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Utilizing a language model to improve online dynamic data collection in P300 spellers.

Publication ,  Journal Article
Mainsah, BO; Colwell, KA; Collins, LM; Throckmorton, CS
Published in: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
July 2014

P300 spellers provide a means of communication for individuals with severe physical limitations, especially those with locked-in syndrome, such as amyotrophic lateral sclerosis. However, P300 speller use is still limited by relatively low communication rates due to the multiple data measurements that are required to improve the signal-to-noise ratio of event-related potentials for increased accuracy. Therefore, the amount of data collection has competing effects on accuracy and spelling speed. Adaptively varying the amount of data collection prior to character selection has been shown to improve spelling accuracy and speed. The goal of this study was to optimize a previously developed dynamic stopping algorithm that uses a Bayesian approach to control data collection by incorporating a priori knowledge via a language model. Participants ( n = 17) completed online spelling tasks using the dynamic stopping algorithm, with and without a language model. The addition of the language model resulted in improved participant performance from a mean theoretical bit rate of 46.12 bits/min at 88.89% accuracy to 54.42 bits/min ( ) at 90.36% accuracy.

Duke Scholars

Published In

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society

DOI

EISSN

1558-0210

ISSN

1534-4320

Publication Date

July 2014

Volume

22

Issue

4

Start / End Page

837 / 846

Related Subject Headings

  • Young Adult
  • Writing
  • Word Processing
  • Task Performance and Analysis
  • Online Systems
  • Natural Language Processing
  • Models, Theoretical
  • Male
  • Language
  • Humans
 

Citation

APA
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ICMJE
MLA
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Mainsah, B. O., Colwell, K. A., Collins, L. M., & Throckmorton, C. S. (2014). Utilizing a language model to improve online dynamic data collection in P300 spellers. IEEE Transactions on Neural Systems and Rehabilitation Engineering : A Publication of the IEEE Engineering in Medicine and Biology Society, 22(4), 837–846. https://doi.org/10.1109/tnsre.2014.2321290
Mainsah, Boyla O., Kenneth A. Colwell, Leslie M. Collins, and Chandra S. Throckmorton. “Utilizing a language model to improve online dynamic data collection in P300 spellers.IEEE Transactions on Neural Systems and Rehabilitation Engineering : A Publication of the IEEE Engineering in Medicine and Biology Society 22, no. 4 (July 2014): 837–46. https://doi.org/10.1109/tnsre.2014.2321290.
Mainsah BO, Colwell KA, Collins LM, Throckmorton CS. Utilizing a language model to improve online dynamic data collection in P300 spellers. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 2014 Jul;22(4):837–46.
Mainsah, Boyla O., et al. “Utilizing a language model to improve online dynamic data collection in P300 spellers.IEEE Transactions on Neural Systems and Rehabilitation Engineering : A Publication of the IEEE Engineering in Medicine and Biology Society, vol. 22, no. 4, July 2014, pp. 837–46. Epmc, doi:10.1109/tnsre.2014.2321290.
Mainsah BO, Colwell KA, Collins LM, Throckmorton CS. Utilizing a language model to improve online dynamic data collection in P300 spellers. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society. 2014 Jul;22(4):837–846.

Published In

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society

DOI

EISSN

1558-0210

ISSN

1534-4320

Publication Date

July 2014

Volume

22

Issue

4

Start / End Page

837 / 846

Related Subject Headings

  • Young Adult
  • Writing
  • Word Processing
  • Task Performance and Analysis
  • Online Systems
  • Natural Language Processing
  • Models, Theoretical
  • Male
  • Language
  • Humans