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Multi-view optimization of time-frequency common spatial patterns for brain-computer interfaces

JOURNAL OF NEUROSCIENCE METHODS 2022年 365卷 109378页

作者： Huang, Yitao Jin, Jing Xu, Ren Miao, Yangyang Liu, Chang Cichocki, Andrzej East China Univ Sci & Technol Key Lab Smart Mfg Energy Chem Proc Minist Educ Shanghai Peoples R China Guger Technol OG Herbersteinstr 60 A-8020 Graz Austria Skolkowo Inst Sci & Technol Moscow 143025 Russia Nicolaus Copernicus Univ UMK PL-87100 Torun Poland

Background: Common spatial pattern (CSP) is a prevalent method applied to feature extraction in motor imagery (MI)-based brain-computer interfaces (BCIs) recorded by electroencephalogram (EEG). The selection of time windows and frequency bands prominently affects the performance of CSP algorithms. Concerning the joint optimization of these two parameters, several studies have utilized a unified framework based on different feature selection strategies and achieved considerable improvement. However, during the feature selection process, useful information could be discarded inevitably and the underlying internal structure of features could be neglected. New method: In this paper, we proposed a novel framework termed time window filter bank common spatial pattern with multi-view optimization (TWFBCSP-MVO) to further boost the decoding of MI tasks. Concretely, after extracting CSP features from different time-frequency decompositions of EEG signals, a preliminary screening strategy based on variance ratio was devised to filter out the unrelated spatial patterns. We then introduced a multi-view learning strategy for the simultaneous optimization of time windows and frequency bands. A support vector machine classifier was trained to determine the output of the brain. Results: An experimental study was conducted on two public datasets to verify the effectiveness of TWFBCSPMVO. Results showed that the proposed TWFBCSP-MVO could help improve the performance of MI classification. Comparison with existing methods: In comparison to other competing methods, the proposed method performed significantly better (p < 0.01). Conclusions: The proposed method is a promising contestant to improve the performance of practical MI-based BCIs.

关键词： Common spatial pattern Electroencephalogram Motor imagery brain-computer interfaces Multi-view optimization

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Applications of brain-computer interfaces in neurodegenerative diseases

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NEUROSURGICAL REVIEW 2023年第1期46卷 1-10页

作者： Tayebi, Hossein Azadnajafabad, Sina Maroufi, Seyed Farzad Pour-Rashidi, Ahmad Khorasanizadeh, MirHojjat Faramarzi, Sina Slavin, Konstantin V. Universal Sci Educ & Res Network USERN Neurosurg Res Network NRN Tehran Iran Shahid Beheshti Univ Med Sci Sch Med Tehran Iran Univ Tehran Med Sci Dept Surg Tehran Iran Univ Tehran Med Sci Sch Med Tehran Iran Univ Tehran Med Sci Sina Hosp Dept Neurosurg Tehran Iran Icahn Sch Med Mt Sinai Hosp Dept Neurosurg New York NY USA Univ Calif Irvine Irvine CA USA Univ Illinois Dept Neurosurg Chicago IL 60612 USA

brain-computer interfaces (BCIs) provide the central nervous system with channels of direct communication to the outside world, without having to go through the peripheral nervous system. Neurodegenerative diseases (NDs) are notoriously incurable and burdensome medical conditions that will result in progressive deterioration of the nervous system. The applications of BCIs in NDs have been studied for decades now through different approaches, resulting in a considerable amount of literature in all related areas. In this study, we begin by introducing BCIs and proceed by explaining the principles of BCI-based neurorehabilitation. Then, we go through four specific types of NDs, including amyotrophic lateral sclerosis, Parkinson's disease, Alzheimer's disease, and spinal muscular atrophy, and review some of the applications of BCIs in the neural rehabilitation of these diseases. We conclude with a discussion of the characteristics, challenges, and future possibilities of research in the field. Going through the uses of BCIs in NDs, we can see that approaches and strategies employed to tackle the wide range of limitations caused by NDs are numerous and diverse. Furthermore, NDs can fall under different categories based on the target area of neurodegeneration and thus require different methods of BCI-based rehabilitation. In recent years, neurotechnology companies have substantially invested in research on BCIs, focusing on commercializing BCIs and bringing BCI-based technologies from bench to bedside. This can mean the beginning of a new era for BCI-based neurorehabilitation, with an anticipated spike in interest among researchers, practitioners, engineers, and entrepreneurs alike.

关键词： Neurodegenerative diseases brain-computer interfaces Neurological rehabilitation Amyotrophic lateral sclerosis Alzheimer's disease

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Comparing interaction techniques for serious games through brain-computer interfaces: A user perception evaluation study

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ENTERTAINMENT COMPUTING 2014年第4期5卷 391-399页

作者： Liarokapis, Fotis Debattista, Kurt Vourvopoulos, Athanasios Petridis, Panagiotis Ene, Alina Masaryk Univ Fac Informat Human Comp Interact Lab Botanicka 554-68a Brno Czech Republic Univ Warwick WMG Coventry CV32 5LD W Midlands England Univ Madeira Madeira Interact Technol Inst Funchal Portugal Coventry Univ Coventry Innovat Village Serious Games Inst Coventry CV1 2TL W Midlands England

This paper examines the application of commercial and non-invasive electroencephalography (EEG)based brain-computer (BCIs) interfaces with serious games. Two different EEG-based BCI devices were used to fully control the same serious game. The first device (NeuroSky MindSet) uses only a single dry electrode and requires no calibration. The second device (Emotiv EPOC) uses 14 wet sensors requiring additional training of a classifier. User testing was performed on both devices with sixty-two participants measuring the player experience as well as key aspects of serious games, primarily learnability, satisfaction, performance and effort. Recorded feedback indicates that the current state of BCIs can be used in the future as alternative game interfaces after familiarisation and in some cases calibration. Comparative analysis showed significant differences between the two devices. The first device provides more satisfaction to the players whereas the second device is more effective in terms of adaptation and interaction with the serious game. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Serious games brain-computer interfaces Virtual environments Human-machine interaction

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Thoughts Unlocked by Technology-a Survey in Germany About brain-computer interfaces

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NANOETHICS 2021年第3期15卷 303-313页

作者： Schmid, J. R. Friedrich, O. Kessner, S. Jox, R. J. Ludwig Maximilian Univ Munich Inst Eth Hist & Theory Med Lessingstr 2 D-80336 Munich Germany Distance Univ Hagen Fac Cultural & Social Sci Inst Philosophy Univ Str 33 D-58097 Hagen Germany Lausanne Univ Hosp CHUV Inst Humanites Med Ave Provence 82 CH-1107 Lausanne Switzerland Univ Lausanne Ave Provence 82 CH-1107 Lausanne Switzerland

A brain-computer interface (BCI) is a rapidly evolving neurotechnology connecting the human brain with a computer. In its classic form, brain activity is recorded and used to control external devices like protheses or wheelchairs. Thus, BCI users act with the power of their thoughts. While the initial development has focused on medical uses of BCIs, non-medical applications have recently been gaining more attention, for example in automobiles, airplanes, and the entertainment context. However, the attitudes of the general public towards BCIs have hardly been explored. Among the general population in Germany aged 18-65 years, a representative online survey with 20 items was conducted in summer 2018 (n = 1000) and analysed by descriptive statistics. The survey assessed: affinity for technology;previous knowledge and experience concerning BCIs;the attitude towards ethical, social and legal implications of BCI use and demographic information. Our results indicate that BCIs are a unique and puzzling way of human-machine interaction. The findings reveal a positive view and high level of trust in BCIs on the one hand but on the other hand a wide range of ethical and anthropological concerns. Agency and responsibility were clearly attributed to the BCI user. The participants' opinions were divided regarding the impact BCIs have on humankind. In summary, a high level of ambivalence regarding BCIs was found. We suggest better information of the public and the promotion of public deliberation about BCIs in order to ensure responsible development and application of this potentially disruptive technology.

关键词： brain-computer interfaces Neuro-ethics Public survey General public Online survey Empirical research

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Feature selection for classification in Steady state visually evoked potentials (SSVEP)-based brain-computer interfaces with genetic algorithm

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BIO-ALGORITHMS AND MED-SYSTEMS 2020年第2期16卷

作者： Karkosz, Stanislaw Jukiewicz, Marcin SWPS Univ Social Sci & Humanities Warsaw Poland Adam Mickiewicz Univ Poznan Poland

Objectives: Optimization of brain-computer Interface by detecting the minimal number of morphological features of signal that maximize accuracy. Methods: System of signal processing and morphological features extractor was designed, then the genetic algorithm was used to select such characteristics that maximize the accuracy of the signal's frequency recognition in offline brain-computer Interface (BCI). Results: The designed system provides higher accuracy results than a previously developed system that uses the same preprocessing methods, however, different results were achieved for various subjects. Conclusions: It is possible to enhance the previously developed BCI by combining it with morphological features extraction, however, it's performance is dependent on subject variability.

关键词： accuracy brain-computer interfaces feature selection genetic algorithms information transfer rate morphological features steady state visually evoked potentials

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Transcranial Direct Current Stimulation and brain-computer interfaces for Improving Post-Stroke Recovery: A Systematic Review and Meta-Analysis

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CLINICAL REHABILITATION 2024年第1期38卷 3-14页

作者： Lima, Eloise de Oliveira Silva, Leticia Maria Melo, Ana Luisa Vilar D'arruda, Julia Vitoria Torres de Albuquerque, Marlon Alexandre Neto, Jose Mauricio Ramos de Souza de Oliveira, Eliane Araujo Andrade, Suellen Marinho Univ Fed Paraiba Aging & Neurosci Lab Joao Pessoa Brazil Univ Fed Paraiba Ctr Alternat & Renewable Energies Joao Pessoa Brazil Univ Fed Paraiba Aging & Neurosci Lab Campus I Lot Cidade Univ BR-58051900 Joao Pessoa PB Brazil

Objective This study aimed to evaluate the effectiveness of transcranial direct current stimulation associated with brain-computer interface in stroke *** sources The PubMed, Central, PEDro, Web of Science, SCOPUS, PsycINFO Ovid, CINAHL EBSCO, EMBASE, and ScienceDirect databases were searched from inception to April 2023 for randomized controlled studies reporting the effects of active transcranial direct current stimulation associated with brain-computer interface to a transcranial direct current stimulation sham associated with brain-computer interface condition on the outcome measure (motor performance and functional independence).Review methods We searched for full-text articles which had investigated the effect of transcranial direct current stimulation associated with brain-computer interface on motor performance in the upper extremities in stroke patients. The standardized mean differences derived from the change in scores between pretreatment and post-treatment were adopted as the effect size measure, with a 95% confidence interval. Possible sources of heterogeneity were analyzed by performing subgroup analyses in order to examine the moderating effects for one variable: the level of injury *** Nine studies were included in the qualitative synthesis and the meta-analysis. The findings of the conducted analyses indicated there is not enough evidence to suggest that active transcranial direct current stimulation associated with brain-computer interface is more efficient in motor performance and functional independence when compared to sham transcranial direct current stimulation associated with brain-computer interface or brain-computer interface alone. In addition, the quality of evidence was rated very low. A subgroup analysis was performed for the motor performance outcome considering the injury severity *** We found evidence that transcranial direct current stimulation associated with brain-computer interface was not mor

关键词： Stroke transcranial direct current stimulation brain-computer interfaces systematic review meta-analysis

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Methodological Recommendations for Studies on the Daily Life Implementation of Implantable Communication-brain-computer interfaces for Individuals With Locked-in Syndrome

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NEUROREHABILITATION AND NEURAL REPAIR 2022年第1-11期36卷 666-677页

作者： Vansteensel, Mariska J. Branco, Mariana P. Leinders, Sacha Freudenburg, Zac F. Schippers, Anouck Geukes, Simon H. Gaytant, Michael A. Gosselaar, Peter H. Aarnoutse, Erik J. Ramsey, Nick F. Univ Med Ctr Utrecht UMC Utrecht Brain Ctr Dept Neurol & Neurosurg POB 85060 NL-3508 AB Utrecht Netherlands Univ Med Ctr Utrecht Dept Pulm Dis Home Mech Ventilat Utrecht Netherlands

Implantable brain-computer interfaces (BCIs) promise to be a viable means to restore communication in individuals with locked-in syndrome (LIS). In 2016, we presented the world-first fully implantable BCI system that uses subdural electrocorticography electrodes to record brain signals and a subcutaneous amplifier to transmit the signals to the outside world, and that enabled an individual with LIS to communicate via a tablet computer by selecting icons in spelling software. For future clinical implementation of implantable communication-BCIs, however, much work is still needed, for example, to validate these systems in daily life settings with more participants, and to improve the speed of communication. We believe the design and execution of future studies on these and other topics may benefit from the experience we have gained. Therefore, based on relevant literature and our own experiences, we here provide an overview of procedures, as well as recommendations, for recruitment, screening, inclusion, imaging, hospital admission, implantation, training, and support of participants with LIS, for studies on daily life implementation of implantable communication-BCIs. With this article, we not only aim to inform the BCI community about important topics of concern, but also hope to contribute to improved methodological standardization of implantable BCI research.

关键词： methods brain-computer interfaces electrodes implanted reference standard home environment amyotrophic lateral sclerosis

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Spatio-temporal analysis of error-related brain activity in active and passive brain-computer interfaces

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brain-computer interfaces 2019年第4期6卷 118-127页

作者： Mousavi, M. de Sa, V. R. Univ Calif San Diego Dept Elect & Comp Engn San Diego CA 92103 USA Univ Calif San Diego Dept Cognit Sci San Diego CA 92103 USA Univ Calif San Diego Halicioglu Data Sci Inst San Diego CA 92103 USA

Electroencephalography (EEG)-based brain-computer interface (BCI) systems infer brain signals recorded via EEG without using common neuromuscular pathways. User brain response to BCI error is a contributor to non-stationarity of the EEG signal and poses challenges in developing reliable active BCI control. Many passive BCI implementations, on the other hand, have the detection of error-related brain activity as their primary goal. Therefore, reliable detection of this signal is crucial in both active and passive BCIs. In this work, we propose CREST: a novel covariance-based method that uses Riemannian and Euclidean geometry and combines spatial and temporal aspects of the feedback-related brain activity in response to BCI error. We evaluate our proposed method with two datasets: an active BCI for 1-D cursor control using motor imagery and a passive BCI for 2-D cursor control. We show significant improvement across participants in both datasets compared to existing methods.

关键词： brain-computer interfaces electroencephalography passive BCI BCI feedback error-related potentials error-related spectral perturbation Riemannian geometry common spatial patterns common temporal patterns

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Embodied Tools, Cognitive Tools and brain-computer interfaces

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NEUROETHICS 2013年第1期6卷 207-219页

作者： Heersmink, Richard Macquarie Univ Macquarie Ctr Cognit Sci Sydney NSW 2109 Australia

In this paper I explore systematically the relationship between brain-computer interfaces (BCIs) and their human users from a phenomenological and cognitive perspective. First, I functionally decompose BCI systems and develop a typology in which I categorize BCI applications with similar functional properties into three categories, those with (1) motor, (2) virtual, and (3) linguistic applications. Second, developing and building on the notions of an embodied tool and cognitive tool, I analyze whether these distinct BCI applications can be seen as bodily or cognitive extensions. Contrary to some recent philosophical claims, I will argue that, although BCI technology may have the potential to become bodily and cognitive extensions for skilled users, at this stage they are not. And while the electrodes may to a variable degree be transparent and incorporated in the body schema, the BCI system as a whole is not. Moreover, BCIs do not have a functional role characteristic for cognition and are therefore not cognitive extensions. Third, based on concepts from the distributed cognition framework, I give a number of suggestions to improve the interface design of linguistic applications, i.e. BCIs that allow its user to spell words by selecting letters on a screen. These suggestions may result in cognitive extension and would enhance the autonomy and quality of life of its users. In sum, in this paper I develop a typology, analysis and critique on the current philosophical debate on BCIs, thereby providing a richer conceptual understanding of BCI systems which allows me to offer some suggestions for improving the interface design of linguistic applications.

关键词： brain-computer interfaces Human-technology relations Extended cognition Trust Embodiment Cognitive artifacts Interface design Distributed cognition Quality of life Autonomy

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EEG-Based brain-computer interfaces A Novel Neurotechnology and Computational Intelligence Method

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IEEE SYSTEMS MAN AND CYBERNETICS MAGAZINE 2017年第4期3卷 16-26页

作者： Lin, Chin-Teng Liu, Yu-Ting Wu, Shang-Lin Cao, Zehong Wang, Yu-Kai Huang, Chih-Sheng King, Jung-Tai Chen, Shi-An Lu, Shao-Wei Chuang, Chun-Hsiang Univ Technol Sydney Fac Engn & Informat Technol Sydney NSW Australia NCTU Elect & Comp Engn Hsinchu Taiwan Univ Calif San Diego San Diego CA 92103 USA Univ Nottingham Nottingham England Univ Technol Sydney Sch Software Sydney NSW Australia MediaTek Inc Hsinchu Taiwan Natl Chiao Tung Univ Inst Elect Control Engn Hsinchu Taiwan Singular Wings Med Res & Dev Div Hsinchu Taiwan NCTU Brain Res Ctr Hsinchu Taiwan Natl Chiao Tung Univ Brain Res Ctr Hsinchu Taiwan

This article presents the latest BCI-related research done in our group. Our previous work applied computational intelligence technology in BCIs to inspire detailed investigations of practical issues in real-life applications. Novel EEG devices featuring dry electrodes facilitate and speed up electrode positioning before recording and allow subjects to move freely in operational environments. We also demonstrate the feasibility of applying CCA, RBFNs, effective connectivity measurements, and D-S theory to help BCIs extract informative knowledge from brain signals. Two recent trends in research in the computational and artificial intelligence community, big data and deep learning, are expected to impact the direction and development of BCIs.

关键词： Electroencephalography Electrodes Sensors Feature extraction Biometrics (access control) Cybernetics brain modeling brain-computer interfaces

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