Literature DB >> 31645318

Can commercially available wearable EEG devices be used for diagnostic purposes? An explorative pilot study.

Yannic Titgemeyer1, Rainer Surges2, Dirk-Matthias Altenmüller3, Susanne Fauser4, Albrecht Kunze5, Michael Lanz6, Michael P Malter7, Robert Daniel Nass2, Felix von Podewils8, Jan Remi9, Sarah von Spiczak10, Adam Strzelczyk11, Roann Munoz Ramos12, Ekaterina Kutafina13, Stephan Michael Jonas14.   

Abstract

Electroencephalography (EEG) is a core element in the diagnosis of epilepsy syndromes and can help to monitor antiseizure treatment. Mobile EEG (mEEG) devices are increasingly available on the consumer market and may offer easier access to EEG recordings especially in rural or resource-poor areas. The usefulness of consumer-grade devices for clinical purposes is still underinvestigated. Here, we compared EEG traces of a commercially available mEEG device (Emotiv EPOC) to a simultaneously recorded clinical video EEG (vEEG). Twenty-two adult patients (11 female, mean age 40.2 years) undergoing noninvasive vEEG monitoring for clinical purposes were prospectively enrolled. The EEG recordings were evaluated by 10 independent raters with unmodifiable view settings. The individual evaluations were compared with respect to the presence of abnormal EEG findings (regional slowing, epileptiform potentials, seizure pattern). Video EEG yielded a sensitivity of 56% and specificity of 88% for abnormal EEG findings, whereas mEEG reached 39% and 85%, respectively. Interrater reliability coefficients were better in vEEG as compared to mEEG (ϰ = 0.50 vs. 0.30), corresponding to a moderate and fair agreement. Intrarater reliability between mEEG and vEEG evaluations of simultaneous recordings of a given participant was moderate (ϰ = 0.48). Given the limitations of our exploratory pilot study, our results suggest that vEEG is superior to mEEG, but that mEEG can be helpful for diagnostic purposes. We present the first quantitative comparison of simultaneously acquired clinical and mobile consumer-grade EEG for a clinical use-case.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Brain-computer interfaces; Electroencephalography; Epilepsy; Mobile EEG; Mobile health; Wearable sensors

Year:  2019        PMID: 31645318     DOI: 10.1016/j.yebeh.2019.106507

Source DB:  PubMed          Journal:  Epilepsy Behav        ISSN: 1525-5050            Impact factor:   2.937


  7 in total

1.  Exploring EEG spectral and temporal dynamics underlying a hand grasp movement.

Authors:  Sandeep Bodda; Shyam Diwakar
Journal:  PLoS One       Date:  2022-06-23       Impact factor: 3.752

2.  Research on Night Light Comfort of Pedestrian Space in Urban Park.

Authors:  Jun Zhang; Wenhan Dai
Journal:  Comput Math Methods Med       Date:  2021-12-21       Impact factor: 2.238

Review 3.  Remote Patient Monitoring for Neuropsychiatric Disorders: A Scoping Review of Current Trends and Future Perspectives from Recent Publications and Upcoming Clinical Trials.

Authors:  Tetsuo Sakamaki; Yoshihiko Furusawa; Ayako Hayashi; Masaru Otsuka; Jovelle Fernandez
Journal:  Telemed J E Health       Date:  2022-01-24       Impact factor: 5.033

4.  Tablet-based electroencephalography diagnostics for patients with epilepsy in the West African Republic of Guinea.

Authors:  E Sokolov; D H Abdoul Bachir; F Sakadi; J Williams; A C Vogel; M Schaekermann; N Tassiou; A K Bah; V Khatri; G C Hotan; N Ayub; E Leung; T A Fantaneanu; A Patel; M Vyas; T Milligan; M F Villamar; D Hoch; S Purves; B Esmaeili; M Stanley; T Lehn-Schioler; J Tellez-Zenteno; E Gonzalez-Giraldo; I Tolokh; L Heidarian; L Worden; N Jadeja; S Fridinger; L Lee; E Law; C Fodé Abass; F J Mateen
Journal:  Eur J Neurol       Date:  2020-05-30       Impact factor: 6.089

Review 5.  Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces.

Authors:  Roberto Portillo-Lara; Bogachan Tahirbegi; Christopher A R Chapman; Josef A Goding; Rylie A Green
Journal:  APL Bioeng       Date:  2021-07-20

6.  Predicting stroke severity with a 3-min recording from the Muse portable EEG system for rapid diagnosis of stroke.

Authors:  Cassandra M Wilkinson; Jennifer I Burrell; Jonathan W P Kuziek; Sibi Thirunavukkarasu; Brian H Buck; Kyle E Mathewson
Journal:  Sci Rep       Date:  2020-10-28       Impact factor: 4.379

Review 7.  Noninvasive mobile EEG as a tool for seizure monitoring and management: A systematic review.

Authors:  Andrea Biondi; Viviana Santoro; Pedro F Viana; Petroula Laiou; Deb K Pal; Elisa Bruno; Mark P Richardson
Journal:  Epilepsia       Date:  2022-03-27       Impact factor: 6.740

  7 in total

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