Neuroscience from the comfort of your home: Repeated, self-administered wireless dry EEG measures brain function with high fidelity

Florentine M. Barbey, Francesca R. Farina, Alison R. Buick, Lena Danyeli, John F. Dyer, Md Nurul Islam, Marina Krylova, Brian Murphy, Hugh Nolan, Laura M. Rueda-Delgado, Martin Walter, Robert Whelan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Recent advances have enabled the creation of wireless, “dry” electroencephalography (EEG) recording systems, and easy-to-use engaging tasks, that can be operated repeatedly by naïve users, unsupervised in the home. Here, we evaluated the validity of dry-EEG, cognitive task gamification, and unsupervised home-based recordings used in combination. Two separate cohorts of participants—older and younger adults—collected data at home over several weeks using a wireless dry EEG system interfaced with a tablet for task presentation. Older adults (n = 50; 25 females; mean age = 67.8 years) collected data over a 6-week period. Younger male adults (n = 30; mean age = 25.6 years) collected data over a 4-week period. All participants were asked to complete gamified versions of a visual Oddball task and Flanker task 5–7 days per week. Usability of the EEG system was evaluated via participant adherence, percentage of sessions successfully completed, and quantitative feedback using the System Usability Scale. In total, 1,449 EEG sessions from older adults (mean = 28.9; SD = 6.64) and 684 sessions from younger adults (mean = 22.87; SD = 1.92) were collected. Older adults successfully completed 93% of sessions requested and reported a mean usability score of 84.5. Younger adults successfully completed 96% of sessions and reported a mean usability score of 88.3. Characteristic event-related potential (ERP) components—the P300 and error-related negativity—were observed in the Oddball and Flanker tasks, respectively. Using a conservative threshold for inclusion of artifact-free data, 50% of trials were rejected per at-home session. Aggregation of ERPs across sessions (2–4, depending on task) resulted in grand average signal quality with similar Standard Measurement Error values to those of single-session wet EEG data collected by experts in a laboratory setting from a young adult sample. Our results indicate that easy-to-use task-driven EEG can enable large-scale investigations in cognitive neuroscience. In future, this approach may be useful in clinical applications such as screening and tracking of treatment response.

Original languageEnglish (US)
Article number944753
JournalFrontiers in Digital Health
Volume4
DOIs
StatePublished - Jul 29 2022

Funding

The studies on which this paper is based were funded by the Irish Research Council (IRC), Science Foundation Ireland and Cumulus Neuroscience Ltd. FB was supported by the IRC Employment Based Postgraduate Programme (EBPPG/2019/53), FF by the IRC Enterprise Partnership Postdoctoral Scheme (EPSPD/2017/110). LR-D was supported by the Science Foundation Ireland (18/IF/6272). LD was funded by the Leibniz Institute for Neurobiology in Magdeburg, Germany (SFB779). MK was supported by the Jena University Hospital. FB and FF received funding from Cumulus Neuroscience Ltd., in partnership the Irish Research Council, through the IRC Employment Based Postgraduate Programme (EBPPG/2019/53), and the IRC Enterprise Partnership Postdoctoral Scheme (EPSPD/2017/110), respectively, with RW as the mentor on both these projects.

Keywords

  • Standard Measurement Error
  • cognition
  • dry electroencephalography
  • electroencephalography
  • gamification
  • humans
  • longitudinal
  • signal quality

ASJC Scopus subject areas

  • Health Informatics
  • Biomedical Engineering
  • Medicine (miscellaneous)
  • Computer Science Applications

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