Direct control of a computer from the human central nervous system.
By P. Kennedy, R. Bakay, M.M. Moore, Kim Adams, J. Goldwaithe. IEEE transactions on rehabilitation engineering, 2000
616 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Neurology
View Paper: https://www.semanticscholar.org/paper/ac8fae45d201e085963abdf271c547a6c648d60a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Jonathan R. Wolpaw
- Niels Birbaumer
- Mikhail A. Lebedev
- Miguel A. L. Nicolelis
- John P. Donoghue
- Dennis J. McFarland
- Gerwin Schalk
- Theresa M. Vaughan
In Cognitive Neuroscience
- Jonathan R. Wolpaw
- Niels Birbaumer
- Mikhail A. Lebedev
- Miguel A. L. Nicolelis
- Dennis J. McFarland
- John P. Donoghue
- Andrea Kübler
- Gert Pfurtscheller
In Neurology
- Jonathan R. Wolpaw
- Niels Birbaumer
- Gary E. Birch
- Mikhail A. Lebedev
- John P. Donoghue
- Gert Pfurtscheller
- Steven G. Mason
Citations in the corpus
- The Design of Integrated Circuits to Observe Brain Activity (2008, background): “Recent work in the field of neuroprosthetics has demonstrated that rats [12], monkeys [13]–[15], and paralyzed humans [ 16 ], [17] can learn to control robotic arms or computer cursors by thoughts if multiple neural signals from motor regions of the cerebral cortex are used for control.”
- Chronic neural recording using silicon-substrate microelectrode arrays implanted in cerebral cortex (2004, methodology): “At one extreme, locked-in patients with no voluntary muscle control have been able to control a brain-computer interface (BCI) system by volitional modulation of a small number of spike trains recorded using an invasive neurotrophic microelectrode permanently implanted in motor cortex [1].”
- Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. (2017, background): “A patient suffering from brain stem stroke received the implant in an unspecified cortical area and was able to control a computer cursor with the recorded signals (419).”
- Brain-computer interface technology: a review of the first international meeting. (2000, background): “…illustrate, BCI's may use frequency-domain features (such as EEG or rhythms occurring in specific areas of cortex) [6]–[9] and [11]–[14], or time-domain features (such as slow cortical potentials, P300 potentials, or the action potentials of single cortical neurons) [3]–[5], [10], [12], [15]–[18].”
- BCI2000: a general-purpose brain-computer interface (BCI) system (2004, background): “, [1]–[8]); see [9] for a comprehensive review.”
- Brain-computer interfaces for communication and control. (2002, methodology): “These electrodes, implanted in motor cortices of monkeys and several humans nearly locked-in by ALS or brainstem stroke, have provided stable neuronal recordings for more than a year (Kennedy and Bakay, 1998; Kennedy et al., 2000).”
- Cortical neural prosthetics. (2004, background): “Ideally, one would like to regulate the extraelectrode environment so that sprouting neurites are attracted to the vicinity of the recording surface before encapsulation takes place (Kennedy et al. 2000).”
- Brain-computer interfaces in medicine. (2012, background): “During the 4-year trial the patient learned to control a computer cursor.(105,106) Current research seeks to restore speech by implanting the device in the speech motor area and decoding phonemes from imagined speech.”
- Connecting cortex to machines: recent advances in brain interfaces (2002, neutral): “Neurotrophic recording electrodes are also being teste”
- Learning to control brain activity: a review of the production and control of EEG components for driving brain-computer interface (BCI) systems. (2003, methodology): “Research into BCI systems has mainly involved recording of electroencephalographic (EEG) signals using surface electrodes, although implanted electrodes have also been used (Kennedy et al., 2000).”