Skip to main content
Journal cover image

Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface.

Publication ,  Journal Article
Clements, JM; Sellers, EW; Ryan, DB; Caves, K; Collins, LM; Throckmorton, CS
Published in: J Neural Eng
December 2016

OBJECTIVE: Dry electrodes have an advantage over gel-based 'wet' electrodes by providing quicker set-up time for electroencephalography recording; however, the potentially poorer contact can result in noisier recordings. We examine the impact that this may have on brain-computer interface communication and potential approaches for mitigation. APPROACH: We present a performance comparison of wet and dry electrodes for use with the P300 speller system in both healthy participants and participants with communication disabilities (ALS and PLS), and investigate the potential for a data-driven dynamic data collection algorithm to compensate for the lower signal-to-noise ratio (SNR) in dry systems. MAIN RESULTS: Performance results from sixteen healthy participants obtained in the standard static data collection environment demonstrate a substantial loss in accuracy with the dry system. Using a dynamic stopping algorithm, performance may have been improved by collecting more data in the dry system for ten healthy participants and eight participants with communication disabilities; however, the algorithm did not fully compensate for the lower SNR of the dry system. An analysis of the wet and dry system recordings revealed that delta and theta frequency band power (0.1-4 Hz and 4-8 Hz, respectively) are consistently higher in dry system recordings across participants, indicating that transient and drift artifacts may be an issue for dry systems. SIGNIFICANCE: Using dry electrodes is desirable for reduced set-up time; however, this study demonstrates that online performance is significantly poorer than for wet electrodes for users with and without disabilities. We test a new application of dynamic stopping algorithms to compensate for poorer SNR. Dynamic stopping improved dry system performance; however, further signal processing efforts are likely necessary for full mitigation.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

J Neural Eng

DOI

EISSN

1741-2552

Publication Date

December 2016

Volume

13

Issue

6

Start / End Page

066018

Location

England

Related Subject Headings

  • Signal-To-Noise Ratio
  • Male
  • Humans
  • Healthy Volunteers
  • Female
  • Event-Related Potentials, P300
  • Electroencephalography
  • Electrodes
  • Data Collection
  • Communication Disorders
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Clements, J. M., Sellers, E. W., Ryan, D. B., Caves, K., Collins, L. M., & Throckmorton, C. S. (2016). Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface. J Neural Eng, 13(6), 066018. https://doi.org/10.1088/1741-2560/13/6/066018
Clements, J. M., E. W. Sellers, D. B. Ryan, K. Caves, L. M. Collins, and C. S. Throckmorton. “Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface.J Neural Eng 13, no. 6 (December 2016): 066018. https://doi.org/10.1088/1741-2560/13/6/066018.
Clements JM, Sellers EW, Ryan DB, Caves K, Collins LM, Throckmorton CS. Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface. J Neural Eng. 2016 Dec;13(6):066018.
Clements, J. M., et al. “Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface.J Neural Eng, vol. 13, no. 6, Dec. 2016, p. 066018. Pubmed, doi:10.1088/1741-2560/13/6/066018.
Clements JM, Sellers EW, Ryan DB, Caves K, Collins LM, Throckmorton CS. Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface. J Neural Eng. 2016 Dec;13(6):066018.
Journal cover image

Published In

J Neural Eng

DOI

EISSN

1741-2552

Publication Date

December 2016

Volume

13

Issue

6

Start / End Page

066018

Location

England

Related Subject Headings

  • Signal-To-Noise Ratio
  • Male
  • Humans
  • Healthy Volunteers
  • Female
  • Event-Related Potentials, P300
  • Electroencephalography
  • Electrodes
  • Data Collection
  • Communication Disorders