Literature DB >> 24060755

Mobile EEG in epilepsy.

Jessica Askamp1, Michel J A M van Putten2.   

Abstract

The sensitivity of routine EEG recordings for interictal epileptiform discharges in epilepsy is limited. In some patients, inpatient video-EEG may be performed to increase the likelihood of finding abnormalities. Although many agree that home EEG recordings may provide a cost-effective alternative to these recordings, their use is still not introduced everywhere. We surveyed Dutch neurologists and patients and evaluated a novel mobile EEG device (Mobita, TMSi). Key specifications were compared with three other current mobile EEG devices. We shortly discuss algorithms to assist in the review process. Thirty percent (33 out of 109) of Dutch neurologists reported that home EEG recordings are used in their hospital. The majority of neurologists think that mobile EEG can have additional value in investigation of unclear paroxysms, but not in the initial diagnosis after a first seizure. Poor electrode contacts and signal quality, limited recording time and absence of software for reliable and effective assistance in the interpretation of EEGs have been important constraints for usage, but in recent devices discussed here, many of these problems have been solved. The majority of our patients were satisfied with the home EEG procedure and did not think that our EEG device was uncomfortable to wear, but they did feel uneasy wearing it in public.
© 2013.

Entities:  

Keywords:  Computer assisted reviewing; EEG devices; Epilepsy; Home EEG; Mobile EEG; Neurologists' opinions; Patient satisfaction

Mesh:

Year:  2013        PMID: 24060755     DOI: 10.1016/j.ijpsycho.2013.09.002

Source DB:  PubMed          Journal:  Int J Psychophysiol        ISSN: 0167-8760            Impact factor:   2.997


  14 in total

1.  Feasibility of assessing brain activity using mobile, in-home collection of electroencephalography: methods and analysis.

Authors:  Sonya V Troller-Renfree; Santiago Morales; Stephanie C Leach; Maureen E Bowers; Ranjan Debnath; William P Fifer; Nathan A Fox; Kimberly G Noble
Journal:  Dev Psychobiol       Date:  2021-06-04       Impact factor: 2.531

2.  Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy.

Authors:  Ying Gu; Evy Cleeren; Jonathan Dan; Kasper Claes; Wim Van Paesschen; Sabine Van Huffel; Borbála Hunyadi
Journal:  Sensors (Basel)       Date:  2017-12-23       Impact factor: 3.576

Review 3.  Understanding Minds in Real-World Environments: Toward a Mobile Cognition Approach.

Authors:  Simon Ladouce; David I Donaldson; Paul A Dudchenko; Magdalena Ietswaart
Journal:  Front Hum Neurosci       Date:  2017-01-12       Impact factor: 3.169

4.  A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings.

Authors:  Gabriella Tamburro; Patrique Fiedler; David Stone; Jens Haueisen; Silvia Comani
Journal:  PeerJ       Date:  2018-02-23       Impact factor: 2.984

5.  Development of a Modular Board for EEG Signal Acquisition.

Authors:  Tomas Uktveris; Vacius Jusas
Journal:  Sensors (Basel)       Date:  2018-07-03       Impact factor: 3.576

Review 6.  Mobile EEG in research on neurodevelopmental disorders: Opportunities and challenges.

Authors:  Alex Lau-Zhu; Michael P H Lau; Gráinne McLoughlin
Journal:  Dev Cogn Neurosci       Date:  2019-03-08       Impact factor: 6.464

7.  Comparison between a wireless dry electrode EEG system with a conventional wired wet electrode EEG system for clinical applications.

Authors:  Hermann Hinrichs; Michael Scholz; Anne Katrin Baum; Julia W Y Kam; Robert T Knight; Hans-Jochen Heinze
Journal:  Sci Rep       Date:  2020-03-23       Impact factor: 4.379

8.  Is Brain Dynamics Preserved in the EEG After Automated Artifact Removal? A Validation of the Fingerprint Method and the Automatic Removal of Cardiac Interference Approach Based on Microstate Analysis.

Authors:  Gabriella Tamburro; Pierpaolo Croce; Filippo Zappasodi; Silvia Comani
Journal:  Front Neurosci       Date:  2021-01-12       Impact factor: 4.677

Review 9.  Categorisation of Mobile EEG: A Researcher's Perspective.

Authors:  Anthony D Bateson; Heidi A Baseler; Kevin S Paulson; Fayyaz Ahmed; Aziz U R Asghar
Journal:  Biomed Res Int       Date:  2017-12-04       Impact factor: 3.411

10.  Overlaps and distinctions between attention deficit/hyperactivity disorder and autism spectrum disorder in young adulthood: Systematic review and guiding framework for EEG-imaging research.

Authors:  Alex Lau-Zhu; Anne Fritz; Gráinne McLoughlin
Journal:  Neurosci Biobehav Rev       Date:  2018-10-24       Impact factor: 8.989

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