A binary method for simple and accurate two-dimensional cursor control from EEG with minimal subject training

Kayagil, Turan A; Bai, Ou; Henriquez, Craig S.; Lin, Peter; Furlani, S.; Vorbach, Sherry; Hallett, Mark

doi:10.1186/1743-0003-6-14

Cited by 27 publications

(30 citation statements)

References 26 publications

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“…We found that the discrimination of ERD from ERS was much more reliable than the discrimination of ERD from background activities in conventional BCI methods (Bai et al, 2008;Kayagil et al, 2009). A short-lasting burst of EEG oscillation, termed as beta rebound or beta-ERS, has been observed in beta band (16-30 Hz) over human sensorimotor area after subjects produce a self-paced movement (Salmelin et al, 1995;Pfurtscheller and Lopes da Silva, 1999;Neuper and Pfurtscheller, 2001).…”

Section: What Challenges Practical Applications Of Eeg-bci?mentioning

confidence: 93%

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A Two Dimensional Brain-Computer Interface Associated with Human Natural Motor Control

Huang¹,

Chen²,

Fei³

et al. 2011

Recent Advances in Brain-Computer Interface Systems

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Section: What Challenges Practical Applications Of Eeg-bci?mentioning

confidence: 93%

“…After an inter-trial interval randomly from 4 to 6 s, the next text message was provided. The detailed paradigm was provided in a previous study (Bai et al, 2008;Kayagil et al, 2009). Patients participated in both motor execution and motor imagery sessions.…”

Section: Binary and Four-directional Control Paradigms For 2d Controlmentioning

confidence: 99%

A Two Dimensional Brain-Computer Interface Associated with Human Natural Motor Control

Huang¹,

Chen²,

Fei³

et al. 2011

Recent Advances in Brain-Computer Interface Systems

Self Cite

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“…The acquisition and maintenance of BCI-based skills like reliable multidimensional movement control require comparable plasticity (eg, as described by various investigators 10,24,110,113 ). Brain-computer interface operation rests on the effective interaction of 2 adaptive controllers, the CNS and the BCI.…”

Section: Reliabilitymentioning

confidence: 99%

Brain-Computer Interfaces in Medicine

Shih

Krusienski

Wolpaw

2012

Mayo Clinic Proceedings

564

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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“…The output might be used to operate a spelling program on a computer screen through letter selection [6, 11], to move a cursor on a computer screen [12, 84, 85], to drive a wheelchair [86, 87] or other assistive devices [88], to manipulate a robotic arm [89, 90], or even to control movement of a paralyzed arm through a neuroprosthesis [15, 91]. At present, the most commonly used output device is the computer screen, and it is used for communication.…”

Section: Bci Definition Signal Types and Operationmentioning

confidence: 99%

Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects

Mak

Wolpaw

2009

IEEE Rev. Biomed. Eng.

421

204

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Brain-computer interfaces (BCIs) allow their users to communicate or control external devices using brain signals rather than the brain's normal output pathways of peripheral nerves and muscles. Motivated by the hope of restoring independence to severely disabled individuals and by interest in further extending human control of external systems, researchers from many fields are engaged in this challenging new work. BCI research and development have grown explosively over the past two decades. Efforts have recently begun to provide laboratory-validated BCI systems to severely disabled individuals for real-world applications. In this review, we discuss the current status and future prospects of BCI technology and its clinical applications. We will define BCI, review the BCIrelevant signals from the human brain, and describe the functional components of BCIs. We will also review current clinical applications of BCI technology, and identify potential users and potential applications. Finally, we will discuss current limitations of BCI technology, impediments to its widespread clinical use, and expectations for the future.

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A binary method for simple and accurate two-dimensional cursor control from EEG with minimal subject training

Cited by 27 publications

References 26 publications

A Two Dimensional Brain-Computer Interface Associated with Human Natural Motor Control

A Two Dimensional Brain-Computer Interface Associated with Human Natural Motor Control

Brain-Computer Interfaces in Medicine

Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects

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