Validation of a smartphone-based EEG among people with epilepsy: A prospective study

Publication: Research - peer-reviewJournal article – Annual report year: 2017

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DOI

  • Author: Mckenzie, Erica D.

    Massachusetts General Hospital, United States

  • Author: Lim, Andrew S P

    University of Toronto, Canada

  • Author: Leung, Edward C W

    University of Manitoba, Canada

  • Author: Cole, Andrew J.

    Massachusetts General Hospital, United States

  • Author: Lam, Alice D.

    Massachusetts General Hospital, United States

  • Author: Eloyan, Ani

    Brown University, United States

  • Author: Nirola, Damber K.

    Jigme Dorji Wangchuck National Referral Hospital, Bhutan

  • Author: Tshering, Lhab

    Jigme Dorji Wangchuck National Referral Hospital, Bhutan

  • Author: Thibert, Ronald

    Massachusetts General Hospital, United States

  • Author: Garcia, Rodrigo Zepeda

    Massachusetts General Hospital, United States

  • Author: Bui, Esther

    University of Toronto, Canada

  • Author: Deki, Sonam

    Jigme Dorji Wangchuck National Referral Hospital, Bhutan

  • Author: Lee, Liesly

    University of Toronto, Canada

  • Author: Clark, Sarah J.

    Massachusetts General Hospital, United States

  • Author: Cohen, Joseph M.

    Massachusetts General Hospital, United States

  • Author: Mantia, Jo

    University of Toronto, Canada

  • Author: Brizzi, Kate T.

    Massachusetts General Hospital, United States

  • Author: Sorets, Tali R.

    Massachusetts General Hospital, United States

  • Author: Wahlster, Sarah

    University of Washington, United States

  • Author: Borzello, Mia

    Massachusetts General Hospital, United States

  • Author: Stopczynski, Arkadiusz

    Department of Applied Mathematics and Computer Science , Technical University of Denmark, Richard Petersens Plads, 2800, Kgs. Lyngby, Denmark

  • Author: Cash, Sydney S.

    Massachusetts General Hospital, United States

  • Author: Mateen, Farrah J.

    Massachusetts General Hospital, United States

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Our objective was to assess the ability of a smartphone-based electroencephalography (EEG) application, the Smartphone Brain Scanner-2 (SBS2), to detect epileptiform abnormalities compared to standard clinical EEG. The SBS2 system consists of an Android tablet wirelessly connected to a 14-electrode EasyCap headset (cost ∼ 300 USD). SBS2 and standard EEG were performed in people with suspected epilepsy in Bhutan (2014-2015), and recordings were interpreted by neurologists. Among 205 participants (54% female, median age 24 years), epileptiform discharges were detected on 14% of SBS2 and 25% of standard EEGs. The SBS2 had 39.2% sensitivity (95% confidence interval (CI) 25.8%, 53.9%) and 94.8% specificity (95% CI 90.0%, 97.7%) for epileptiform discharges with positive and negative predictive values of 0.71 (95% CI 0.51, 0.87) and 0.82 (95% CI 0.76, 0.89) respectively. 31% of focal and 82% of generalized abnormalities were identified on SBS2 recordings. Cohen's kappa (κ) for the SBS2 EEG and standard EEG for the epileptiform versus non-epileptiform outcome was κ = 0.40 (95% CI 0.25, 0.55). No safety or tolerability concerns were reported. Despite limitations in sensitivity, the SBS2 may become a viable supportive test for the capture of epileptiform abnormalities, and extend EEG access to new, especially resource-limited, populations at a reduced cost.
Original languageEnglish
Article number45567
JournalScientific Reports
Volume7
Number of pages8
ISSN2045-2322
DOIs
StatePublished - 2017
CitationsWeb of Science® Times Cited: No match on DOI

    Keywords

  • Multidisciplinary
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