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

Allison, Brendan Z.; McFarland, Dennis J.; Schalk, Gerwin; Zheng, Shi Dong; Jackson, Melody Moore; Wolpaw, Jonathan R.

doi:10.1016/j.clinph.2007.09.121

Cited by 285 publications

(197 citation statements)

References 42 publications

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“…Mean online accuracy on healthy subjects able to communicate was 80.3 ± 8.6%. Offline analysis showed that healthy subjects succeeded in reaching an average accuracy of 85% (with three subjects out of ten reaching more than 94%), which exceeds accuracies of previous covert SSVEP-based BCIs [18][19][20]. Moreover, the proposed 'interlaced squares' stimulation pattern is small, portable, easy to use and adapted for bedside use with patients, features which are not shared by other covert stimulation devices requiring a cathode ray tube screen.…”

Section: Discussionmentioning

confidence: 80%

“…The panel, placed at 30 cm from subject's head, is a 7 × 7 cm 2 'interlaced square' made of red and yellow 1 × 1 cm 2 light emitting diode (LED)-squares with a white fixation cross in the middle (see figure 1). The interlaced square pattern showed a 10% improvement in accuracy in comparison with a 'line' pattern [19]. The control unit is an electronic embedded system used for precise control of red and yellow flickering frequencies, which can be varied independently between 1 and 99 Hz by a programmable integrated circuit microcontroller.…”

Section: Data Collectionmentioning

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: Discussionmentioning

confidence: 80%

Section: Data Collectionmentioning

confidence: 99%

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

et al. 2014

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“…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

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562

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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“…Cette exigence ne pose aucun problème pour des sujets sains, mais limite fortement l'application de l'interface chez des patients dont le handicap moteur s'étend au contrôle oculaire (altéré ou inexistant). Afin de pouvoir utiliser ce système indépendamment du contrôle du regard, l'utilisation de l'attention implicite (covert attention) a été proposée [24][25][26]. Dans cette situation, le sujet se concentre mentalement sur le stimulus cible sans bouger les yeux.…”

Section: Vers Un Paradigme Visuel Indépendantunclassified