root mean square value (RMS) methods were used to identify signals. Therefore, the proposed system allowed users to operate it without system calibration. A total of 12 healthy subjects participated in online experiment, with an average accuracy of 93.52 ± 1.66% and the average information transfer rate (ITR) reached 93.50 ± 3.10 bits/min. Furthermore, 12 participants perfectly completed the free-spelling tasks. These results of the experiments indicated feasibility and practicality of the proposed hybrid BCI speller system. |
| first_indexed | 2024-03-12T02:34:29Z |
| format | Article |
| id | doaj.art-257b3bc89e0b4192b8aeeada88c556b0 |
| institution | Directory Open Access Journal |
| issn | 1558-0210 |
| language | English |
| last_indexed | 2024-03-12T02:34:29Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj.art-257b3bc89e0b4192b8aeeada88c556b02023-09-04T23:00:06ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1558-02102023-01-01313492350010.1109/TNSRE.2023.330877910230298A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMGRuoqing Zhang0Guoya Dong1https://orcid.org/0000-0002-8980-1757Meng Li2Zhihua Tang3Xiaogang Chen4https://orcid.org/0000-0002-5334-1728Hongyan Cui5Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, ChinaSchool of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin, ChinaInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, ChinaState Grid Zhumadian Power Supply Company, Zhumadian, ChinaInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, ChinaInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, ChinaHybrid brain-computer interface (hBCI) systems that combine steady-state visual evoked potential (SSVEP) and surface electromyography (sEMG) signals have attracted attention of researchers due to the advantage of exhibiting significantly improved system performance. However, almost all existing studies adopt low-frequency SSVEP to build hBCI. It produces much more visual fatigue than high-frequency SSVEP. Therefore, the current study attempts to build a hBCI based on high-frequency SSVEP and sEMG. With these two signals, this study designed and realized a 32-target hBCI speller system. Thirty-two targets were separated from the middle into two groups. Each side contained 16 sets of targets with different high-frequency visual stimuli (i.e., 31-34.75 Hz with an interval of 0.25 Hz). sEMG was utilized to choose the group and SSVEP was adopted to identify intra-group targets. The filter bank canonical correlation analysis (FBCCA) and the root mean square value (RMS) methods were used to identify signals. Therefore, the proposed system allowed users to operate it without system calibration. A total of 12 healthy subjects participated in online experiment, with an average accuracy of 93.52 ± 1.66% and the average information transfer rate (ITR) reached 93.50 ± 3.10 bits/min. Furthermore, 12 participants perfectly completed the free-spelling tasks. These results of the experiments indicated feasibility and practicality of the proposed hybrid BCI speller system.https://ieeexplore.ieee.org/document/10230298/Brain–computer interfacesteady-state visual evoked potentialsurface electromyographyfilter bank canonical correlation analysis |
| spellingShingle | Ruoqing Zhang Guoya Dong Meng Li Zhihua Tang Xiaogang Chen Hongyan Cui A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG IEEE Transactions on Neural Systems and Rehabilitation Engineering Brain–computer interface steady-state visual evoked potential surface electromyography filter bank canonical correlation analysis |
| title | A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG |
| title_full | A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG |
| title_fullStr | A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG |
| title_full_unstemmed | A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG |
| title_short | A Calibration-Free Hybrid BCI Speller System Based on High-Frequency SSVEP and sEMG |
| title_sort | calibration free hybrid bci speller system based on high frequency ssvep and semg |
| topic | Brain–computer interface steady-state visual evoked potential surface electromyography filter bank canonical correlation analysis |
| url | https://ieeexplore.ieee.org/document/10230298/ |
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