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Journal ArticleDOI

The wadsworth BCI research and development program: at home with BCI

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TLDR
It is shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions, which has resulted in prototype systems for every day use in people's homes.
Abstract
The ultimate goal of brain-computer interface (BCI) technology is to provide communication and control capacities to people with severe motor disabilities. BCI research at the Wadsworth Center focuses primarily on noninvasive, electroencephalography (EEG)-based BCI methods. We have shown that people, including those with severe motor disabilities, can learn to use sensorimotor rhythms (SMRs) to move a cursor rapidly and accurately in one or two dimensions. We have also improved P300-based BCI operation. We are now translating this laboratory-proven BCI technology into a system that can be used by severely disabled people in their homes with minimal ongoing technical oversight. To accomplish this, we have: improved our general-purpose BCI software (BCI2000); improved online adaptation and feature translation for SMR-based BCI operation; improved the accuracy and bandwidth of P300-based BCI operation; reduced the complexity of system hardware and software and begun to evaluate home system use in appropriate users. These developments have resulted in prototype systems for every day use in people's homes.

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Citations
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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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A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update

TL;DR: A comprehensive overview of the modern classification algorithms used in EEG-based BCIs is provided, the principles of these methods and guidelines on when and how to use them are presented, and a number of challenges to further advance EEG classification in BCI are identified.
Journal ArticleDOI

Brain-computer interfaces in neurological rehabilitation.

TL;DR: Non-invasive, electroencephalogram (EEG)-based brain-computer interface technologies can be used to control a computer cursor or a limb orthosis, for word processing and accessing the internet, and for other functions such as environmental control or entertainment.
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A comparison of classification techniques for the P300 Speller

TL;DR: The results indicate that while all methods attained acceptable performance levels, SWLDA and FLD provide the best overall performance and implementation characteristics for practical classification of P300 Speller data.
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Toward enhanced P300 speller performance

TL;DR: By supplementing the classical P300 recording locations with posterior locations, online classification performance of P300 speller responses can be significantly improved using SWLDA and the favorable parameters derived from the offline comparative analysis.
References
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Journal ArticleDOI

Brain-computer interfaces for communication and control.

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.
Journal ArticleDOI

Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials

TL;DR: The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec, which means that subjects can communicate 12.0 bits, or 2.3 characters, per min.
Journal ArticleDOI

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

The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function

TL;DR: A revised version of the ALSFRS, which incorporates additional assessments of dyspnea, orthopnea, and the need for ventilatory support is validated, indicating that the quality of function is a strong determinant of quality of life in ALS.
Journal ArticleDOI

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.
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