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Online transcranial Doppler ultrasonographic control of an onscreen keyboard
Brain-computer interface (BCI) systems exploit brain activity for generating a control command and may be used by individuals with severe motor disabilities as an alternative means of communication. An emerging brain monitoring modality for BCI development is transcranial Doppler ultrasonography (TC...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001051/ https://www.ncbi.nlm.nih.gov/pubmed/24795590 http://dx.doi.org/10.3389/fnhum.2014.00199 |
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author | Lu, Jie Mamun, Khondaker A. Chau, Tom |
author_facet | Lu, Jie Mamun, Khondaker A. Chau, Tom |
author_sort | Lu, Jie |
collection | PubMed |
description | Brain-computer interface (BCI) systems exploit brain activity for generating a control command and may be used by individuals with severe motor disabilities as an alternative means of communication. An emerging brain monitoring modality for BCI development is transcranial Doppler ultrasonography (TCD), which facilitates the tracking of cerebral blood flow velocities associated with mental tasks. However, TCD-BCI studies to date have exclusively been offline. The feasibility of a TCD-based BCI system hinges on its online performance. In this paper, an online TCD-BCI system was implemented, bilaterally tracking blood flow velocities in the middle cerebral arteries for system-paced control of a scanning keyboard. Target letters or words were selected by repetitively rehearsing the spelling while imagining the writing of the intended word, a left-lateralized task. Undesired letters or words were bypassed by performing visual tracking, a non-lateralized task. The keyboard scanning period was 15 s. With 10 able-bodied right-handed young adults, the two mental tasks were differentiated online using a Naïve Bayes classification algorithm and a set of time-domain, user-dependent features. The system achieved an average specificity and sensitivity of 81.44 ± 8.35 and 82.30 ± 7.39%, respectively. The level of agreement between the intended and machine-predicted selections was moderate (κ = 0.60). The average information transfer rate was 0.87 bits/min with an average throughput of 0.31 ± 0.12 character/min. These findings suggest that an online TCD-BCI can achieve reasonable accuracies with an intuitive language task, but with modest throughput. Future interface and signal classification enhancements are required to improve communication rate. |
format | Online Article Text |
id | pubmed-4001051 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-40010512014-05-02 Online transcranial Doppler ultrasonographic control of an onscreen keyboard Lu, Jie Mamun, Khondaker A. Chau, Tom Front Hum Neurosci Neuroscience Brain-computer interface (BCI) systems exploit brain activity for generating a control command and may be used by individuals with severe motor disabilities as an alternative means of communication. An emerging brain monitoring modality for BCI development is transcranial Doppler ultrasonography (TCD), which facilitates the tracking of cerebral blood flow velocities associated with mental tasks. However, TCD-BCI studies to date have exclusively been offline. The feasibility of a TCD-based BCI system hinges on its online performance. In this paper, an online TCD-BCI system was implemented, bilaterally tracking blood flow velocities in the middle cerebral arteries for system-paced control of a scanning keyboard. Target letters or words were selected by repetitively rehearsing the spelling while imagining the writing of the intended word, a left-lateralized task. Undesired letters or words were bypassed by performing visual tracking, a non-lateralized task. The keyboard scanning period was 15 s. With 10 able-bodied right-handed young adults, the two mental tasks were differentiated online using a Naïve Bayes classification algorithm and a set of time-domain, user-dependent features. The system achieved an average specificity and sensitivity of 81.44 ± 8.35 and 82.30 ± 7.39%, respectively. The level of agreement between the intended and machine-predicted selections was moderate (κ = 0.60). The average information transfer rate was 0.87 bits/min with an average throughput of 0.31 ± 0.12 character/min. These findings suggest that an online TCD-BCI can achieve reasonable accuracies with an intuitive language task, but with modest throughput. Future interface and signal classification enhancements are required to improve communication rate. Frontiers Media S.A. 2014-04-22 /pmc/articles/PMC4001051/ /pubmed/24795590 http://dx.doi.org/10.3389/fnhum.2014.00199 Text en Copyright © 2014 Lu, Mamun and Chau. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Lu, Jie Mamun, Khondaker A. Chau, Tom Online transcranial Doppler ultrasonographic control of an onscreen keyboard |
title | Online transcranial Doppler ultrasonographic control of an onscreen keyboard |
title_full | Online transcranial Doppler ultrasonographic control of an onscreen keyboard |
title_fullStr | Online transcranial Doppler ultrasonographic control of an onscreen keyboard |
title_full_unstemmed | Online transcranial Doppler ultrasonographic control of an onscreen keyboard |
title_short | Online transcranial Doppler ultrasonographic control of an onscreen keyboard |
title_sort | online transcranial doppler ultrasonographic control of an onscreen keyboard |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4001051/ https://www.ncbi.nlm.nih.gov/pubmed/24795590 http://dx.doi.org/10.3389/fnhum.2014.00199 |
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