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Data Analytics in Steady-State Visual Evoked Potential-based Brain-Computer Interface: A Review

Yue Zhang, Sheng Quan Xie, He Wang, Zhibin Yu, Zhiqiang Zhang
2020 IEEE Sensors Journal  
In this paper, we review the current research in SSVEP-based BCI, focusing on the data analytics that enables continuous, accurate detection of SSVEPs and thus high information transfer rate.  ...  Of various EEG paradigms, steady-state visual evoked potential (SSVEP)-based BCI system which uses multiple visual stimuli (such as LEDs or boxes on a computer screen) flickering at different frequencies  ...  With these approaches, the performance of target detection in SSVEP-based BCI systems has been highly enhanced compared with the CCA.  ... 
doi:10.1109/jsen.2020.3017491 fatcat:uommodmjb5cnzju7me4s2uhxpm

Steady-State Visual Evoked Potential-Based Brain–Computer Interface Using a Novel Visual Stimulus with Quick Response (QR) Code Pattern

Nannaphat Siribunyaphat, Yunyong Punsawad
2022 Sensors  
Two popular SSVEP methods, i.e., power spectral density (PSD) with Welch periodogram and canonical correlation analysis (CCA) with overlapping sliding window, are used to detect SSVEP intensity and response  ...  The findings can be used in the future to implement a real-time, SSVEP-based BCI for verifying user and system performance in actual environments.  ...  In this paper, we propose a new visual stimulus pattern for enhancing a SSVEP-based BCI system.  ... 
doi:10.3390/s22041439 pmid:35214341 pmcid:PMC8877481 fatcat:7zecgcb7ujeofbmia2sievkfuy

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

Mohammad Hadi Mehdizavareh, Sobhan Hemati, Hamid Soltanian-Zadeh, Xiang Gao
2020 PLoS ONE  
However, SSVEP-based methods can be improved in terms of their accuracy and target detection time.  ...  We propose a new method based on canonical correlation analysis (CCA) to integrate subject-specific models and subject-independent information and enhance BCI performance.  ...  Acknowledgments The authors would like to thank the authors of [25] for providing the benchmark dataset freely. Visualization: Mohammad Hadi Mehdizavareh.  ... 
doi:10.1371/journal.pone.0226048 pmid:31935220 pmcid:PMC6959579 fatcat:rkkimklsr5hmbiygdbo7wbydiu

3D Input Convolutional Neural Network for SSVEP Classification in Design of Brain Computer Interface for Patient User

Zeki Oralhan, Burcu Oralhan, Manal M. Khayyat, Sayed Abdel-Khalek, Romany F. Mansour, Deepika Koundal
2022 Computational and Mathematical Methods in Medicine  
Our proposed method is novel and state-of-art model for steady-state visual evoked potential classification.  ...  This research was aimed at presenting performance of 3-dimensional input convolutional neural networks for steady-state visual evoked potential classification in a wireless EEG-based brain-computer interface  ...  Acknowledgments The authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code: (22UQU4400271DSR05) and Taif University Researchers  ... 
doi:10.1155/2022/8452002 pmid:35664638 pmcid:PMC9159868 fatcat:spfya6deync5xnkhqnmitwzknm

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

Masaki Nakanishi, Yijun Wang, Xiaogang Chen, Yu-Te Wang, Xiaorong Gao, Tzyy-Ping Jung
2018 IEEE Transactions on Biomedical Engineering  
This study conducted a comparison of BCI performance between the proposed TRCA-based method and an extended canonical correlation analysis (CCA)-based method using a 40-class SSVEP dataset recorded from  ...  Objective-This study proposes and evaluates a novel data-driven spatial filtering approach for enhancing steady-state visual evoked potentials (SSVEPs) detection towards a high-speed braincomputer interface  ...  CONCLUSIONS A novel SSVEP detection method using the TRCA-based spatial filters was proposed and evaluated in this paper.  ... 
doi:10.1109/tbme.2017.2694818 pmid:28436836 pmcid:PMC5783827 fatcat:37vclinoejbalpzk54gihcbjya

Control of a Robotic Arm With an Optimized Common Template-Based CCA Method for SSVEP-Based BCI

Fang Peng, Ming Li, Su-na Zhao, Qinyi Xu, Jiajun Xu, Haozhen Wu
2022 Frontiers in Neurorobotics  
The comparison results of offline experimental based on a public benchmark dataset indicated that the proposed OCT-CCA method achieved significant improvement of detection accuracy in contrast to CCA and  ...  was applied to enhance the SSVEP recognition accuracy, called OCT-based canonical correlation analysis (OCT-CCA).  ...  In summary, a novel OCT-based CCA method was proposed for target identification to perform the reaching tasks of a 7-DOF robotic arm in the 3D space.  ... 
doi:10.3389/fnbot.2022.855825 pmid:35370596 pmcid:PMC8965569 fatcat:kvmfy4okefeknix3wyhdu5mnee

Multi-Objective Optimisation for SSVEP Detection

Yue Zhang, Zhiqiang Zhang, Shengquan Xie
2021 2021 IEEE 17th International Conference on Wearable and Implantable Body Sensor Networks (BSN)  
In this paper, we propose a novel multi-objective optimisation-based spatial filtering method for enhancing SSVEP recognition.  ...  Data-driven spatial filtering approaches have been widely used for steady-state visual evoked potentials (SSVEPs) detection toward the brain-computer interface (BCI).  ...  CONCLUSION A novel multiple objectives optimisation-based spatial filtering method was proposed to improve the recognition performance for the SSVEP-based BCI system.  ... 
doi:10.1109/bsn51625.2021.9507041 fatcat:zhmvyjjc6rgxrdcrcgxdlwebde

Cross-Subject Assistance: Inter-and Intra-Subject Maximal Correlation for Enhancing the Performance of SSVEP-Based BCIs

Haoran Wang, Yaoru Sun, Fang Wang, Lei Cao, Wei Zhou, Zijian Wang, Shiyi Chen
2021 IEEE transactions on neural systems and rehabilitation engineering  
For addressing this issue, this study proposes a novel inter- and intra-subject maximal correlation (IISMC) method to enhance the robustness of SSVEP recognition via employing the inter- and intra-subject  ...  The current state-of-the-art methods significantly improve the detection performance of the steady-state visual evoked potentials (SSVEPs) by using the individual calibration data.  ...  CONCLUSION This study proposed a novel IISMC-based cross-subject assistance framework to enhance the performance of SSVEP-based BCI.  ... 
doi:10.1109/tnsre.2021.3057938 pmid:33556014 fatcat:c3k5lnt6kvgvjjkvdeutlldmjy

A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain–computer interface

Yi-Feng Chen, Kiran Atal, Sheng-Quan Xie, Quan Liu
2017 Journal of Neural Engineering  
study, a novel MEMD method for improving the performance of SSVEP-based BCI is 38 introduced.  ...  In a SSVEP-based BCI, 40 the MEMD algorithm enhanced multi-component extraction of SSVEP responses buried in 41 broadband background activities.  ... 
doi:10.1088/1741-2552/aa6a23 pmid:28357991 fatcat:ocpbieaxu5bgrkq66edr3vqaly

Noninvasive Electroencephalogram Based Control of a Robotic Arm for Writing Task Using Hybrid BCI System

Qiang Gao, Lixiang Dou, Abdelkader Nasreddine Belkacem, Chao Chen
2017 BioMed Research International  
A novel hybrid brain-computer interface (BCI) based on the electroencephalogram (EEG) signal which consists of a motor imagery- (MI-) based online interactive brain-controlled switch, "teeth clenching"  ...  state detector, and a steady-state visual evoked potential- (SSVEP-) based BCI was proposed to provide multidimensional BCI control.  ...  Conclusions This paper presented a combination of synchronous and asynchronous control using a novel hybrid EEG-EMG-based BCI which consists of motor imagery, muscle artifacts, and SSVEP to provide a multidimensional  ... 
doi:10.1155/2017/8316485 pmid:28660211 pmcid:PMC5474280 fatcat:jbjqsgte45e67jr22m5nvxtmlm

Improvement of the Classification Accuracy of Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces by Combining L1-MCCA with SVM

Yuhang Gao, Juanning Si, Sijin Wu, Weixian Li, Hao Liu, Jianhu Chen, Qing He, Yujin Zhang
2021 Applied Sciences  
Canonical correlation analysis (CCA) has been used for the steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) for a long time.  ...  This accuracy is higher than that of the traditional CCA and PSD methods.  ...  Comparison of PSDA and CCA detection methods in a SSVEP-based BCI-system. Cent. Telemat. Inf. Technol. Univ. Twente 2011, 78, 183–192. 26. Wang, R.; Wen, W.; Iramina, K.; Ge, S.  ... 
doi:10.3390/app112311453 fatcat:suepexv4p5afvlqxorfwjd2qfe

Hierarchical feature fusion framework for frequency recognition in SSVEP-based BCIs [article]

Yangsong Zhang, Erwei Yin, Fali Li, Yu Zhang, Daqing Guo, Dezhong Yao, Peng Xu
2019 arXiv   pre-print
Accordingly, the proposed framework holds promise to enhance the performance of frequency recognition methods in SSVEP-based BCIs.  ...  Effective frequency recognition algorithms are critical in steady-state visual evoked potential (SSVEP) based brain-computer interfaces (BCIs).  ...  This novel framework may be used to develop efficient methods for frequency recognition in SSVEP-based BCIs. Fig. 1 1 Fig. 1).  ... 
arXiv:1812.10227v2 fatcat:ug52hnh5mzamnk5bhmtxcdvzui

Enhancing Performance of SSVEP-Based Visual Acuity via Spatial Filtering

Xiaowei Zheng, Guanghua Xu, Chengcheng Han, Peiyuan Tian, Kai Zhang, Renghao Liang, Yaguang Jia, Wenqiang Yan, Chenghang Du, Sicong Zhang
2021 Frontiers in Neuroscience  
The study proved that the performance of SSVEP-based visual acuity can be enhanced by spatial filtering methods of CCA and MSI and also recommended CCA as the spatial filtering method for multielectrode  ...  The purpose of this study was to enhance the performance of steady-state visual evoked potential (SSVEP)-based visual acuity assessment with spatial filtering methods.  ...  A survey on training of feature extraction methods for SSVEP-based BCIs. J. Neural.  ... 
doi:10.3389/fnins.2021.716051 pmid:34489633 pmcid:PMC8417433 fatcat:7xhkn4ljxbcdpfuwpd2h3sqsre

A Minimally Invasive Low-Power Platform for Real-Time Brain Computer Interaction based on Canonical Correlation Analysis

Mattia Salvaro, Simone Benatti, Victor Kartsch, Marco Guermandi, Luca Benini
2018 IEEE Internet of Things Journal  
The system is based on Visual Evoked Potentials detection and runs the Canonical Correlation Analysis (CCA) on a low power microcontroller.  ...  Acting directly by decoding neural activity is a very natural way of interaction and one of the fundamental paradigms of Brain Computer Interfaces (BCIs) as well.  ...  The state-of-the-art method for SSVEP-based BCIs [54] is named Canonical Correlation Analysis (CCA).  ... 
doi:10.1109/jiot.2018.2866341 fatcat:vschftp7nbbpjokblpsgylbtdy

A Hybrid BCI Based on SSVEP and EOG for Robotic Arm Control

Yuanlu Zhu, Ying Li, Jinling Lu, Pengcheng Li
2020 Frontiers in Neurorobotics  
We designed an EOG-based switch which used a triple blink to either activate or deactivate the flash of SSVEP-based BCI.  ...  The basic control of a robotic arm with six degrees of freedom was a steady-state visual evoked potential (SSVEP) based BCI with fifteen target classes.  ...  ACKNOWLEDGMENTS The authors would like to thank the volunteers who participated in the BCI experiments.  ... 
doi:10.3389/fnbot.2020.583641 pmid:33328950 pmcid:PMC7714925 fatcat:jlptdzoknjh2xlawpfjitw2fj4
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