D
Dennis J. McFarland
Researcher at New York State Department of Health
Publications - 176
Citations - 31685
Dennis J. McFarland is an academic researcher from New York State Department of Health. The author has contributed to research in topics: Brain–computer interface & Sensorimotor rhythm. The author has an hindex of 62, co-authored 176 publications receiving 29030 citations. Previous affiliations of Dennis J. McFarland include University at Albany, SUNY & Wadsworth Center.
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Journal ArticleDOI
Brain-computer interfaces for communication and control.
Jonathan R. Wolpaw,Jonathan R. Wolpaw,Niels Birbaumer,Niels Birbaumer,Dennis J. McFarland,Gert Pfurtscheller,Theresa M. Vaughan +6 more
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.
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BCI2000: a general-purpose brain-computer interface (BCI) system
TL;DR: This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BCI2000 system is based upon and gives examples of successful BCI implementations using this system.
Journal ArticleDOI
Brain-computer interfaces for communication and control
TL;DR: The brain's electrical signals enable people without muscle control to physically interact with the world through the use of their brains' electrical signals.
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Brain-computer interface technology: a review of the first international meeting
Jonathan R. Wolpaw,Niels Birbaumer,W.J. Heetderks,Dennis J. McFarland,Paul Hunter Peckham,Gerwin Schalk,Emanuel Donchin,L.A. Quatrano,C.J. Robinson,C.J. Robinson,Theresa M. Vaughan +10 more
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.
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Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans
TL;DR: It is shown that a noninvasive BCI that uses scalp-recorded electroencephalographic activity and an adaptive algorithm can provide humans, including people with spinal cord injuries, with multidimensional point-to-point movement control that falls within the range of that reported with invasive methods in monkeys.