Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces
TL;DR: Novel methods for detecting steady-state visual evoked potentials using multiple electroencephalogram (EEG) signals are presented, tailored for brain-computer interfacing, where fast and accurate detection is of vital importance for achieving high information transfer rates.
Abstract: In this paper, novel methods for detecting steady-state visual evoked potentials using multiple electroencephalogram (EEG) signals are presented. The methods are tailored for brain-computer interfacing, where fast and accurate detection is of vital importance for achieving high information transfer rates. High detection accuracy using short time segments is obtained by finding combinations of electrode signals that cancel strong interference signals in the EEG data. Data from a test group consisting of 10 subjects are used to evaluate the new methods and to compare them to standard techniques. Using 1-s signal segments, six different visual stimulation frequencies could be discriminated with an average classification accuracy of 84%. An additional advantage of the presented methodology is that it is fully online, i.e., no calibration data for noise estimation, feature extraction, or electrode selection is needed
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TL;DR: The steady-state evoked activity, its properties, and the mechanisms behind SSVEP generation are investigated and future research directions related to basic and applied aspects of SSVEPs are outlined.
898 citations
Cites background from "Multiple Channel Detection of Stead..."
...However, doubts have been raised about ICA, especially in the context of BCI systems; statistical independence may not be a valid assumption, and it is not always obvious how to rank the independent sources (Friman et al., 2007)....
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...- B est classification results are usually reached by using a bipolar derivation (Wang et al., 2005b; Lin et al., 2006; Friman et al., 2007; Müller-Putz et al., 2008)....
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TL;DR: The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.
Abstract: Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials were first introduced over 80 years ago as a means to study visual sensation and perception. From the first single-channel recording of responses to modulated light to the present use of sophisticated digital displays composed of complex visual stimuli and high-density recording arrays, steady-state methods have been applied in a broad range of scientific and applied settings.The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.
875 citations
TL;DR: The positive characteristics of the proposed SSVEP-based BCI system are that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.
Abstract: In recent years, there has been increasing interest in using steady-state visual evoked potential (SSVEP) in brain–computer interface (BCI) systems. However, several aspects of current SSVEP-based BCI systems need improvement, specifically in relation to speed, user variation and ease of use. With these improvements in mind, this paper presents an online multi-channel SSVEP-based BCI system using a canonical correlation analysis (CCA) method for extraction of frequency information associated with the SSVEP. The key parameters, channel location, window length and the number of harmonics, are investigated using offline data, and the result used to guide the design of the online system. An SSVEP-based BCI system with six targets, which use nine channel locations in the occipital and parietal lobes, a window length of 2 s and the first harmonic, is used for online testing on 12 subjects. The results show that the proposed BCI system has a high performance, achieving an average accuracy of 95.3% and an information transfer rate of 58 ± 9.6 bit min−1. The positive characteristics of the proposed system are that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.
694 citations
Cites background or methods from "Multiple Channel Detection of Stead..."
...Friman et al [9] proposed a minimum energy method (MEC) which shows many advantages such as high detection accuracy and no calibration data....
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...The previous multiple-channel method usually performed these two steps separately [9]....
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01 Jul 1976
TL;DR: Electrical and computer engineering ece courses ece 257a multiuser communication systems 4 congestion control convex programming and dual controller fair end end rate allocation max min fair vs proportional, electrical systems engineering washington university.
Abstract: electrical and computer engineering ece courses ece 257a multiuser communication systems 4 congestion control convex programming and dual controller fair end end rate allocation max min fair vs proportional, electrical systems engineering washington university arye nehorai eugene and martha lohman professor of electrical engineering phd stanford university signal processing imaging biomedicine communications, ieee transactions on aerospace and electronic systems ieee transactions on aerospace and electronic systems focuses on the organization design development integration and operation of complex systems for space air, department of electrical engineering and computer science h kumar wickramsinghe department chair 2213 engineering hall 949 824 4821 http www eng uci edu dept eecs overview electrical engineering and computer science is, download electrical and electronics engineering ebooks syst mes temps discret commande num rique des proc d s pdf 499 ko terminology and symbols in control engineering pdf 326 ko the best of thomas, publications stream wise list iit kanpur papers published in journals in 2016 dutta s patchaikani p k behera l near optimal controller for nonlinear continuous time systems with unknown dynamics, resolve a doi name type or paste a doi name into the text box click go your browser will take you to a web page url associated with that doi name send questions or comments to doi, peer reviewed journal ijera com international journal of engineering research and applications ijera is an open access online peer reviewed international journal that publishes research, dod sbir 2016 2 sbir gov note the solicitations and topics listed on this site are copies from the various sbir agency solicitations and are not necessarily the latest and most up, an english japanese dictionary of electrical engineering c 2952 9 691 c band c c contact c c maccs centre for mathematical modelling and computer simulation, the of and to a in that is was he for it with as his on be most common text click on the icon to return to www berro com and to enjoy and benefit the of and to a in that is was he for it with as his on be at by i this had
590 citations
TL;DR: This paper reviews the literature on SSVEP-based BCIs and comprehensively reports on the different RVS choices in terms of rendering devices, properties, and their potential influence on BCI performance, user safety and comfort.
Abstract: Brain-computer interface (BCI) systems based on the steady-state visual evoked potential (SSVEP) provide higher information throughput and require shorter training than BCI systems using other brain signals. To elicit an SSVEP, a repetitive visual stimulus (RVS) has to be presented to the user. The RVS can be rendered on a computer screen by alternating graphical patterns, or with external light sources able to emit modulated light. The properties of an RVS (e.g., frequency, color) depend on the rendering device and influence the SSVEP characteristics. This affects the BCI information throughput and the levels of user safety and comfort. Literature on SSVEP-based BCIs does not generally provide reasons for the selection of the used rendering devices or RVS properties. In this paper, we review the literature on SSVEP-based BCIs and comprehensively report on the different RVS choices in terms of rendering devices, properties, and their potential influence on BCI performance, user safety and comfort.
563 citations
Cites methods from "Multiple Channel Detection of Stead..."
...2007 [34] LED 5, 7, 9, 11, 13, 15 Hz — —...
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...Additionally, spatial filters that combine several lead signals into one channel [34] can be used to increase the SSVEP energy enough so it can effectively be used in a BCI....
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References
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TL;DR: With adequate recognition and effective engagement of all issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
6,803 citations
"Multiple Channel Detection of Stead..." refers background in this paper
...Another important consideration in brain-computer interfacing is whether the BCI is of a dependent or independent type [13]....
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01 Jan 1988
2,657 citations
"Multiple Channel Detection of Stead..." refers methods in this paper
...The models are efficiently fitted by invoking the Wiener-Khinchin theorem for computing the autocovariance of each channel signal and then solving the Yule-Walker equations using a Levinson-Durbin recursion [28]....
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TL;DR: In this article, the authors present an overview of the physics-EEG interface, including the physics of electromagnetic fields and EEG, as well as EEG-based recording strategies, reference issues, and dipole localization.
Abstract: 1. The physics-EEG interface 2. Fallacies in EEG 3. An overview of electromagnetic fields 4. Electric fields and currents in biological tissue 5. Current sources in a homogeneous and isotropic medium 6. Current sources in inhomogeneous and isotropic media 7. Recording strategies, reference issues, and dipole localization 8. High-resolution EEG 9. Measures of EEG dynamic properties 10. Spatial-temporal properties of EEG 11. Neocortical dynamics, EEG, and cognition APPENDICES A. Introduction to the calculus of vector fields B. Quasi-static reduction of Maxwell's equations C. Surface magnetic field due to a dipole at an arbitrary location in a volume conductor D. Derivation of the membrane diffusion equation E. Solutions to the membrane diffusion equation F. Point source in a five layered plane medium G. Radial dipole and dipole layer inside the 4-sphere model H. Tangential dipole inside concentric spherical shells I. Spherical harmonics J. The spline Laplacian K. Impressed currents and cross-scale relations in volume conductors L. Outline of neocortical dynamic global theory
2,484 citations
01 Dec 2000
TL;DR: It is demonstrated that spatial filters for multichannel EEG effectively extract discriminatory information from two populations of single-trial EEG, recorded during left- and right-hand movement imagery.
Abstract: The development of an electroencephalograph (EEG)-based brain-computer interface (BCI) requires rapid and reliable discrimination of EEG patterns, e.g., associated with imaginary movement. One-sided hand movement imagination results in EEG changes located at contra- and ipsilateral central areas. The authors demonstrate that spatial filters for multichannel EEG effectively extract discriminatory information from two populations of single-trial EEG, recorded during left- and right-hand movement imagery. The best classification results for three subjects are 90.8%, 92.7%, and 99.7%. The spatial filters are estimated from a set of data by the method of common spatial patterns and reflect the specific activation of cortical areas. The method performs a weighting of the electrodes according to their importance for the classification task. The high recognition rates and computational simplicity make it a promising method for an EEG-based brain-computer interface.
2,217 citations
"Multiple Channel Detection of Stead..." refers background in this paper
...In the EEG literature, this is sometimes referred to as a spatial filter, and producing such combinations is a well established procedure in EEG signal processing [33]–[35]....
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01 Jun 2000
TL;DR: The first international meeting devoted to brain-computer interface research and development is summarized, which focuses on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users.
Abstract: Over the past decade, many laboratories have begun to explore brain-computer interface (BCI) technology as a radically new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. BCI's provide these users with communication channels that do not depend on peripheral nerves and muscles. This article summarizes the first international meeting devoted to BCI research and development. Current BCI's use electroencephalographic (EEG) activity recorded at the scalp or single-unit activity recorded from within cortex to control cursor movement, select letters or icons, or operate a neuroprosthesis. The central element in each BCI is a translation algorithm that converts electrophysiological input from the user into output that controls external devices. BCI operation depends on effective interaction between two adaptive controllers, the user who encodes his or her commands in the electrophysiological input provided to the BCI, and the BCI which recognizes the commands contained in the input and expresses them in device control. Current BCI's have maximum information transfer rates of 5-25 b/min. Achievement of greater speed and accuracy depends on improvements in signal processing, translation algorithms, and user training. These improvements depend on increased interdisciplinary cooperation between neuroscientists, engineers, computer programmers, psychologists, and rehabilitation specialists, and on adoption and widespread application of objective methods for evaluating alternative methods. The practical use of BCI technology depends on the development of appropriate applications, identification of appropriate user groups, and careful attention to the needs and desires of individual users. BCI research and development will also benefit from greater emphasis on peer-reviewed publications, and from adoption of standard venues for presentations and discussion.
2,121 citations
Additional excerpts
...A BCI translates brain activity patterns into control commands [12]–[14], e....
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