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Pitt KM, McCarthy JW. Strategies for highlighting items within visual scene displays to support augmentative and alternative communication access for those with physical impairments. Disabil Rehabil Assist Technol 2023; 18:1319-1329. [PMID: 34788177 DOI: 10.1080/17483107.2021.2003455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 11/02/2021] [Indexed: 10/19/2022]
Abstract
PURPOSE In contrast to the traditional grid-based display, visual scene displays (VSDs) offer a new paradigm for aided communication. For individuals who cannot select items from an AAC display by direct selection due to physical impairments, AAC access can be supported via methods such as item scanning. Item scanning sequentially highlights items on a display until the individual signals for selection. How items are highlighted or scanned for AAC access can impact performance outcomes. Further, the effectiveness of a VSD interface may be enhanced through consultation with experts in visual communication. Therefore, to support AAC access for those with physical impairments, the aim of this study was to evaluate the perspectives of experts in visual communication regarding effective methods for highlighting VSD elements. METHODS Thirteen participants with expertise related to visual communication (e.g., photographers, artists) completed semi-structured interviews regarding techniques for item highlighting. RESULTS Study findings identified four main themes to inform how AAC items may be highlighted or scanned, including (1) use of contrast related to light and dark, (2) use of contrast as it relates to colour, (3) outline highlighting, and (4) use of scale and motion. CONCLUSION By identifying how compositional techniques can be utilized to highlight VSD elements, study findings may inform current practice for scanning-based AAC access, along with other selection techniques where feedback or highlighting is used (e.g., eye-gaze, brain-computer interface). Further, avenues for just-in-time programming are discussed to support effective implementation for those with physical impairments.IMPLICATIONS FOR REHABILITATIONFindings identify multiple potential techniques to improve scanning through items in a photograph for individuals with severe motor impairments using alternative access strategies.Study findings inform current practice for scanning-based AAC access, along with other selection techniques where feedback or highlighting is used (e.g., eye-gaze, brain-computer interface).Avenues for just in time programming of AAC displays are discussed to decrease programming demands and support effective implementation of study findings.
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Affiliation(s)
- Kevin M Pitt
- Department of Special Education and Communication Disorders, University of Nebraska-Lincoln, Lincoln, NE, USA
| | - John W McCarthy
- Division of Communication Sciences and Disorders, Ohio University, Athens, OH, USA
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2
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Pan J, Chen X, Ban N, He J, Chen J, Huang H. Advances in P300 brain-computer interface spellers: toward paradigm design and performance evaluation. Front Hum Neurosci 2022; 16:1077717. [PMID: 36618996 PMCID: PMC9810759 DOI: 10.3389/fnhum.2022.1077717] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 11/23/2022] [Indexed: 12/24/2022] Open
Abstract
A brain-computer interface (BCI) is a non-muscular communication technology that provides an information exchange channel for our brains and external devices. During the decades, BCI has made noticeable progress and has been applied in many fields. One of the most traditional BCI applications is the BCI speller. This article primarily discusses the progress of research into P300 BCI spellers and reviews four types of P300 spellers: single-modal P300 spellers, P300 spellers based on multiple brain patterns, P300 spellers with multisensory stimuli, and P300 spellers with multiple intelligent techniques. For each type of P300 speller, we further review several representative P300 spellers, including their design principles, paradigms, algorithms, experimental performance, and corresponding advantages. We particularly emphasized the paradigm design ideas, including the overall layout, individual symbol shapes and stimulus forms. Furthermore, several important issues and research guidance for the P300 speller were identified. We hope that this review can assist researchers in learning the new ideas of these novel P300 spellers and enhance their practical application capability.
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Affiliation(s)
- Jiahui Pan
- *Correspondence: Jiahui Pan Haiyun Huang
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3
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Neuropsychological and Neurophysiological Mechanisms behind Flickering Light Stimulus Processing. BIOLOGY 2022; 11:biology11121720. [PMID: 36552230 PMCID: PMC9774938 DOI: 10.3390/biology11121720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 11/29/2022]
Abstract
The aim of this review is to summarise current knowledge about flickering light and the underlying processes that occur during its processing in the brain. Despite the growing interest in the topic of flickering light, its clinical applications are still not well understood. Studies using EEG indicate an appearing synchronisation of brain wave frequencies with the frequency of flickering light, and hopefully, it could be used in memory therapy, among other applications. Some researchers have focused on using the flicker test as an indicator of arousal, which may be useful in clinical studies if the background for such a relationship is described. Since flicker testing has a risk of inducing epileptic seizures, however, every effort must be made to avoid high-risk combinations, which include, for example, red-blue light flashing at 15 Hz. Future research should focus on the usage of neuroimaging methods to describe the specific neuropsychological and neurophysiological processes occurring in the brain during the processing of flickering light so that its clinical utility can be preliminarily determined and randomised clinical trials can be initiated to test existing reports.
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4
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Rathi N, Singla R, Tiwari S. A comparative study of classification methods for designing a pictorial P300-based authentication system. Med Biol Eng Comput 2022; 60:2899-2916. [DOI: 10.1007/s11517-022-02626-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 06/24/2022] [Indexed: 10/15/2022]
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Palumbo A, Ielpo N, Calabrese B. An FPGA-Embedded Brain-Computer Interface System to Support Individual Autonomy in Locked-In Individuals. SENSORS (BASEL, SWITZERLAND) 2022; 22:318. [PMID: 35009860 PMCID: PMC8749705 DOI: 10.3390/s22010318] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/25/2021] [Accepted: 12/29/2021] [Indexed: 06/14/2023]
Abstract
Brain-computer interfaces (BCI) can detect specific EEG patterns and translate them into control signals for external devices by providing people suffering from severe motor disabilities with an alternative/additional channel to communicate and interact with the outer world. Many EEG-based BCIs rely on the P300 event-related potentials, mainly because they require training times for the user relatively short and provide higher selection speed. This paper proposes a P300-based portable embedded BCI system realized through an embedded hardware platform based on FPGA (field-programmable gate array), ensuring flexibility, reliability, and high-performance features. The system acquires EEG data during user visual stimulation and processes them in a real-time way to correctly detect and recognize the EEG features. The BCI system is designed to allow to user to perform communication and domotic controls.
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6
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Gutierrez-Martinez J, Mercado-Gutierrez JA, Carvajal-Gámez BE, Rosas-Trigueros JL, Contreras-Martinez AE. Artificial Intelligence Algorithms in Visual Evoked Potential-Based Brain-Computer Interfaces for Motor Rehabilitation Applications: Systematic Review and Future Directions. Front Hum Neurosci 2021; 15:772837. [PMID: 34899220 PMCID: PMC8656949 DOI: 10.3389/fnhum.2021.772837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/04/2021] [Indexed: 11/13/2022] Open
Abstract
Brain-Computer Interface (BCI) is a technology that uses electroencephalographic (EEG) signals to control external devices, such as Functional Electrical Stimulation (FES). Visual BCI paradigms based on P300 and Steady State Visually Evoked potentials (SSVEP) have shown high potential for clinical purposes. Numerous studies have been published on P300- and SSVEP-based non-invasive BCIs, but many of them present two shortcomings: (1) they are not aimed for motor rehabilitation applications, and (2) they do not report in detail the artificial intelligence (AI) methods used for classification, or their performance metrics. To address this gap, in this paper the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was applied to prepare a systematic literature review (SLR). Papers older than 10 years, repeated or not related to a motor rehabilitation application, were excluded. Of all the studies, 51.02% referred to theoretical analysis of classification algorithms. Of the remaining, 28.48% were for spelling, 12.73% for diverse applications (control of wheelchair or home appliances), and only 7.77% were focused on motor rehabilitation. After the inclusion and exclusion criteria were applied and quality screening was performed, 34 articles were selected. Of them, 26.47% used the P300 and 55.8% the SSVEP signal. Five applications categories were established: Rehabilitation Systems (17.64%), Virtual Reality environments (23.52%), FES (17.64%), Orthosis (29.41%), and Prosthesis (11.76%). Of all the works, only four performed tests with patients. The most reported machine learning (ML) algorithms used for classification were linear discriminant analysis (LDA) (48.64%) and support vector machine (16.21%), while only one study used a deep learning algorithm: a Convolutional Neural Network (CNN). The reported accuracy ranged from 38.02 to 100%, and the Information Transfer Rate from 1.55 to 49.25 bits per minute. While LDA is still the most used AI algorithm, CNN has shown promising results, but due to their high technical implementation requirements, many researchers do not justify its implementation as worthwile. To achieve quick and accurate online BCIs for motor rehabilitation applications, future works on SSVEP-, P300-based and hybrid BCIs should focus on optimizing the visual stimulation module and the training stage of ML and DL algorithms.
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Affiliation(s)
- Josefina Gutierrez-Martinez
- División de Investigación en Ingeniería Médica, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City, Mexico
| | - Jorge A. Mercado-Gutierrez
- División de Investigación en Ingeniería Médica, Instituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City, Mexico
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7
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Zhang X, Jin J, Li S, Wang X, Cichocki A. Evaluation of color modulation in visual P300-speller using new stimulus patterns. Cogn Neurodyn 2021; 15:873-886. [PMID: 34603548 DOI: 10.1007/s11571-021-09669-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/04/2021] [Accepted: 02/04/2021] [Indexed: 02/07/2023] Open
Abstract
Objective The stimulus color of P300-BCI systems has been successfully modified. However, the effects of different color combinations have not been widely investigated. In this study, we designed new stimulus patterns to evaluate the influence of color modulation on the BCI performance and waveforms of the evoked related potential (ERP).Methods Comparison was performed for three new stimulus patterns consisting of red face and colored block-shape, namely, red face with a white rectangle (RFW), red face with a blue rectangle (RFB), and red face with a red rectangle (RFR). Bayesian linear discriminant analysis (BLDA) was used to construct the individual classifier model. Repeated-measures ANOVA and Bonferroni correction were applied for statistical analysis. Results The RFW pattern obtained the highest average online accuracy with 96.94%, and those of RFR and RFB patterns were 93.61% and of 92.22% respectively. Significant differences in online accuracy and information transfer rate (ITR) were found between RFW and RFR patterns (p < 0.05). Conclusion Compared with RFR and RFB patterns, RFW yielded the best performance in P300-BCI. These new stimulus patterns with different color combinations have considerable importance to BCI applications and user-friendliness.
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Affiliation(s)
- Xinru Zhang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Jing Jin
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Shurui Li
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Xingyu Wang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Andrzej Cichocki
- Skolkovo Institute of Science and Technology (Skoltech), 121205 Moscow, Russia.,Nicolaus Copernicus University (UMK), 87-100 Torun, Poland
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8
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Onishi A. Brain-computer interface with rapid serial multimodal presentation using artificial facial images and voice. Comput Biol Med 2021; 136:104685. [PMID: 34343888 DOI: 10.1016/j.compbiomed.2021.104685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 07/22/2021] [Accepted: 07/22/2021] [Indexed: 10/20/2022]
Abstract
Electroencephalography (EEG) signals elicited by multimodal stimuli can drive brain-computer interfaces (BCIs), and research has demonstrated that visual and auditory stimuli can be employed simultaneously to improve BCI performance. However, no studies have investigated the effect of multimodal stimuli in rapid serial visual presentation (RSVP) BCIs. The present study proposed a rapid serial multimodal presentation (RSMP) BCI that incorporates artificial facial images and artificial voice stimuli. To clarify the effect of audiovisual stimuli on the RSMP BCI, scrambled images and masked sounds were applied instead of visual and auditory stimuli, respectively. The findings indicated that the audiovisual stimuli improved performance of the RSMP BCI, and that P300 at Pz contributed to classification accuracy. Online accuracy of the BCI reached 85.7 ± 11.5 %. Taken together, these findings may aid in the development of better gaze-independent BCI systems.
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Affiliation(s)
- A Onishi
- Department of Electronic Systems Engineering, National Institute of Technology, Kagawa College, 551, Kohda, Takuma-cho, Mitoyo-shi, Kagawa, 769-1192, Japan; Center for Frontier Medical Engineering, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba, Japan.
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Sutaj N, Walchshofer M, Schreiner L, Turchet L, Pretl H, Guger C. Evaluating a Novel P300-Based Real-Time Image Ranking BCI. FRONTIERS IN COMPUTER SCIENCE 2021. [DOI: 10.3389/fcomp.2021.661224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Brain–computer interfaces (BCIs) establish communication between a human brain and a computer or external devices by translating the electroencephalography (EEG) signal into computer commands. After stimulating a sensory organ, a positive deflection of the EEG signal between 250 and 700 ms can be measured. This signal component of the event-related potential (ERP) is called “P300.” Numerous studies have provided evidence that the P300 amplitude and latency are linked to sensory perception, engagement, and cognition. Combining the advances in technology, classification methods, and signal processing, we developed a novel image ranking system called the Unicorn Blondy Check. In this study, the application was tested on 21 subjects using three different visual oddball paradigms. Two consisted of female faces and gray-scale images, while the third test paradigm consisted of familiar and unfamiliar faces. The images were displayed for a duration of 150 ms in a randomized order. The system was trained using 50 trials and tested with 30 trials. The EEG data were acquired using the Unicorn Hybrid Black eight-channel BCI system. These synchronized recordings were analyzed, and the achieved classification accuracies were calculated. The EEG signal was averaged over all participants and for every paradigm separately. Analysis of the EEG data revealed a significant shift in the P300 latency dependent on the paradigm and decreased amplitude for a lower target to non-target ratio. The image ranking application achieved a mean accuracy of 100 and 95.5% for ranking female faces above gray-scale images with ratios of 1:11 and 5:11, respectively. In the case of four familiar faces to 24 unfamiliar faces, 86.4% was reached. The obtained results illustrate this novel system’s functionality due to accuracies above chance levels for all subjects.
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10
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Yu X, da Silva-Sauer L, Donchin E. Habituation of P300 in the Use of P300-based Brain-Computer Interface Spellers: Individuals With Amyotrophic Lateral Sclerosis Versus Age-Matched Controls. Clin EEG Neurosci 2021; 52:221-230. [PMID: 32419492 DOI: 10.1177/1550059420918755] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The P300-based brain-computer interface speller can provide motor independent communication to individuals with amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disorder that affects the motor system. P300 amplitude stability is critical for operation of the P300 speller. The P300 has good long-term stability, but to our knowledge, short-term habituation in the P300 speller has not been studied. In the current study, 15 participants: 8 ALS patients and 7 age-matched healthy volunteers (HVs), used 2 versions of P300 spellers, Face speller and Flash speller, each for 30 minutes. The ALS group performed as well as the HVs in both spellers and HVs did better with the Face speller than Flash speller while the ALS group performed equally well in both spellers. Neither intra-run P300 habituation nor inter-run P300 habituation was found. The P300 speller could be a reliable communication device for individuals with ALS.
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Affiliation(s)
- Xiaoqian Yu
- Department of Psychology, 7831University of South Florida, Tampa, FL, USA
| | - Leandro da Silva-Sauer
- Department of Psychology, 7831University of South Florida, Tampa, FL, USA.,123204Federal University of Paraiba, João Pessoa, Paraiba, Brazil
| | - Emanuel Donchin
- Department of Psychology, 7831University of South Florida, Tampa, FL, USA
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11
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Shirzhiyan Z, Keihani A, Farahi M, Shamsi E, GolMohammadi M, Mahnam A, Haidari MR, Jafari AH. Toward New Modalities in VEP-Based BCI Applications Using Dynamical Stimuli: Introducing Quasi-Periodic and Chaotic VEP-Based BCI. Front Neurosci 2020; 14:534619. [PMID: 33328841 PMCID: PMC7718037 DOI: 10.3389/fnins.2020.534619] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 09/15/2020] [Indexed: 11/13/2022] Open
Abstract
Visual evoked potentials (VEPs) to periodic stimuli are commonly used in brain computer interfaces for their favorable properties such as high target identification accuracy, less training time, and low surrounding target interference. Conventional periodic stimuli can lead to subjective visual fatigue due to continuous and high contrast stimulation. In this study, we compared quasi-periodic and chaotic complex stimuli to common periodic stimuli for use with VEP-based brain computer interfaces (BCIs). Canonical correlation analysis (CCA) and coherence methods were used to evaluate the performance of the three stimulus groups. Subjective fatigue caused by the presented stimuli was evaluated by the Visual Analogue Scale (VAS). Using CCA with the M2 template approach, target identification accuracy was highest for the chaotic stimuli (M = 86.8, SE = 1.8) compared to the quasi-periodic (M = 78.1, SE = 2.6, p = 0.008) and periodic (M = 64.3, SE = 1.9, p = 0.0001) stimulus groups. The evaluation of fatigue rates revealed that the chaotic stimuli caused less fatigue compared to the quasi-periodic (p = 0.001) and periodic (p = 0.0001) stimulus groups. In addition, the quasi-periodic stimuli led to lower fatigue rates compared to the periodic stimuli (p = 0.011). We conclude that the target identification results were better for the chaotic group compared to the other two stimulus groups with CCA. In addition, the chaotic stimuli led to a less subjective visual fatigue compared to the periodic and quasi-periodic stimuli and can be suitable for designing new comfortable VEP-based BCIs.
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Affiliation(s)
- Zahra Shirzhiyan
- Computational Neuroscience, Institute of Medical Technology, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany.,Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmadreza Keihani
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
| | - Morteza Farahi
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
| | - Elham Shamsi
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mina GolMohammadi
- Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
| | - Amin Mahnam
- Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
| | - Mohsen Reza Haidari
- Section of Neuroscience, Department of Neurology, Faculty of Medicine, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Amir Homayoun Jafari
- Department of Medical Physics & Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Research Center for Biomedical Technologies and Robotics (RCBTR), Tehran University of Medical Sciences, Tehran, Iran
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Reichert C, Tellez Ceja IF, Sweeney-Reed CM, Heinze HJ, Hinrichs H, Dürschmid S. Impact of Stimulus Features on the Performance of a Gaze-Independent Brain-Computer Interface Based on Covert Spatial Attention Shifts. Front Neurosci 2020; 14:591777. [PMID: 33335470 PMCID: PMC7736242 DOI: 10.3389/fnins.2020.591777] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 11/10/2020] [Indexed: 11/18/2022] Open
Abstract
Regaining communication abilities in patients who are unable to speak or move is one of the main goals in decoding brain waves for brain-computer interface (BCI) control. Many BCI approaches designed for communication rely on attention to visual stimuli, commonly applying an oddball paradigm, and require both eye movements and adequate visual acuity. These abilities may, however, be absent in patients who depend on BCI communication. We have therefore developed a response-based communication BCI, which is independent of gaze shifts but utilizes covert shifts of attention to the left or right visual field. We recorded the electroencephalogram (EEG) from 29 channels and coregistered the vertical and horizontal electrooculogram. Data-driven decoding of small attention-based differences between the hemispheres, also known as N2pc, was performed using 14 posterior channels, which are expected to reflect correlates of visual spatial attention. Eighteen healthy participants responded to 120 statements by covertly directing attention to one of two colored symbols (green and red crosses for "yes" and "no," respectively), presented in the user's left and right visual field, respectively, while maintaining central gaze fixation. On average across participants, 88.5% (std: 7.8%) of responses were correctly decoded online. In order to investigate the potential influence of stimulus features on accuracy, we presented the symbols with different visual angles, by altering symbol size and eccentricity. The offline analysis revealed that stimulus features have a minimal impact on the controllability of the BCI. Hence, we show with our novel approach that spatial attention to a colored symbol is a robust method with which to control a BCI, which has the potential to support severely paralyzed people with impaired eye movements and low visual acuity in communicating with their environment.
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Affiliation(s)
- Christoph Reichert
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Research Campus STIMULATE, Magdeburg, Germany
| | | | - Catherine M. Sweeney-Reed
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Hans-Jochen Heinze
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Hermann Hinrichs
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Research Campus STIMULATE, Magdeburg, Germany
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Stefan Dürschmid
- Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
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13
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Zhu Y, Li Y, Lu J, Li P. A Hybrid BCI Based on SSVEP and EOG for Robotic Arm Control. Front Neurorobot 2020; 14:583641. [PMID: 33328950 PMCID: PMC7714925 DOI: 10.3389/fnbot.2020.583641] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 10/26/2020] [Indexed: 11/21/2022] Open
Abstract
Brain-computer interface (BCI) for robotic arm control has been studied to improve the life quality of people with severe motor disabilities. There are still challenges for robotic arm control in accomplishing a complex task with a series of actions. An efficient switch and a timely cancel command are helpful in the application of robotic arm. Based on the above, we proposed an asynchronous hybrid BCI in this study. 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. We designed an EOG-based switch which used a triple blink to either activate or deactivate the flash of SSVEP-based BCI. Stopping flash in the idle state can help to reduce visual fatigue and false activation rate (FAR). Additionally, users were allowed to cancel the current command simply by a wink in the feedback phase to avoid executing the incorrect command. Fifteen subjects participated and completed the experiments. The cue-based experiment obtained an average accuracy of 92.09%, and the information transfer rates (ITR) resulted in 35.98 bits/min. The mean FAR of the switch was 0.01/min. Furthermore, all subjects succeeded in asynchronously operating the robotic arm to grasp, lift, and move a target object from the initial position to a specific location. The results indicated the feasibility of the combination of EOG and SSVEP signals and the flexibility of EOG signal in BCI to complete a complicated task of robotic arm control.
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Affiliation(s)
- Yuanlu Zhu
- Wuhan National Laboratory for Optoelectronics, Britton Chance Center of Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Li
- Wuhan National Laboratory for Optoelectronics, Britton Chance Center of Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Jinling Lu
- Wuhan National Laboratory for Optoelectronics, Britton Chance Center of Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China
| | - Pengcheng Li
- Wuhan National Laboratory for Optoelectronics, Britton Chance Center of Biomedical Photonics, Huazhong University of Science and Technology, Wuhan, China.,MoE Key Laboratory for Biomedical Photonics, School of Engineering Sciences, Huazhong University of Science and Technology, Wuhan, China.,Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Suzhou, China
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14
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Fried-Oken M, Kinsella M, Peters B, Eddy B, Wojciechowski B. Human visual skills for brain-computer interface use: a tutorial. Disabil Rehabil Assist Technol 2020; 15:799-809. [PMID: 32476516 DOI: 10.1080/17483107.2020.1754929] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background and objectives: Many brain-computer interfaces (BCIs) for people with severe disabilities present stimuli in the visual modality with little consideration of the visual skills required for successful use. The primary objective of this tutorial is to present researchers and clinical professionals with basic information about the visual skills needed for functional use of visual BCIs, and to offer modifications that would render BCI technology more accessible for persons with vision impairments.Methods: First, we provide a background on BCIs that rely on a visual interface. We then describe the visual skills required for BCI technologies that are used for augmentative and alternative communication (AAC), as well as common eye conditions or impairments that can impact the user's performance. We summarize screening tools that can be administered by the non-eye care professional in a research or clinical setting, as well as the role of the eye care professional. Finally, we explore potential BCI design modifications to compensate for identified functional impairments. Information was generated from literature review and the clinical experience of vision experts.Results and conclusions: This in-depth description culminates in foundational information about visual skills and functional visual impairments that affect the design and use of visual interfaces for BCI technologies. The visual interface is a critical component of successful BCI systems. We can determine a BCI system for potential users with visual impairments and design BCI visual interfaces based on sound anatomical and physiological visual clinical science.Implications for RehabilitationAs brain-computer interfaces (BCIs) become possible access methods for people with severe motor impairments, it is critical that clinicians have a basic knowledge of the visual skills necessary for use of visual BCI interfaces.Rehabilitation providers must have a knowledge of objectively gathering information regarding a potential BCI user's functional visual skills.Rehabilitation providers must understand how to modify BCI visual interfaces for the potential user with visual impairments.Rehabilitation scientists should understand the visual demands of BCIs as they develop and evaluate these new access methods.
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Affiliation(s)
- Melanie Fried-Oken
- Departments of Neurology, Pediatrics, Biomedical Engineering, and Otolaryngology, Oregon Health & Science University, Portland, OR, USA.,Institute on Development and Disability, Oregon Health & Science University, Portland, OR, USA
| | - Michelle Kinsella
- Institute on Development and Disability, Oregon Health & Science University, Portland, OR, USA
| | - Betts Peters
- Institute on Development and Disability, Oregon Health & Science University, Portland, OR, USA
| | - Brandon Eddy
- Institute on Development and Disability, Oregon Health & Science University, Portland, OR, USA.,Department of Speech and Hearing Sciences, Portland State University, Portland, OR, USA
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15
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Li S, Jin J, Daly I, Zuo C, Wang X, Cichocki A. Comparison of the ERP-Based BCI Performance Among Chromatic (RGB) Semitransparent Face Patterns. Front Neurosci 2020; 14:54. [PMID: 32082118 PMCID: PMC7006297 DOI: 10.3389/fnins.2020.00054] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 01/14/2020] [Indexed: 11/18/2022] Open
Abstract
Objective Previous studies have shown that combing with color properties may be used as part of the display presented to BCI users in order to improve performance. Build on this, we explored the effects of combinations of face stimuli with three primary colors (RGB) on BCI performance which is assessed by classification accuracy and information transfer rate (ITR). Furthermore, we analyzed the waveforms of three patterns. Methods We compared three patterns in which semitransparent face is overlaid three primary colors as stimuli: red semitransparent face (RSF), green semitransparent face (GSF), and blue semitransparent face (BSF). Bayesian linear discriminant analysis (BLDA) was used to construct the individual classifier model. In addition, a Repeated-measures ANOVA (RM-ANOVA) and Bonferroni correction were chosen for statistical analysis. Results The results indicated that the RSF pattern achieved the highest online averaged accuracy with 93.89%, followed by the GSF pattern with 87.78%, while the lowest performance was caused by the BSF pattern with an accuracy of 81.39%. Furthermore, significant differences in classification accuracy and ITR were found between RSF and GSF (p < 0.05) and between RSF and BSF patterns (p < 0.05). Conclusion The semitransparent faces colored red (RSF) pattern yielded the best performance of the three patterns. The proposed patterns based on ERP-BCI system have a clinically significant impact by increasing communication speed and accuracy of the P300-speller for patients with severe motor impairment.
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Affiliation(s)
- Shurui Li
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Jing Jin
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Ian Daly
- Brain-Computer Interfacing and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom
| | - Cili Zuo
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Xingyu Wang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Andrzej Cichocki
- Skolkowo Institute of Science and Technology, Moscow, Russia.,Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland.,Department of Informatics, Nicolaus Copernicus University, Toruń, Poland
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16
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Jin J, Li S, Daly I, Miao Y, Liu C, Wang X, Cichocki A. The Study of Generic Model Set for Reducing Calibration Time in P300-Based Brain–Computer Interface. IEEE Trans Neural Syst Rehabil Eng 2020; 28:3-12. [DOI: 10.1109/tnsre.2019.2956488] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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17
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Lu Z, Li Q, Gao N, Yang J, Bai O. Happy emotion cognition of bimodal audiovisual stimuli optimizes the performance of the P300 speller. Brain Behav 2019; 9:e01479. [PMID: 31729840 PMCID: PMC6908870 DOI: 10.1002/brb3.1479] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 09/17/2019] [Accepted: 10/26/2019] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE Prior studies of emotional cognition have found that emotion-based bimodal face and voice stimuli can elicit larger event-related potential (ERP) amplitudes and enhance neural responses compared with visual-only emotional face stimuli. Recent studies on brain-computer interface have shown that emotional face stimuli have significantly improved the performance of the traditional P300 speller system, but its performance needs to be further improved for practical applications. Therefore, we herein propose a novel audiovisual P300 speller based on bimodal emotional cognition to further improve the performance of the P300 system. METHODS The audiovisual P300 speller we proposed is based on happy emotions, with visual and auditory stimuli that consist of several pairs of smiling faces and audible chuckles (E-AV spelling paradigm) of different ages and sexes. The control paradigm was the visual-only emotional face P300 speller (E-V spelling paradigm). RESULTS We compared the ERP amplitudes, accuracy, and raw bit rate between the E-AV and E-V spelling paradigms. The target stimuli elicited significantly increased P300 amplitudes (p < .05) and P600 amplitudes (p < .05) in the E-AV spelling paradigm compared with those in the E-V paradigm. The E-AV spelling paradigm also significantly improved the spelling accuracy and the raw bit rate compared with those in the E-V paradigm at one superposition (p < .05) and at two superpositions (p < .05). SIGNIFICANCE The proposed emotion-based audiovisual spelling paradigm not only significantly improves the performance of the P300 speller, but also provides a basis for the development of various bimodal P300 speller systems, which is a step forward in the clinical application of brain-computer interfaces.
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Affiliation(s)
- Zhaohua Lu
- School of Computer Science and TechnologyChangchun University of Science and TechnologyChangchunChina
| | - Qi Li
- School of Computer Science and TechnologyChangchun University of Science and TechnologyChangchunChina
| | - Ning Gao
- School of Computer Science and TechnologyChangchun University of Science and TechnologyChangchunChina
| | - Jingjing Yang
- School of Computer Science and TechnologyChangchun University of Science and TechnologyChangchunChina
| | - Ou Bai
- Department of Electrical and Computer EngineeringFlorida International UniversityMiamiFLUSA
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18
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Lu Z, Li Q, Gao N, Yang J, Bai O. A Novel Audiovisual P300-Speller Paradigm Based on Cross-Modal Spatial and Semantic Congruence. Front Neurosci 2019; 13:1040. [PMID: 31611770 PMCID: PMC6777004 DOI: 10.3389/fnins.2019.01040] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Accepted: 09/13/2019] [Indexed: 11/19/2022] Open
Abstract
Objective Although many studies have attempted to improve the performance of the visual-based P300-speller system, its performance is still not satisfactory. The current system has limitations for patients with neurodegenerative diseases, in which muscular control of the eyes may be impaired or deteriorate over time. Some studies have shown that the audiovisual stimuli with spatial and semantic congruence elicited larger event-related potential (ERP) amplitudes than do unimodal visual stimuli. Therefore, this study proposed a novel multisensory P300-speller based on audiovisual spatial and semantic congruence. Methods We designed a novel audiovisual P300-speller paradigm (AV spelling paradigm) in which the pronunciation and visual presentation of characters were matched in spatial position and semantics. We analyzed the ERP waveforms elicited in the AV spelling paradigm and visual-based spelling paradigm (V spelling paradigm) and compared the classification accuracies between these two paradigms. Results ERP analysis revealed significant differences in ERP amplitudes between the two paradigms in the following areas (AV > V): the frontal area at 60–140 ms, frontal–central–parietal area at 360–460 ms, frontal area at 700–800 ms, right temporal area at 380–480 and 700–780 ms, and left temporal area at 500–780 ms. Offline classification results showed that the accuracies were significantly higher in the AV spelling paradigm than in the V spelling paradigm after superposing 1, 2, 5, 6, 9, and 10 times (P < 0.05), and there were trends toward improvement in the accuracies at superposing 3, 4, 7, and 8 times (P = 0.06). Similar results were found for information transfer rate between V and AV spelling paradigms at 1, 2, 5, 6, and 10 superposition times (P < 0.05). Significance The proposed audiovisual P300-speller paradigm significantly improved the classification accuracies compared with the visual-based P300-speller paradigm. Our novel paradigm combines spatial and semantic features of two sensory modalities, and the present findings provide valuable insights into the development of multimodal ERP-based BCI paradigms.
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Affiliation(s)
- Zhaohua Lu
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Qi Li
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Ning Gao
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Jingjing Yang
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Ou Bai
- Department of Electrical and Computer Engineering, Florida International University, Miami, FL, United States
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19
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Fernández-Rodríguez Á, Velasco-Álvarez F, Medina-Juliá MT, Ron-Angevin R. Evaluation of emotional and neutral pictures as flashing stimuli using a P300 brain-computer interface speller. J Neural Eng 2019; 16:056024. [PMID: 31382248 DOI: 10.1088/1741-2552/ab386d] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Previous works have reported that complex emotional and visual stimuli can increase the amplitude of the P300 brain potential. Thus, the aim of the present work is to assess these kinds of images in a P300 brain-computer interface (BCI) speller as flashing stimuli. APPROACH Twenty-three volunteers controlled four spellers with different sets of flashing stimuli: flashing letters, neutral pictures (NP), emotional pleasant pictures (EPP) and emotional unpleasant pictures (EUP). MAIN RESULTS The sets of pictures showed a higher performance than the letters in accuracy and information transfer rate. These results were supported by the analysis of the P300 signal, where the picture sets offered the greatest amplitudes. The NP and EPP sets were the best evaluated in the subjective questionnaire. SIGNIFICANCE In short, despite the fact that the effect of emotional stimuli could not be observed in the performance metrics, picture sets have offered a high performance and should be considered in future proposals for visual P300-based BCI applications.
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20
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Guo M, Jin J, Jiao Y, Wang X, Cichockia A. Investigation of Visual Stimulus With Various Colors and the Layout for the Oddball Paradigm in Evoked Related Potential-Based Brain-Computer Interface. Front Comput Neurosci 2019; 13:24. [PMID: 31105544 PMCID: PMC6499038 DOI: 10.3389/fncom.2019.00024] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 04/01/2019] [Indexed: 11/23/2022] Open
Abstract
Objective: Stimulus visual patterns, such as size, content, color, luminosity, and interval, play key roles for brain–computer interface (BCI) performance. However, the three primary colors to be intercompared as a single variable or factor on the same platform are poorly studied. In this work, we configured the visual stimulus patterns with red, green, and blue operating on a newly designed layout of the flash pattern of BCI to study the waveforms and performance of the evoked related potential (ERP). Approach: Twelve subjects participated in our experiment, and each subject was required to finish three different color sub-experiments. Four blocks of the interface were presented along the edge of the screen, and the other four were assembled in the center, aiming to investigate the problem of adjacency distraction. Repeated-measures ANOVA and Bonferroni correction were applied for statistical analysis. Main results: The averaged online accuracy was 98.44% for the red paradigm, higher than 92.71% for the green paradigm, and 93.23% for the blue paradigm. Furthermore, significant differences in online accuracy (p < 0.05) and information transfer rate (p < 0.05) were found between the red and green paradigms. Significance: The red stimulus paradigm yielded the best performance. The proposed design of ERP-based BCI was practical and effective for many potential applications.
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Affiliation(s)
- Miaoji Guo
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Jing Jin
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Yong Jiao
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Xingyu Wang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | - Andrzej Cichockia
- Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia.,Systems Research Institute PAS, Warsaw, Poland.,Department of Informatics, Nicolaus Copernicus University (UMK), Torun, Poland
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21
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Li Q, Lu Z, Gao N, Yang J. Optimizing the Performance of the Visual P300-Speller Through Active Mental Tasks Based on Color Distinction and Modulation of Task Difficulty. Front Hum Neurosci 2019; 13:130. [PMID: 31057381 PMCID: PMC6478661 DOI: 10.3389/fnhum.2019.00130] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Accepted: 03/28/2019] [Indexed: 11/20/2022] Open
Abstract
Objective: P300-speller is the most commonly used brain-computer interface (BCI) for providing a means of communication to patients with amyotrophic lateral sclerosis. However, the performance of the P300-speller BCI is still inadequate. We investigated whether the performance of P300-speller can be further improved by increasing the mental effort required of the user. Methods: We designed two active mental tasks for a P300-speller based on a differently colored smiling cartoon-face paradigm. The tasks were based on color distinction, and their difficulty was modulated. One of the active mental tasks (DC task) required participants to focus on and distinguish the color of a target, while the other task (CN + DC task) required participants to simultaneously count the number of times a target flashed and distinguish its color. Results: The amplitudes of the event-related potentials (ERPs) in both DC and CN + DC tasks were higher than that in the CN task. The significant difference in the amplitudes between the DC and CN tasks was observed around the parietal-central area from 440 to 800 ms (late positive component, LPC), and that between the CN + DC and CN tasks was observed around the left-frontal and right-frontal areas from 320 to 480 ms (P3a) and the parietal-central area from 480 to 800 ms (P3b and LPC). The latency of the P300 potential in the CN + DC task was significantly longer than that in the CN task at F3, Fz, F4, C4, Pz, and P4 (P < 0.05). Offline (P < 0.05 at superposing once, twice, and thrice) and online (P < 0.001) classification results showed that the average accuracies in the CN + DC task were significantly greater than that in the CN task. Similar results were found for online information transfer rates (ITRs; P < 0.001). In addition, we found that the average online accuracies in the DC task were greater than those in the CN task, although the difference was not statistically significant (P = 0.051). Significance: The active mental task based on task difficulty modulation can significantly improve the performance of the P300-speller, and that based on color distinction shows a trend of improved performance.
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Affiliation(s)
- Qi Li
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Zhaohua Lu
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Ning Gao
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Jingjing Yang
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
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22
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Zhang N, Zhou Z, Liu Y, Yin E, Jiang J, Hu D. A Novel Single-Character Visual BCI Paradigm With Multiple Active Cognitive Tasks. IEEE Trans Biomed Eng 2019; 66:3119-3128. [PMID: 30794504 DOI: 10.1109/tbme.2019.2900555] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To introduce a novel event-related potential (ERP)-based brain-computer interface (BCI) paradigm with active mental tasks multiplying precise judgment and visual cognitive capacities and evaluate its performance. METHODS This study employed a paradigm with three types of targets (true-, pseudo-, and non-), double flash codes, colors and color terms, and four test conditions. The primary hypothesis was that active mental tasks combining multiple cognitive capacities and clear judgment for different categories of stimuli increase the BCI performance and evoke stronger or specific ERPs. Classification methods were proposed and evaluated, and two were used in online experiments. RESULTS The modes containing active mental tasks provided higher accuracy than the control mode (by up to 19.06%). The color-word matching mode had the highest judgment level and achieved the best performance. True-stimuli evoked strong P3b, while pseudotarget signals provided obvious N4, but the control mode seemed less sensitive to both of them. Different types of stimuli evoked distinctive N2 and P3a components. CONCLUSION An appropriate boost in the judgment level using multiple stimuli and cognitive approaches could be investigated to improve the BCI performance and evoke or enhance ERPs. Utilizing active mental tasks may be a promising way to promote BCIs. SIGNIFICANCE Active mental tasks combining multiple cognitive capacities and precise judgments were adopted in an ERP-based BCI. Color and color words were introduced as stimuli to construct an alternative paradigm, and the judgment levels of different conditions were calculated. High accuracies and the participants' preferences were obtained, which may promote the effective use of BCIs.
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23
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Mainsah BO, Reeves G, Collins LM, Throckmorton CS. Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction. J Neural Eng 2018; 14:046025. [PMID: 28548052 DOI: 10.1088/1741-2552/aa7525] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The role of a brain-computer interface (BCI) is to discern a user's intended message or action by extracting and decoding relevant information from brain signals. Stimulus-driven BCIs, such as the P300 speller, rely on detecting event-related potentials (ERPs) in response to a user attending to relevant or target stimulus events. However, this process is error-prone because the ERPs are embedded in noisy electroencephalography (EEG) data, representing a fundamental problem in communication of the uncertainty in the information that is received during noisy transmission. A BCI can be modeled as a noisy communication system and an information-theoretic approach can be exploited to design a stimulus presentation paradigm to maximize the information content that is presented to the user. However, previous methods that focused on designing error-correcting codes failed to provide significant performance improvements due to underestimating the effects of psycho-physiological factors on the P300 ERP elicitation process and a limited ability to predict online performance with their proposed methods. Maximizing the information rate favors the selection of stimulus presentation patterns with increased target presentation frequency, which exacerbates refractory effects and negatively impacts performance within the context of an oddball paradigm. An information-theoretic approach that seeks to understand the fundamental trade-off between information rate and reliability is desirable. APPROACH We developed a performance-based paradigm (PBP) by tuning specific parameters of the stimulus presentation paradigm to maximize performance while minimizing refractory effects. We used a probabilistic-based performance prediction method as an evaluation criterion to select a final configuration of the PBP. MAIN RESULTS With our PBP, we demonstrate statistically significant improvements in online performance, both in accuracy and spelling rate, compared to the conventional row-column paradigm. SIGNIFICANCE By accounting for refractory effects, an information-theoretic approach can be exploited to significantly improve BCI performance across a wide range of performance levels.
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Affiliation(s)
- B O Mainsah
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, United States of America
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24
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Ryan DB, Colwell KA, Throckmorton CS, Collins LM, Caves K, Sellers EW. Evaluating Brain-Computer Interface Performance in an ALS Population: Checkerboard and Color Paradigms. Clin EEG Neurosci 2018; 49:114-121. [PMID: 29076357 DOI: 10.1177/1550059417737443] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The objective of this study was to investigate the performance of 3 brain-computer interface (BCI) paradigms in an amyotrophic lateral sclerosis (ALS) population (n = 11). Using a repeated-measures design, participants completed 3 BCI conditions: row/column (RCW), checkerboard (CBW), and gray-to-color (CBC). Based on previous studies, it is hypothesized that the CBC and CBW conditions will result in higher accuracy, information transfer rate, waveform amplitude, and user preference over the RCW condition. An offline dynamic stopping simulation will also increase information transfer rate. Higher mean accuracy was observed in the CBC condition (89.7%), followed by the CBW (84.3%) condition, and lowest in the RCW condition (78.7%); however, these differences did not reach statistical significance ( P = .062). Eight of the eleven participants preferred the CBC and the remaining three preferred the CBW conditions. The offline dynamic stopping simulation significantly increased information transfer rate ( P = .005) and decreased accuracy ( P < .000). The findings of this study suggest that color stimuli provide a modest improvement in performance and that participants prefer color stimuli over monochromatic stimuli. Given these findings, BCI paradigms that use color stimuli should be considered for individuals who have ALS.
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Affiliation(s)
- David B Ryan
- 1 Department of Psychology, East Tennessee State University, Johnson City TN, USA
| | | | | | | | - Kevin Caves
- 2 Duke University Pratt School of Engineering, Durham NC, USA
| | - Eric W Sellers
- 1 Department of Psychology, East Tennessee State University, Johnson City TN, USA
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25
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Evaluating the Influence of Chromatic and Luminance Stimuli on SSVEPs from Behind-the-Ears and Occipital Areas. SENSORS 2018; 18:s18020615. [PMID: 29462975 PMCID: PMC5855130 DOI: 10.3390/s18020615] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Revised: 02/05/2018] [Accepted: 02/14/2018] [Indexed: 01/23/2023]
Abstract
This work presents a study of chromatic and luminance stimuli in low-, medium-, and high-frequency stimulation to evoke steady-state visual evoked potential (SSVEP) in the behind-the-ears area. Twelve healthy subjects participated in this study. The electroencephalogram (EEG) was measured on occipital (Oz) and left and right temporal (TP9 and TP10) areas. The SSVEP was evaluated in terms of amplitude, signal-to-noise ratio (SNR), and detection accuracy using power spectral density analysis (PSDA), canonical correlation analysis (CCA), and temporally local multivariate synchronization index (TMSI) methods. It was found that stimuli based on suitable color and luminance elicited stronger SSVEP in the behind-the-ears area, and that the response of the SSVEP was related to the flickering frequency and the color of the stimuli. Thus, green-red stimulus elicited the highest SSVEP in medium-frequency range, and green-blue stimulus elicited the highest SSVEP in high-frequency range, reaching detection accuracy rates higher than 80%. These findings will aid in the development of more comfortable, accurate and stable BCIs with electrodes positioned on the behind-the-ears (hairless) areas.
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26
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Piña-Ramirez O, Valdes-Cristerna R, Yanez-Suarez O. Scenario Screen: A Dynamic and Context Dependent P300 Stimulator Screen Aimed at Wheelchair Navigation Control. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2018; 2018:7108906. [PMID: 29666663 PMCID: PMC5832133 DOI: 10.1155/2018/7108906] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Revised: 12/21/2017] [Accepted: 01/04/2018] [Indexed: 12/02/2022]
Abstract
P300 spellers have been widely modified to implement nonspelling tasks. In this work, we propose a "scenario" stimulation screen that is a P300 speller variation to command a wheelchair. Our approach utilized a stimulation screen with an image background (scenario snapshot for a wheelchair) and stimulation markers arranged asymmetrically over relevant landmarks, such as suitable paths, doors, windows, and wall signs. Other scenario stimulation screen features were green/blue stimulation marker color scheme, variable Interstimulus Interval, single marker stimulus mode, and optimized stimulus sequence generator. Eighteen able-bodied subjects participated in the experiment; 78% had no experience in BCI usage. A waveform feature analysis and a Mann-Whitney U test performed over the pairs of target and nontarget coherent averages confirmed that 94% of the subjects elicit P300 (p < .005) on this modified stimulator. Least Absolute Shrinkage and Selection Operator optimization and Linear Discriminant Analysis were utilized for the automatic detection of P300. For evaluation with unseen data, target detection was computed (median sensitivity = 1.00 (0.78-1.00)), together with nontarget discrimination (median specificity = 1.00 (0.98-1.00)). The scenario screen adequately elicits P300 and seems suitable for commanding a wheelchair even when users have no previous experience on the BCI spelling task.
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Affiliation(s)
- Omar Piña-Ramirez
- Neuroimaging Research Laboratory, Electrical Engineering Department, Universidad Autonoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, 09340 Ciudad de México, Mexico
| | - Raquel Valdes-Cristerna
- Neuroimaging Research Laboratory, Electrical Engineering Department, Universidad Autonoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, 09340 Ciudad de México, Mexico
| | - Oscar Yanez-Suarez
- Neuroimaging Research Laboratory, Electrical Engineering Department, Universidad Autonoma Metropolitana Unidad Iztapalapa, Av. San Rafael Atlixco 186, Col. Vicentina, Iztapalapa, 09340 Ciudad de México, Mexico
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27
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Operation of a P300-based brain-computer interface in patients with Duchenne muscular dystrophy. Sci Rep 2018; 8:1753. [PMID: 29379140 PMCID: PMC5788861 DOI: 10.1038/s41598-018-20125-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Accepted: 01/09/2018] [Indexed: 11/18/2022] Open
Abstract
A brain-computer interface (BCI) or brain-machine interface is a technology that enables the control of a computer and other external devices using signals from the brain. This technology has been tested in paralysed patients, such as those with cervical spinal cord injuries or amyotrophic lateral sclerosis, but it has not been tested systematically in Duchenne muscular dystrophy (DMD), which is a severe type of muscular dystrophy due to the loss of dystrophin and is often accompanied by progressive muscle weakness and wasting. Here, we investigated the efficacy of a P300-based BCI for patients with DMD. Eight bedridden patients with DMD and eight age- and gender-matched able-bodied controls were instructed to input hiragana characters. We used a region-based, two-step P300-based BCI with green/blue flicker stimuli. EEG data were recorded, and a linear discriminant analysis distinguished the target from other non-targets. The mean online accuracy of inputted characters (accuracy for the two-step procedure) was 71.6% for patients with DMD and 80.6% for controls, with no significant difference between the patients and controls. The P300-based BCI was operated successfully by individuals with DMD in an advanced stage and these findings suggest that this technology may be beneficial for patients with this disease.
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Onishi A, Takano K, Kawase T, Ora H, Kansaku K. Affective Stimuli for an Auditory P300 Brain-Computer Interface. Front Neurosci 2017; 11:522. [PMID: 28983235 PMCID: PMC5613193 DOI: 10.3389/fnins.2017.00522] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 09/05/2017] [Indexed: 12/04/2022] Open
Abstract
Gaze-independent brain computer interfaces (BCIs) are a potential communication tool for persons with paralysis. This study applies affective auditory stimuli to investigate their effects using a P300 BCI. Fifteen able-bodied participants operated the P300 BCI, with positive and negative affective sounds (PA: a meowing cat sound, NA: a screaming cat sound). Permuted stimuli of the positive and negative affective sounds (permuted-PA, permuted-NA) were also used for comparison. Electroencephalography data was collected, and offline classification accuracies were compared. We used a visual analog scale (VAS) to measure positive and negative affective feelings in the participants. The mean classification accuracies were 84.7% for PA and 67.3% for permuted-PA, while the VAS scores were 58.5 for PA and −12.1 for permuted-PA. The positive affective stimulus showed significantly higher accuracy and VAS scores than the negative affective stimulus. In contrast, mean classification accuracies were 77.3% for NA and 76.0% for permuted-NA, while the VAS scores were −50.0 for NA and −39.2 for permuted NA, which are not significantly different. We determined that a positive affective stimulus with accompanying positive affective feelings significantly improved BCI accuracy. Additionally, an ALS patient achieved 90% online classification accuracy. These results suggest that affective stimuli may be useful for preparing a practical auditory BCI system for patients with disabilities.
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Affiliation(s)
- Akinari Onishi
- Systems Neuroscience Section, Department of Rehabilitation for Brain Function, Research Institute of National Rehabilitation Center for Persons with DisabilitiesTokorozawa, Japan.,Center for Frontier Medical Engineering, Chiba UniversityInage, Japan
| | - Kouji Takano
- Systems Neuroscience Section, Department of Rehabilitation for Brain Function, Research Institute of National Rehabilitation Center for Persons with DisabilitiesTokorozawa, Japan
| | - Toshihiro Kawase
- Systems Neuroscience Section, Department of Rehabilitation for Brain Function, Research Institute of National Rehabilitation Center for Persons with DisabilitiesTokorozawa, Japan.,Biointerfaces Unit, Institute of Innovative Research, Tokyo Institute of TechnologyYokohama, Japan
| | - Hiroki Ora
- Systems Neuroscience Section, Department of Rehabilitation for Brain Function, Research Institute of National Rehabilitation Center for Persons with DisabilitiesTokorozawa, Japan.,Brain Science Inspired Life Support Research Center, The University of Electro-CommunicationsChofu, Japan
| | - Kenji Kansaku
- Systems Neuroscience Section, Department of Rehabilitation for Brain Function, Research Institute of National Rehabilitation Center for Persons with DisabilitiesTokorozawa, Japan.,Brain Science Inspired Life Support Research Center, The University of Electro-CommunicationsChofu, Japan
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Ryan DB, Townsend G, Gates NA, Colwell K, Sellers EW. Evaluating brain-computer interface performance using color in the P300 checkerboard speller. Clin Neurophysiol 2017; 128:2050-2057. [PMID: 28863361 DOI: 10.1016/j.clinph.2017.07.397] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2015] [Revised: 07/12/2017] [Accepted: 07/14/2017] [Indexed: 11/18/2022]
Abstract
OBJECTIVE Current Brain-Computer Interface (BCI) systems typically flash an array of items from grey to white (GW). The objective of this study was to evaluate BCI performance using uniquely colored stimuli. METHODS In addition to the GW stimuli, the current study tested two types of color stimuli (grey to color [GC] and color intensification [CI]). The main hypotheses were that in a checkboard paradigm, unique color stimuli will: (1) increase BCI performance over the standard GW paradigm; (2) elicit larger event-related potentials (ERPs); and, (3) improve offline performance with an electrode selection algorithm (i.e., Jumpwise). RESULTS Online results (n=36) showed that GC provides higher accuracy and information transfer rate than the CI and GW conditions. Waveform analysis showed that GC produced higher amplitude ERPs than CI and GW. Information transfer rate was improved by the Jumpwise-selected channel locations in all conditions. CONCLUSIONS Unique color stimuli (GC) improved BCI performance and enhanced ERPs. Jumpwise-selected electrode locations improved offline performance. SIGNIFICANCE These results show that in a checkerboard paradigm, unique color stimuli increase BCI performance, are preferred by participants, and are important to the design of end-user applications; thus, could lead to an increase in end-user performance and acceptance of BCI technology.
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Affiliation(s)
- D B Ryan
- Department of Psychology, East Tennessee State University, Johnson City, TN, USA.
| | - G Townsend
- Department of Computer Science, Algoma University, Sault Ste. Marie, Ontario, Canada
| | - N A Gates
- Department of Psychology, East Tennessee State University, Johnson City, TN, USA
| | - K Colwell
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA
| | - E W Sellers
- Department of Psychology, East Tennessee State University, Johnson City, TN, USA
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Okahara Y, Takano K, Komori T, Nagao M, Iwadate Y, Kansaku K. Operation of a P300-based brain-computer interface by patients with spinocerebellar ataxia. Clin Neurophysiol Pract 2017; 2:147-153. [PMID: 30214988 PMCID: PMC6123944 DOI: 10.1016/j.cnp.2017.06.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2017] [Revised: 06/12/2017] [Accepted: 06/24/2017] [Indexed: 11/16/2022] Open
Abstract
Objective We investigated the efficacy of a P300-based brain-computer interface (BCI) for patients with spinocerebellar ataxia (SCA), which is often accompanied by cerebellar impairment. Methods Eight patients with SCA and eight age- and gender-matched healthy controls were instructed to input Japanese hiragana characters using the P300-based BCI with green/blue flicker. All patients depended on some assistance in their daily lives (modified Rankin scale: mean 3.5). The chief symptom was cerebellar ataxia; no cognitive deterioration was present. A region-based, two-step P300-based BCI was used. During the P300 task, eight-channel EEG data were recorded, and a linear discriminant analysis distinguished the target from other nontarget regions of the matrix. Results The mean online accuracy in BCI operation was 82.9% for patients with SCA and 83.2% for controls; no significant difference was detected. Conclusion The P300-based BCI was operated successfully not only by healthy controls but also by individuals with SCA. Significance These results suggest that the P300-based BCI may be applicable for patients with SCA.
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Affiliation(s)
- Yoji Okahara
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan.,Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chiba, Chiba 260-8670, Japan
| | - Kouji Takano
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan
| | - Tetsuo Komori
- Department of Neurology, National Hakone Hospital, Odawara, Kanagawa 250-0032, Japan
| | - Masahiro Nagao
- Department of Neurology, Tokyo Metropolitan Neurological Hospital, Fuchu, Tokyo 183-0042, Japan
| | - Yasuo Iwadate
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chiba, Chiba 260-8670, Japan
| | - Kenji Kansaku
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan.,Brain Science Inspired Life Support Research Center, The University of Electro-Communications, Chofu, Tokyo 182-8585, Japan
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Ma Z, Qiu T. Performance improvement of ERP-based brain–computer interface via varied geometric patterns. Med Biol Eng Comput 2017; 55:2245-2256. [DOI: 10.1007/s11517-017-1671-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 06/19/2017] [Indexed: 11/24/2022]
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Lebedev MA, Nicolelis MAL. Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. Physiol Rev 2017; 97:767-837. [PMID: 28275048 DOI: 10.1152/physrev.00027.2016] [Citation(s) in RCA: 235] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from neurophysiology, computer science, and engineering in an effort to establish real-time bidirectional links between living brains and artificial actuators. Although theoretical propositions and some proof of concept experiments on directly linking the brains with machines date back to the early 1960s, BMI research only took off in earnest at the end of the 1990s, when this approach became intimately linked to new neurophysiological methods for sampling large-scale brain activity. The classic goals of BMIs are 1) to unveil and utilize principles of operation and plastic properties of the distributed and dynamic circuits of the brain and 2) to create new therapies to restore mobility and sensations to severely disabled patients. Over the past decade, a wide range of BMI applications have emerged, which considerably expanded these original goals. BMI studies have shown neural control over the movements of robotic and virtual actuators that enact both upper and lower limb functions. Furthermore, BMIs have also incorporated ways to deliver sensory feedback, generated from external actuators, back to the brain. BMI research has been at the forefront of many neurophysiological discoveries, including the demonstration that, through continuous use, artificial tools can be assimilated by the primate brain's body schema. Work on BMIs has also led to the introduction of novel neurorehabilitation strategies. As a result of these efforts, long-term continuous BMI use has been recently implicated with the induction of partial neurological recovery in spinal cord injury patients.
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Obeidat QT, Campbell TA, Kong J. Spelling With a Small Mobile Brain-Computer Interface in a Moving Wheelchair. IEEE Trans Neural Syst Rehabil Eng 2017; 25:2169-2179. [PMID: 28475062 DOI: 10.1109/tnsre.2017.2700025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Research into brain-computer interfaces (BCIs), which spell words using brain signals, has revealed that a desktop version of such a speller, the edges paradigm, offers several advantages: This edges paradigm outperforms the benchmark row-column paradigm in terms of accuracy, bitrate, and user experience. It has remained unknown whether these advantages prevailed with a new version of the edges paradigm designed for a mobile device. This paper investigated and evaluated in a rolling wheelchair a mobile BCI, which implemented the edges paradigm on small displays with which visual crowding tends to occur. How the mobile edge paradigm outperforms the mobile row-column paradigm has implications for understanding how principles of visual neurocognition affect BCI speller use in a mobile context. This investigation revealed that all the advantages of the edges paradigm over the row-column paradigm prevailed in this setting. However, the reduction in adjacent errors for the edges paradigm was unprecedentedly limited to horizontal adjacent errors. The interpretation offered is that dimensional constraints of visual interface design on a smartphone thus affected the neurocognitive processes of crowding.
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Speier W, Deshpande A, Cui L, Chandravadia N, Roberts D, Pouratian N. A comparison of stimulus types in online classification of the P300 speller using language models. PLoS One 2017; 12:e0175382. [PMID: 28406932 PMCID: PMC5391014 DOI: 10.1371/journal.pone.0175382] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2016] [Accepted: 03/06/2017] [Indexed: 11/18/2022] Open
Abstract
The P300 Speller is a common brain-computer interface communication system. There are many parallel lines of research underway to overcome the system's low signal to noise ratio and thereby improve performance, including using famous face stimuli and integrating language information into the classifier. While both have been shown separately to provide significant improvements, the two methods have not yet been implemented together to demonstrate that the improvements are complimentary. The goal of this study is therefore twofold. First, we aim to compare the famous faces stimulus paradigm with an existing alternative stimulus paradigm currently used in commercial systems (i.e., character inversion). Second, we test these methods with language model integration to assess whether different optimization approaches can be combined to further improve BCI communication. In offline analysis using a previously published particle filter method, famous faces stimuli yielded superior results to both standard and inverting stimuli. In online trials using the particle filter method, all 10 subjects achieved a higher selection rate when using the famous faces flashing paradigm than when using inverting flashes. The improvements achieved by these methods are therefore complementary and a combination yields superior results to either method implemented individually when tested in healthy subjects.
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Affiliation(s)
- William Speier
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Aniket Deshpande
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Lucy Cui
- Neuroscience Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Nand Chandravadia
- Neuroscience Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Dustin Roberts
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States of America
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States of America
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States of America
- Neuroscience Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, United States of America
- Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, United States of America
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Chen X, Wang Y, Zhang S, Gao S, Hu Y, Gao X. A novel stimulation method for multi-class SSVEP-BCI using intermodulation frequencies. J Neural Eng 2017; 14:026013. [DOI: 10.1088/1741-2552/aa5989] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Wilaiprasitporn T, Yagi T. Investigation of P300 response characteristics through human color vision-based visual stimulation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2016; 2014:4900-3. [PMID: 25571090 DOI: 10.1109/embc.2014.6944722] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In this study, we propose visual stimulation based on the primary colors (red, green, and blue) in order to investigate the characteristics of the P300 response. Eleven healthy volunteers participated in our experiment, and their brain signals were recorded by electroencephalography (EEG). Using two basic measures referred to as `on-peak' and `off-peak' for comparison of the P300 response among the participants, we found that the P300 response varies depending on the color of the stimulus. The results of this investigation are expected to contribute to various existing and future EEG-based applications.
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Townsend G, Platsko V. Pushing the P300-based brain–computer interface beyond 100 bpm: extending performance guided constraints into the temporal domain. J Neural Eng 2016; 13:026024. [DOI: 10.1088/1741-2560/13/2/026024] [Citation(s) in RCA: 43] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Sakurada T, Kawase T, Komatsu T, Kansaku K. Use of high-frequency visual stimuli above the critical flicker frequency in a SSVEP-based BMI. Clin Neurophysiol 2015; 126:1972-8. [PMID: 25577407 DOI: 10.1016/j.clinph.2014.12.010] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2014] [Revised: 11/07/2014] [Accepted: 12/10/2014] [Indexed: 11/30/2022]
Affiliation(s)
- Takeshi Sakurada
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan
| | - Toshihiro Kawase
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan
| | - Tomoaki Komatsu
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan
| | - Kenji Kansaku
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan; Brain Science Inspired Life Support Research Center, The University of Electro-Communications, Chofu, Tokyo 182-8585, Japan.
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Use of a Green Familiar Faces Paradigm Improves P300-Speller Brain-Computer Interface Performance. PLoS One 2015; 10:e0130325. [PMID: 26087308 PMCID: PMC4472698 DOI: 10.1371/journal.pone.0130325] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Accepted: 05/19/2015] [Indexed: 11/25/2022] Open
Abstract
Background A recent study showed improved performance of the P300-speller when the flashing row or column was overlaid with translucent pictures of familiar faces (FF spelling paradigm). However, the performance of the P300-speller is not yet satisfactory due to its low classification accuracy and information transfer rate. Objective To investigate whether P300-speller performance is further improved when the chromatic property and the FF spelling paradigm are combined. Methods We proposed a new spelling paradigm in which the flashing row or column is overlaid with translucent green pictures of familiar faces (GFF spelling paradigm). We analyzed the ERP waveforms elicited by the FF and proposed GFF spelling paradigms and compared P300-speller performance between the two paradigms. Results Significant differences in the amplitudes of four ERP components (N170, VPP, P300, and P600f) were observed between both spelling paradigms. Compared to the FF spelling paradigm, the GFF spelling paradigm elicited ERP waveforms of higher amplitudes and resulted in improved P300-speller performance. Conclusions Combining the chromatic property (green color) and the FF spelling paradigm led to better classification accuracy and an increased information transfer rate. These findings demonstrate a promising new approach for improving the performance of the P300-speller.
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Ceballos GA, Hernández LF. Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface. J Neural Eng 2015; 12:026009. [PMID: 25710243 DOI: 10.1088/1741-2560/12/2/026009] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. APPROACH Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). MAIN RESULTS The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. SIGNIFICANCE We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.
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Affiliation(s)
- G A Ceballos
- Center of Biomedical Engineering and Telemedicine, Faculty of Engineering, University of Los Andes, Merida, Venezuela
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Bamdad M, Zarshenas H, Auais MA. Application of BCI systems in neurorehabilitation: a scoping review. Disabil Rehabil Assist Technol 2015; 10:355-64. [PMID: 25560222 DOI: 10.3109/17483107.2014.961569] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
PURPOSE To review various types of electroencephalographic activities of the brain and present an overview of brain-computer interface (BCI) systems' history and their applications in rehabilitation. METHODS A scoping review of published English literature on BCI application in the field of rehabilitation was undertaken. IEEE Xplore, ScienceDirect, Google Scholar and Scopus databases were searched since inception up to August 2012. All experimental studies published in English and discussed complete cycle of the BCI process was included in the review. RESULTS AND DISCUSSION In total, 90 articles met the inclusion criteria and were reviewed. Various approaches that improve the accuracy and performance of BCI systems were discussed. Based on BCI's clinical application, reviewed articles were categorized into three groups: motion rehabilitation, speech rehabilitation and virtual reality control (VRC). Almost half of the reviewed papers (48%) concentrated on VRC. Speech rehabilitation and motion rehabilitation made up 33% and 19% of the reviewed papers, respectively. Among different types of electroencephalography signals, P300, steady state visual evoked potentials and motor imagery signals were the most common. CONCLUSIONS This review discussed various applications of BCI in rehabilitation and showed how BCI can be used to improve the quality of life for people with neurological disabilities. It will develop and promote new models of communication and finally, will create an accurate, reliable, online communication between human brain and computer and reduces the negative effects of external stimuli on BCI performance. Implications for Rehabilitation The field of brain-computer interfaces (BCI) is rapidly advancing and it is expected to fulfill a critical role in rehabilitation of neurological disorders and in movement restoration in the forthcoming years. In the near future, BCI has notable potential to become a major tool used by people with disabilities to control locomotion and communicate with surrounding environment and, consequently, improve the quality of life for many affected persons. Electrical field recording at the scalp (i.e. electroencephalography) is the most likely method to be of practical value for clinical use as it is simple and non-invasive. However, some aspects need future improvements, such as the ability to separate close imagery signal (motion of extremities and phalanges that are close together).
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Affiliation(s)
- Mahdi Bamdad
- Mechanical Engineering Department, Biomechatronic Research Lab, Shahrood University of Technology , Shahrood , Iran and
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An efficient word typing P300-BCI system using a modified T9 interface and random forest classifier. Comput Biol Med 2015; 56:30-6. [DOI: 10.1016/j.compbiomed.2014.10.021] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Revised: 10/21/2014] [Accepted: 10/25/2014] [Indexed: 11/30/2022]
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Halder S, Pinegger A, Käthner I, Wriessnegger SC, Faller J, Pires Antunes JB, Müller-Putz GR, Kübler A. Brain-controlled applications using dynamic P300 speller matrices. Artif Intell Med 2015; 63:7-17. [PMID: 25533310 DOI: 10.1016/j.artmed.2014.12.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Revised: 11/19/2014] [Accepted: 12/02/2014] [Indexed: 10/24/2022]
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Akcakaya M, Peters B, Moghadamfalahi M, Mooney AR, Orhan U, Oken B, Erdogmus D, Fried-Oken M. Noninvasive brain-computer interfaces for augmentative and alternative communication. IEEE Rev Biomed Eng 2014; 7:31-49. [PMID: 24802700 DOI: 10.1109/rbme.2013.2295097] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Brain-computer interfaces (BCIs) promise to provide a novel access channel for assistive technologies, including augmentative and alternative communication (AAC) systems, to people with severe speech and physical impairments (SSPI). Research on the subject has been accelerating significantly in the last decade and the research community took great strides toward making BCI-AAC a practical reality to individuals with SSPI. Nevertheless, the end goal has still not been reached and there is much work to be done to produce real-world-worthy systems that can be comfortably, conveniently, and reliably used by individuals with SSPI with help from their families and care givers who will need to maintain, setup, and debug the systems at home. This paper reviews reports in the BCI field that aim at AAC as the application domain with a consideration on both technical and clinical aspects.
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Yeom SK, Fazli S, Müller KR, Lee SW. An efficient ERP-based brain-computer interface using random set presentation and face familiarity. PLoS One 2014; 9:e111157. [PMID: 25384045 PMCID: PMC4226481 DOI: 10.1371/journal.pone.0111157] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Accepted: 09/27/2014] [Indexed: 11/18/2022] Open
Abstract
Event-related potential (ERP)-based P300 spellers are commonly used in the field of brain-computer interfaces as an alternative channel of communication for people with severe neuro-muscular diseases. This study introduces a novel P300 based brain-computer interface (BCI) stimulus paradigm using a random set presentation pattern and exploiting the effects of face familiarity. The effect of face familiarity is widely studied in the cognitive neurosciences and has recently been addressed for the purpose of BCI. In this study we compare P300-based BCI performances of a conventional row-column (RC)-based paradigm with our approach that combines a random set presentation paradigm with (non-) self-face stimuli. Our experimental results indicate stronger deflections of the ERPs in response to face stimuli, which are further enhanced when using the self-face images, and thereby improving P300-based spelling performance. This lead to a significant reduction of stimulus sequences required for correct character classification. These findings demonstrate a promising new approach for improving the speed and thus fluency of BCI-enhanced communication with the widely used P300-based BCI setup.
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Affiliation(s)
- Seul-Ki Yeom
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Siamac Fazli
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Klaus-Robert Müller
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
- Machine Learning Group, Berlin Institute of Technology, Berlin, Germany
| | - Seong-Whan Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
- * E-mail:
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Ikegami S, Takano K, Kondo K, Saeki N, Kansaku K. A region-based two-step P300-based brain–computer interface for patients with amyotrophic lateral sclerosis. Clin Neurophysiol 2014; 125:2305-2312. [PMID: 24731767 DOI: 10.1016/j.clinph.2014.03.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2013] [Revised: 03/09/2014] [Accepted: 03/11/2014] [Indexed: 11/16/2022]
Affiliation(s)
- Shiro Ikegami
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan; Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chiba, Chiba 260-8670, Japan
| | - Kouji Takano
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan
| | - Kiyohiko Kondo
- Department of Neurology, Yoka Hospital, Yabu, Hyogo 667-8555, Japan
| | - Naokatsu Saeki
- Department of Neurological Surgery, Chiba University Graduate School of Medicine, Chiba, Chiba 260-8670, Japan
| | - Kenji Kansaku
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities, Tokorozawa, Saitama 359-8555, Japan; Center for Frontier Medical Engineering, Chiba University, Chiba 263-0022, Japan; Brain Science Inspired Life Support Research Center, The University of Electro-Communications, Tokyo 182-8585, Japan.
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Zhou Z, Yin E, Liu Y, Jiang J, Hu D. A novel task-oriented optimal design for P300-based brain-computer interfaces. J Neural Eng 2014; 11:056003. [PMID: 25080373 DOI: 10.1088/1741-2560/11/5/056003] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Objective. The number of items of a P300-based brain-computer interface (BCI) should be adjustable in accordance with the requirements of the specific tasks. To address this issue, we propose a novel task-oriented optimal approach aimed at increasing the performance of general P300 BCIs with different numbers of items. Approach. First, we proposed a stimulus presentation with variable dimensions (VD) paradigm as a generalization of the conventional single-character (SC) and row-column (RC) stimulus paradigms. Furthermore, an embedding design approach was employed for any given number of items. Finally, based on the score-P model of each subject, the VD flash pattern was selected by a linear interpolation approach for a certain task. Main results. The results indicate that the optimal BCI design consistently outperforms the conventional approaches, i.e., the SC and RC paradigms. Specifically, there is significant improvement in the practical information transfer rate for a large number of items. Significance. The results suggest that the proposed optimal approach would provide useful guidance in the practical design of general P300-based BCIs.
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Affiliation(s)
- Zongtan Zhou
- Department of Automatic Control, College of Mechatronic Engineering and Automation, National University of Defense Technology, 410073 Changsha, Hunan, People's Republic of China
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Takano K, Ora H, Sekihara K, Iwaki S, Kansaku K. Coherent Activity in Bilateral Parieto-Occipital Cortices during P300-BCI Operation. Front Neurol 2014; 5:74. [PMID: 24860546 PMCID: PMC4030183 DOI: 10.3389/fneur.2014.00074] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2013] [Accepted: 05/01/2014] [Indexed: 12/02/2022] Open
Abstract
The visual P300 brain–computer interface (BCI), a popular system for electroencephalography (EEG)-based BCI, uses the P300 event-related potential to select an icon arranged in a flicker matrix. In earlier studies, we used green/blue (GB) luminance and chromatic changes in the P300-BCI system and reported that this luminance and chromatic flicker matrix was associated with better performance and greater subject comfort compared with the conventional white/gray (WG) luminance flicker matrix. To highlight areas involved in improved P300-BCI performance, we used simultaneous EEG–fMRI recordings and showed enhanced activities in bilateral and right lateralized parieto-occipital areas. Here, to capture coherent activities of the areas during P300-BCI, we collected whole-head 306-channel magnetoencephalography data. When comparing functional connectivity between the right and left parieto-occipital channels, significantly greater functional connectivity in the alpha band was observed under the GB flicker matrix condition than under the WG flicker matrix condition. Current sources were estimated with a narrow-band adaptive spatial filter, and mean imaginary coherence was computed in the alpha band. Significantly greater coherence was observed in the right posterior parietal cortex under the GB than under the WG condition. Re-analysis of previous EEG-based P300-BCI data showed significant correlations between the power of the coherence of the bilateral parieto-occipital cortices and their performance accuracy. These results suggest that coherent activity in the bilateral parieto-occipital cortices plays a significant role in effectively driving the P300-BCI.
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Affiliation(s)
- Kouji Takano
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities , Tokorozawa , Japan
| | - Hiroki Ora
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities , Tokorozawa , Japan
| | - Kensuke Sekihara
- Department of Systems Design and Engineering, Tokyo Metropolitan University , Tokyo , Japan
| | - Sunao Iwaki
- Cognition and Action Research Group, Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST) , Tsukuba , Japan
| | - Kenji Kansaku
- Systems Neuroscience Section, Department of Rehabilitation for Brain Functions, Research Institute of National Rehabilitation Center for Persons with Disabilities , Tokorozawa , Japan ; Brain Science Inspired Life Support Research Center, The University of Electro-Communications , Tokyo , Japan
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Akram F, Han HS, Kim TS. A P300-based brain computer interface system for words typing. Comput Biol Med 2013; 45:118-25. [PMID: 24480171 DOI: 10.1016/j.compbiomed.2013.12.001] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2013] [Revised: 11/29/2013] [Accepted: 12/03/2013] [Indexed: 10/25/2022]
Abstract
P300 is an event related potential of the brain in response to oddball events. Brain Computer Interface (BCI) utilizing P300 is known as a P300 BCI system. A conventional P300 BCI system for character spelling is composed of a paradigm that displays flashing characters and a classification scheme which identifies target characters. To type a word a user has to spell each character of the word: this spelling process is slow and it can take several minutes to type a word. In this study, we propose a new word typing scheme by integrating a word suggestion mechanism with a dictionary search into the conventional P300-based speller. Our new P300-based word typing system consists of an initial character spelling paradigm, a dictionary unit to give suggestions of possible words and the second word selection paradigm to select a word out of the suggestions. Our proposed methodology reduces typing time significantly and makes word typing easy via a P300 BCI system. We have tested our system with ten subjects and our results demonstrate an average word typing time of 1.91 min whereas the conventional took 3.36 min for the same words.
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Affiliation(s)
- Faraz Akram
- Department of Biomedical Engineering, Kyung Hee University, Republic of Korea
| | - Hee-Sok Han
- Department of Biomedical Engineering, Kyung Hee University, Republic of Korea
| | - Tae-Seong Kim
- Department of Biomedical Engineering, Kyung Hee University, Republic of Korea.
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Kamp SM, Murphy AR, Donchin E. The component structure of event-related potentials in the p300 speller paradigm. IEEE Trans Neural Syst Rehabil Eng 2013; 21:897-907. [PMID: 24235153 DOI: 10.1109/tnsre.2013.2285398] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
We investigated the componential structure of event-related potentials elicited while participants use the P300 BCI. Six healthy participants "typed" all characters in a 6 × 6 matrix twice in a random sequence. A principal component analysis indicated that in addition to the P300, target flashes elicited an earlier frontal positivity, possibly a Novelty P3. The amplitudes of both P300 and the Novelty P3 varied with the matrix row in which the target character was located. However, the P300 elicited by row flashes was largest for targets in the lower part of the matrix, whereas the Novelty P3 elicited by column flashes was largest in the top part. Classification accuracy using stepwise linear discriminant analysis mirrored the pattern in the Novelty P3 (an accuracy difference of 0.1 between rows 1 and 6). When separate classifiers were generated to rely solely on the P300 or solely on the Novelty P3, the latter function led to higher accuracy (a mean accuracy difference of about 0.2 between classifiers). A possible explanation is that some nontarget flashes elicit a P300, leading to lower selection accuracy of the respective classifier. In an additional set of data from six different participants we replicated the ERP structure of the initial analyses and characterized the spatial distributions more closely by using a dense electrode array. Overall, our findings provide new insights in the componential structure of ERPs elicited in the P300 speller paradigm and have important implications for optimizing the speller's selection accuracy.
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