Evidence map›Paper›PMID 33739290›Full record

ArticleJMIR research protocols2021

Remote and Long-Term Self-Monitoring of Electroencephalographic and Noninvasive Measurable Variables at Home in Patients With Epilepsy (EEG@HOME): Protocol for an Observational Study.

Andrea Biondi, Petroula Laiou, Elisa Bruno, Pedro F Viana, Martijn Schreuder, William Hart, Ewan Nurse, Deb K Pal, Mark P Richardson

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 28 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 3 countries.

Andrea BiondiInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-1072-665X
Petroula LaiouInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-5798-6961
Elisa BrunoInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-8166-1190
Pedro F VianaInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-0861-8705
Martijn SchreuderANT Neuro UK, Ltd, Stevenage, United Kingdom.ORCID https://orcid.org/0000-0002-7239-9909
William HartSeer Medical Inc, Melbourne, Australia.ORCID https://orcid.org/0000-0001-8134-1111
Ewan NurseSeer Medical Inc, Melbourne, Australia.ORCID https://orcid.org/0000-0001-8981-0074
Deb K PalInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-2655-0564
Mark P RichardsonInstitute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-8925-3140
King's College London · GBThe University of Melbourne · AUUniversity of Lisbon · PT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpileptic seizures are spontaneous events that severely affect the lives of patients due to their recurrence and unpredictability. The integration of new wearable and mobile technologies to collect electroencephalographic (EEG) and extracerebral signals in a portable system might be the solution to prospectively identify times of seizure occurrence or propensity. The performances of several seizure detection devices have been assessed by validated studies, and patient perspectives on wearables have been explored to better match their needs. Despite this, there is a major gap in the literature on long-term, real-life acceptability and performance of mobile technology essential to managing chronic disorders such as epilepsy.

objectiveEEG@HOME is an observational, nonrandomized, noninterventional study that aims to develop a new feasible procedure that allows people with epilepsy to independently, continuously, and safely acquire noninvasive variables at home. The data collected will be analyzed to develop a general model to predict periods of increased seizure risk.

methodsA total of 12 adults with a diagnosis of pharmaco-resistant epilepsy and at least 20 seizures per year will be recruited at King's College Hospital, London. Participants will be asked to self-apply an easy and portable EEG recording system (ANT Neuro) to record scalp EEG at home twice daily. From each serial EEG recording, brain network ictogenicity (BNI), a new biomarker of the propensity of the brain to develop seizures, will be extracted. A noninvasive wrist-worn device (Fitbit Charge 3; Fitbit Inc) will be used to collect non-EEG biosignals (heart rate, sleep quality index, and steps), and a smartphone app (Seer app; Seer Medical) will be used to collect data related to seizure occurrence, medication taken, sleep quality, stress, and mood. All data will be collected continuously for 6 months. Standardized questionnaires (the Post-Study System Usability Questionnaire and System Usability Scale) will be completed to assess the acceptability and feasibility of the procedure. BNI, continuous wrist-worn sensor biosignals, and electronic survey data will be correlated with seizure occurrence as reported in the diary to investigate their potential values as biomarkers of seizure risk.

resultsThe EEG@HOME project received funding from Epilepsy Research UK in 2018 and was approved by the Bromley Research Ethics Committee in March 2020. The first participants were enrolled in October 2020, and we expect to publish the first results by the end of 2022.

conclusionsWith the EEG@HOME study, we aim to take advantage of new advances in remote monitoring technology, including self-applied EEG, to investigate the feasibility of long-term disease self-monitoring. Further, we hope our study will bring new insights into noninvasively collected personalized risk factors of seizure occurrence and seizure propensity that may help to mitigate one of the most difficult aspects of refractory epilepsy: the unpredictability of seizure occurrence. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25309.

Indexed as

brainbrain ictogenicityEEGelectroencephalographyepilepsymobile technologyseizure predictionseizureswearables

Identifiers

PMID33739290
PMCPMC8088854
OpenAlexW3116974111

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.