Brain–computer interfaces for communication and control

Wolpaw, Jonathan R.; Birbaumer, Niels; McFarland, Dennis J.; Pfurtscheller, Gert; Vaughan, Theresa M.

doi:10.1016/s1388-2457(02)00057-3

Cited by 6,643 publications

(3,674 citation statements)

References 141 publications

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“…We here demonstrated the feasibility of online communication with a covert SSVEP paradigm that is truly independent of neuromuscular function and gaze control [1]. We could functionally communicate with eight out of twelve healthy subjects.…”

Section: Resultsmentioning

confidence: 90%

“…Brain-computer interfaces (BCIs) [1] translate measures of brain activity into messages or commands and provide a direct 6 Both authors contributed equally. connection between the human brain and a computer.…”

Section: Introductionmentioning

confidence: 99%

“…Current BCIs relying on VEPs depend on gaze control [16,17] and thus fall into the category of dependent BCIs [1]. Therefore, these BCIs are not applicable to those whose severe disabilities extend to impaired or nonexistent ocular motor control, such as LIS patients in which (i) eye movements may be inconsistent, very small and easily exhausted in the acute stage and (ii) deteriorated or nonexistent oculomotor control could be observed in the chronic stage.…”

Section: Introductionmentioning

confidence: 99%

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An independent SSVEP-based brain–computer interface in locked-in syndrome

et al. 2014

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Objective. Steady-state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs) allow healthy subjects to communicate. However, their dependence on gaze control prevents their use with severely disabled patients. Gaze-independent SSVEP-BCIs have been designed but have shown a drop in accuracy and have not been tested in brain-injured patients. In the present paper, we propose a novel independent SSVEP-BCI based on covert attention with an improved classification rate. We study the influence of feature extraction algorithms and the number of harmonics. Finally, we test online communication on healthy volunteers and patients with locked-in syndrome (LIS). Approach. Twenty-four healthy subjects and six LIS patients participated in this study. An independent covert two-class SSVEP paradigm was used with a newly developed portable light emitting diode-based 'interlaced squares' stimulation pattern. Main results. Mean offline and online accuracies on healthy subjects were respectively 85 ± 2% and 74 ± 13%, with eight out of twelve subjects succeeding to communicate efficiently with 80 ± 9% accuracy. Two out of six LIS patients reached an offline accuracy above the chance level, illustrating a response to a command. One out of four LIS patients could communicate online. Significance. We have demonstrated the feasibility of online communication with a covert SSVEP paradigm that is truly independent of all neuromuscular functions. The potential clinical use of the presented BCI system as a diagnostic (i.e., detecting command-following) and communication tool for severely brain-injured patients will need to be further explored.

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Section: Resultsmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An independent SSVEP-based brain–computer interface in locked-in syndrome

et al. 2014

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“…In contrast, a brain-computer interface (BCI) is a technology that utilizes neurophysiological signals directly from the brain to control external devices, bypassing the natural muscular output [1]. Currently, BCI systems based on electroencephalography (EEG) can provide severely motordisabled people with a new output channel to voluntarily control applications for communication and environmental control [2,3,4,5,6,7,8].…”

Section: Introductionmentioning

confidence: 99%

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Pokorny

Klobassa

Pichler

et al. 2013

Artificial Intelligence in Medicine

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Objective: Within this work an auditory P300 brain-computer interface (BCI) based on tone stream segregation, which allows for binary decisions, was developed and evaluated. Materials and methods: Two tone streams consisting of short beep tones with infrequently appearing deviant tones at random positions were used as stimuli. This paradigm was evaluated in 10 healthy subjects and applied to 12 patients in a minimally conscious state (MCS) at clinics in Graz, Würzburg, Rome, and Liège. A stepwise linear discriminant analysis (SWLDA) classifier with 10 × 10 cross-validation was used to detect the presence of any P300 and to investigate attentional modulation of the P300 amplitude. Results:The results for healthy subjects were promising and most classification results were better than random. However, for MCS patients only a small number of classification results were above chance level and none of the results were sufficient for communication purposes. Nevertheless, signs of consciousness were detected in most patients, not on a single-trial basis, but after averaging of corresponding data segments and computing significant differences. These significant results, however, strongly varied across sessions and conditions. Conclusion: This work shows the transition of a paradigm from healthy subjects to MCS patients. Promising results with healthy subjects are, however, no guarantee of good results with patients. Therefore, more investigations are required before any definite conclusions about the usability of this paradigm for MCS patients can be drawn. Nevertheless, this paradigm might offer an opportunity to support bedside clinical assessment of MCS patients and eventually, to provide them with a means of communication.

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“…Brain-Computer Interfaces (BCI) are alternative communication systems between human and machine without involving the brain's normal output pathways or peripheral nerves and muscles [1]. In contrast to commonly used human-machine interfaces, which require voluntary movements (e.g.…”

Section: Introductionmentioning

confidence: 99%

Subject response variability in terms of colour and frequency of capacitive SSVEP measurements

Gerloff

Schilling

2012

Biomedical Engineering / Biomedizinische Technik

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With the capacitive 8-channel EEG helmet system, the measurement of steady-state visually evoked potentials (SSVEP) has already been successfully demonstrated. To increase the signal quality and the user comfort of helmet and system control for BCI applications, colour and frequency of the signal-evoking flickering checkerboard pattern are changed from black/white and fixed frequencies to colour combinations of various frequencies. Individual optimal combinations and response variability between subjects are evaluated. Seven colour combinations and the stimulating frequency range from 6 Hz to 17 Hz were chosen for colour-frequency scans. To avoid the fatigue effect of long measurements, each scan was divided into parts, measured separately and assembled afterwards. Seven subjects were measured, three runs each. As expected, the optimal stimulation combination of colour and frequency varies a lot between the subjects. This confirms that an individual-optimized adjustment of the stimulation is recommended. It is indispensable for high performance applications based on SSVEP.

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Brain–computer interfaces for communication and control

Cited by 6,643 publications

References 141 publications

An independent SSVEP-based brain–computer interface in locked-in syndrome

An independent SSVEP-based brain–computer interface in locked-in syndrome

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients

Subject response variability in terms of colour and frequency of capacitive SSVEP measurements

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