Evidence map›Paper›PMID 41701004›Full record

ArticleEpilepsia open2026

Out of the lab, into real life: Evaluating at-home EEG self-monitoring.

Louis Cousyn, Andrea Biondi, Joel S Winston, Matthew McWilliam, Pedro F Viana, Martijn Schreuder, Petroula Laiou, Mark P Richardson

Abstract readEvaluation Study
In one paragraph

Article in Epilepsia open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Louis CousynDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0000-0003-1407-5575
Andrea BiondiDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0000-0003-1072-665X
Joel S WinstonDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0000-0002-3957-0612
Matthew McWilliamDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0009-0009-4325-3941
Pedro F VianaDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0000-0003-0861-8705
Martijn SchreuderANT Neuro GmbH & ANT Neuro UK Ltd, Hengelo, the Netherlands.ORCID https://orcid.org/0000-0002-7239-9909
Petroula LaiouDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0000-0002-5798-6961
Mark P RichardsonDepartment of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), King's College London, London, UK.ORCID https://orcid.org/0000-0001-8925-3140

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Seizure forecasting models require long-term, high-quality data collected in real-life settings using noninvasive or minimally invasive devices, yet, the lack of such systems remains a major barrier to their clinical translation. Here, we aimed to evaluate the signal quality of self-applied at-home EEG monitoring using a wearable system in patients with epilepsy to assess its reliability for future seizure forecasting applications. All EEG recordings were reviewed to identify non-usable data and interictal epileptiform discharges (IEDs). We analyzed power spectral density and the temporal evolution of a signal-to-noise ratio, and applied composite quality criteria for each patient based on spectral profile and the proportion of EEG data discarded. Twelve patients with drug-resistant epilepsy performed self-applied resting-state EEG recordings twice daily over a median period of 173.5 days (min. 12, max. 235). Two-thirds of patients had data of good or moderate quality (N = 3 and 5, respectively), which remained overall stable over time with cap replacement every 2-3 months. IEDs were found in four patients and were concordant with prior in-hospital recordings. Self-applied at-home EEG monitoring can yield clinically relevant insights and may support future seizure forecasting strategies in selected patients, provided patient adherence and the feasibility of regular maintenance follow-up are addressed. PLAIN LANGUAGE SUMMARY: Twelve people whose epilepsy was hard to control with medication recorded a short brain-wave test (electroencephalography, or EEG) at home twice a day for several months. In 8 of the 12 people, most recordings were clear enough to use and stayed steady over time, although some EEG caps needed replacement. In four people, the home EEG showed abnormal spikes between seizures that matched earlier hospital EEGs. This suggests that long-term, self-recorded EEG at home is possible for some patients and may help clinicians track brain activity outside the hospital.

Indexed as

Drug Resistant EpilepsyElectroencephalographyMonitoring, AmbulatoryNeurophysiological MonitoringSeizuresWearable Electronic DevicesAdultClinical RelevanceData AccuracyFemaleForecastingHumansMaleMiddle AgedReproducibility of ResultsRestambulatoryEEG monitoringin‐homeremoteself‐applied

Identifiers

PMID41701004
PMCPMC13052238

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.