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Relationship between the spatial pattern of P300 and performance of a P300-based brain-computer interface in amyotrophic lateral sclerosis

Relationship between the spatial pattern of P300 and performance of a P300-based brain-computer... AbstractThe P300-based brain-computer interface (P300-BCI) is expected to provide a new communication tool for patients with amyotrophic lateral sclerosis (ALS). Currently, there is little evidence about the relationship between the neurophysiological profiles of P300 and the performance of the P300-BCI in patients with ALS. In the present study, we investigate this relationship in detail. Patients were asked to input five characters using a traditional row/column speller which consisted of a 7 × 10 matrix. EEGs were recorded using eight electrodes. The on-line P300-BCI performance was then compared with the neurophysiological profiles of P300. We found that patients who had a robust P300 response over the occipital area showed a higher success rate in the P300-BCI compared with patients who had a large P300 response over the fronto-central area. These results suggest that appropriate evaluation of the neurophysiological aspects of P300 may lead to prediction of and improvement in the P300-BCI performance. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Brain-Computer Interfaces Taylor & Francis

Relationship between the spatial pattern of P300 and performance of a P300-based brain-computer interface in amyotrophic lateral sclerosis

Relationship between the spatial pattern of P300 and performance of a P300-based brain-computer interface in amyotrophic lateral sclerosis

Abstract

AbstractThe P300-based brain-computer interface (P300-BCI) is expected to provide a new communication tool for patients with amyotrophic lateral sclerosis (ALS). Currently, there is little evidence about the relationship between the neurophysiological profiles of P300 and the performance of the P300-BCI in patients with ALS. In the present study, we investigate this relationship in detail. Patients were asked to input five characters using a traditional row/column speller which consisted of a...
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Publisher
Taylor & Francis
Copyright
© 2016 Taylor & Francis
ISSN
2326-2621
eISSN
2326-263x
DOI
10.1080/2326263X.2015.1132080
Publisher site
See Article on Publisher Site

Abstract

AbstractThe P300-based brain-computer interface (P300-BCI) is expected to provide a new communication tool for patients with amyotrophic lateral sclerosis (ALS). Currently, there is little evidence about the relationship between the neurophysiological profiles of P300 and the performance of the P300-BCI in patients with ALS. In the present study, we investigate this relationship in detail. Patients were asked to input five characters using a traditional row/column speller which consisted of a 7 × 10 matrix. EEGs were recorded using eight electrodes. The on-line P300-BCI performance was then compared with the neurophysiological profiles of P300. We found that patients who had a robust P300 response over the occipital area showed a higher success rate in the P300-BCI compared with patients who had a large P300 response over the fronto-central area. These results suggest that appropriate evaluation of the neurophysiological aspects of P300 may lead to prediction of and improvement in the P300-BCI performance.

Journal

Brain-Computer InterfacesTaylor & Francis

Published: Jan 2, 2016

Keywords: Brain-computer interfaces; amyotrophic lateral sclerosis (ALS); P300; ERP; spatial distribution

References