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

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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.

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