Key result
Dry electrodes underperform wet electrodes in P300 spellers despite dynamic algorithms partially offsetting lower SNR.
Why the study?
Dry electrodes provide quicker EEG set-up but may produce noisier recordings, impacting brain-computer interface communication and requiring mitigation strategies.
Does a dynamic data collection algorithm improve the performance of dry electrodes compared to wet electrodes in a P300-based brain-computer interface?
Does a dynamic data collection algorithm improve the performance of dry electrodes compared to wet electrodes in a P300-based brain-computer interface?
While dry electrodes offer quicker set-up for EEG-based brain-computer interfaces, their performance remains inferior to wet electrodes even when using dynamic stopping algorithms to compensate for lower signal-to-noise ratios.
Dry electrodes reduce P300 speller accuracy versus wet; leaves open whether dynamic collection or other mitigations can achieve reliable clinical BCI use.
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.
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Clements et al. (2016) studied Communication disabilities (ALS and PLS) and healthy (n=24). Dry electrodes with dynamic data collection algorithm vs. Wet electrodes with standard static data collection was evaluated on Performance accuracy and signal-to-noise ratio. Dry electrodes demonstrated significantly poorer online performance than wet electrodes for a P300 speller system, and a dynamic stopping algorithm only partially compensated for the lower SNR.
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