A P300-based brain-computer interface: initial tests by ALS patients.

By Eric W. Sellers, Emanuel Donchin. Clinical Neurophysiology, 2006

810 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/66f4d9d4e2fc7857152b56bd712ad754d755e7de

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

In Human-Computer Interaction

Citations in the corpus

The brain–computer interface cycle (2009, background): “For example, area under the ROC curve is only applicable in the case of binary classification problems whereas the bit rate can be misleading due to the exclusion of intertrial intervals or due to the fact that systematic misclassification may even increase the bit rate [44].”
Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. (2009, background): “P300 may also serve as a mediating response, allowing brain control of prosthetic devices (Donchin et al., 2000; Sellers and Donchin, 2006; Nijboer et al., 2008).”
Visual and Auditory Brain–Computer Interfaces (2014, background): “Although the v-BCIs and a-BCIs have mainly been developed towards clinical applications, very few studies have been carried out in patients [6, 14, 15, 16, 17, 18, 19, 71].”
An auditory oddball (P300) spelling system for brain-computer interfaces. (2009, methodology): “After its first description as an input signal for BCI in 1988 by Farwell and Donchin, the P300 component of the event-related potential (ERP) has been recently explored intensively with regards to its triggering, detection, usability for communication, and habituation during long-term use (Nijboer ”
Brain–computer interfaces: communication and restoration of movement in paralysis (2007, background): “Journal compilation C© 2007 The Physiological Society P300 ERP appears in the EEG selecting the desired letter (Sellers & Donchin, 2006).”
BCI Demographics: How Many (and What Kinds of) People Can Use an SSVEP BCI? (2010, background): “selections, which is done in some papers, could increase ITR at the cost of providing a less realistic picture of BCI operation (discussed in [42]).”
(C)overt attention and visual speller design in an ERP-based brain-computer interface (2010, background): “Second, successful communication using ERP-based visual spellers has been demonstrated in ALS patients [21,22], but in progressed stages of the disease, oculomotor control can deteriorate.”
A Brain–Computer Interface Controlled Auditory Event‐Related Potential (P300) Spelling System for Locked‐In Patients (2009, methodology): “Previous studies of classiﬁcation methods demonstrated that SWLDA provides good overall performance in classifying both visual P300 11 , 12 , 21 , 31 and auditory P300 within the frame of BCI.”
A comparison of classification techniques for the P300 Speller (2006, background): “Recent studies have demonstrated that a P300based BCI trained on a limited amount of data can serve as an effective communication device [1, 13, 14].”
Toward enhanced P300 speller performance. (2008, neutral): “In the previous work on SWLDA for classifying P300 responses (BCI, 2003; Farwell and Donchin, 1988; Sellers and Donchin, 2006), only channels Fz, Cz, and Pz were used for analysis.”
Brain-machine interfaces: past, present and future. (2006, positive): “Off-line analyses showed that P300 potentials can be used to obtain information about stimulus selections made by patients with ALS [ 22 ].”
A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns (2010, background): “Moreover, with the RCP, some people are not able to achieve accuracy high enough for practical BCI use (Sellers and Donchin, 2006).”