Natural language processing with dynamic classification improves P300 speller accuracy and bit rate

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Natural language processing with dynamic classification improves P300 speller accuracy and bit rate.

The P300 speller is an example of a brain-computer interface that can restore functionality to victims of neuromuscular disorders. Although the most common application of this system has been communicating language, the properties and constraints of the linguistic domain have not to date been exploited when decoding brain signals that pertain to language. We hypothesized that combining the stan...

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Improved P300 speller performance using electrocorticography, spectral features, and natural language processing.

OBJECTIVE The P300 speller is a system designed to restore communication to patients with advanced neuromuscular disorders. This study was designed to explore the potential improvement from using electrocorticography (ECoG) compared to the more traditional usage of electroencephalography (EEG). METHODS We tested the P300 speller on two epilepsy patients with temporary subdural electrode array...

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P300 Speller with Enhanced Accuracy in Brain Computer Interface

Communication channel connecting the brain to a computer or other electronic devices is nothing but brain computer interface (BCI). The information extraction from brain is a very demanding task. Brain signals are mixed with other signals or noises coming from a finite set of brain activities that overlap in both time and space. Electroencephalogram (EEG) has been the most popular signal that i...

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Accuracy of a P300 Speller for different conditions: A comparison

When using a Brain-Computer Interface (BCI) as a spelling device, the P300-based BCI is mostly common, because of its high speed and accuracy, compared to other BCI paradigms. During the last years many studies have been performed to optimize the single spelling parameters, the stimulation frequency and stimulation intensity. Also different options for the electrode position and classification ...

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A comparison of stimulus types in online classification of the P300 speller using language models

The P300 Speller is a common brain-computer interface communication system. There are many parallel lines of research underway to overcome the system's low signal to noise ratio and thereby improve performance, including using famous face stimuli and integrating language information into the classifier. While both have been shown separately to provide significant improvements, the two methods h...

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ژورنال

عنوان ژورنال: Journal of Neural Engineering

سال: 2011

ISSN: 1741-2560,1741-2552

DOI: 10.1088/1741-2560/9/1/016004