The brain response interface: communication through visually-induced electrical brain responses

Sutter, Erich E.

doi:10.1016/0745-7138(92)90045-7

Cited by 357 publications

(238 citation statements)

References 2 publications

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“…They can exhibit good information throughput relative to other BCIs (Sutter, 1992;Cheng et al, 2002;Gao et al, 2003;Müller-Putz et al, 2005). They can operate in challenging environments with uncontrolled distraction and electrical noise (Cheng et al, 2002;Wang et al, 2004;Trejo et al, 2006) and hence could work well in homes or hospital settings.…”

Section: 4: Future Directions With Ssvep Bcismentioning

confidence: 99%

“…SSVEP BCI articles typically note that subjects were told to shift gaze (Sutter et al, 1992;Middendorf et al, 2000;Cheng et al, 2002;Gao et al, 2003). Two BCI reviews (Kübler et al, 2001;Wolpaw et al, 2002) define SSVEP BCIs as "dependent" BCIs, meaning that they use EEG features that depend on muscle activity and thus would not work in patients without control over that activity.…”

Section: Introductionmentioning

confidence: 99%

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Towards an independent brain–computer interface using steady state visual evoked potentials

Allison

McFarland

Schalk

et al. 2008

Clinical Neurophysiology

284

183

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Objective-Brain -computer interface (BCI) systems using steady state visual evoked potentials (SSVEPs) have allowed healthy subjects to communicate. However, these systems may not work in severely disabled users because they may depend on gaze shifting. This study evaluates the hypothesis that overlapping stimuli can evoke changes in SSVEP activity sufficient to control a BCI. This would provide evidence that SSVEP BCIs could be used without shifting gaze.Methods-Subjects viewed a display containing two images that each oscillated at a different frequency. Different conditions used overlapping or non-overlapping images to explore dependence on gaze function. Subjects were asked to direct attention to one or the other of these images during each of twelve one-minute runs.Results-Half of the subjects produced differences in SSVEP activity elicited by overlapping stimuli that could support BCI control. In all remaining users, differences did exist at corresponding frequencies but were not strong enough to allow effective control.Conclusions-The data demonstrate that SSVEP differences sufficient for BCI control may be elicited by selective attention to one of two overlapping stimuli. Thus, some SSVEP-based BCI approaches may not depend on gaze control. The nature and extent of any BCI's dependence on muscle activity is a function of many factors, including the display, task, environment, and user.Significance-SSVEP BCIs might function in severely disabled users unable to reliably control gaze. Further research with these users is necessary to explore the optimal parameters of such a system and validate online performance in a home environment.

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Section: 4: Future Directions With Ssvep Bcismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Towards an independent brain–computer interface using steady state visual evoked potentials

Allison

McFarland

Schalk

et al. 2008

Clinical Neurophysiology

284

183

View full text Add to dashboard Cite

show abstract

“…On the other hand, P300-based BCIs are much less dependent than steady-state visual evoked potentials based BCIs on eye-movement control. Steady-state visual evoked potentials have been used for binary selection, [48][49][50][51] both discrete and continuous control of a cursor in 2 dimensions, 52 prosthesis control, 53 FES, 54,55 spelling, 56 and environmental control. 57 For patients with impaired vision, various auditory 39,40,[58][59][60][61] and tactile [62][63][64][65] paradigms have been investigated.…”

Section: Device Outputmentioning

confidence: 99%

Brain-Computer Interfaces in Medicine

Shih

Krusienski

Wolpaw

2012

Mayo Clinic Proceedings

544

279

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Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. U ntil recently, the dream of being able to control one's environment through thoughts had been in the realm of science fiction. However, the advance of technology has brought a new reality: Today, humans can use the electrical signals from brain activity to interact with, influence, or change their environments. The emerging field of brain-computer interface (BCI) technology may allow individuals unable to speak and/or use their limbs to once again communicate or operate assistive devices for walking and manipulating objects. Brain-computer interface research is an area of high public awareness. Videos on YouTube as well as news reports in the lay media indicate intense curiosity and interest in a field that hopefully one day soon will dramatically improve the lives of many disabled persons affected by a number of different disease processes.This review seeks to provide the general medical community with an introduction to BCIs. We define BCI and then review some of the seminal discoveries in this rapidly emerging field, the brain signals used by BCIs, the essential components of a BCI system, current BCI systems, and the key issues now engaging researchers. Challenges are inherent in translating any new technology to practical and useful clinical applications, and BCIs are no exception. We discuss the potent...

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“…Numbers of study on BCI have been using one or a combination of these frequency bands in order to access variety of brain signal component such as visual evoked potentials [22], [23], slow cortical potentials [24], [25], P300 evoked potentials [26], [27], mu and beta rhythms [28], [29] and cortical neuronal action potentials [30].…”

Section: Signal Analysis Of Eeg Band Signalmentioning

confidence: 99%

“…This study measured ERD/ERS through mu (8)(9)(10)(11)(12)(13) and beta bands (14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). The ERD/ERS was quantified following standard calculation of Pfurtscheller and Aranibar [35].…”

Section: Signal Analysis Of Eeg Band Signalmentioning

confidence: 99%

Brain Computer Interface: Assessment of Spinal Cord Injury Patient towards Motor Movement through EEG application

et al. 2017

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Abstract. Electroencephalography (EEG) associated with motor task have been comprehensively investigated and it can also describe the brain activities while spinal cord injury (SCI) patient with para/tetraplegia performing movement with their limbs. This paper reviews on conducted research regarding application of brain computer interface (BCI) that offer alternative for neural impairments community such as spinal cord injury patient (SCI) which include the experimental design, signal analysis of EEG band signal and data processing methods. The findings claim that the EEG signals of SCI patients associated with movement tasks can be stimulated through mental and motor task. Other than that EEG signal component such as alpha and beta frequency bands indicate significance for analysing the brain activity of subjects with SCI during movements.

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The brain response interface: communication through visually-induced electrical brain responses

Cited by 357 publications

References 2 publications

Towards an independent brain–computer interface using steady state visual evoked potentials

Towards an independent brain–computer interface using steady state visual evoked potentials

Brain-Computer Interfaces in Medicine

Brain Computer Interface: Assessment of Spinal Cord Injury Patient towards Motor Movement through EEG application

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