Advanced Intelligent Systems (Aug 2023)

Flexible Silver/Carbon Nanotube‐Graphene Oxide‐Polydimethylsiloxane Electrode Patch for Electroencephalography Language

  • Penghai Li,
  • Chen Wang,
  • Mingji Li,
  • Xiuwei Xuan,
  • Baozeng Zhou,
  • Hongji Li

DOI
https://doi.org/10.1002/aisy.202300018
Journal volume & issue
Vol. 5, no. 8
pp. n/a – n/a

Abstract

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A flexible silver/carbon nanotube‐graphene oxide‐polydimethylsiloxane (Ag/CNT‐GO‐PDMS) patch electrode for recording electroencephalography (EEG) signals and recognizing words is prepared. These patches record EEG signals under the synergistic sensing mechanism of the noncontact capacitance mode of the CNT‐GO‐PDMS patch and contact current mode of the Ag claws, with low scalp contact resistance of 6.4 kΩ. In the occipital region, the signal‐to‐noise ratios (SNR) are ≈90 dB for α‐waves and 9 dB for visual‐evoked signals; the SNR of auditory‐evoked EEG signals in the temporal region is ≈10 dB. The EEG cap comprises seven Ag/CNT‐GO‐PDMS patches to record EEG signals in steady‐state visual‐evoked potentials (SSVEP) and multiple auditory steady‐state response (MASSR). These patches can recognize nine words (“one” to “nine”) in the SSVEP–MASSR paradigm, with a visual accuracy of 90.4% and auditory accuracy of 54.0%. The statistical analysis also shows that the stimulation frequency and scalp channel are significant influencing factors for the accuracy of word recognition. We developed a standardized process of flexible Ag/CNT‐GO‐PDMS patches and herein propose a new strategy to identify words, which is of great significance for the establishment of the EEG language database and the application of EEG in the field of information transmission.

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