JMIR Publications

ABSTRACT

Background:

Epileptic seizures are spontaneous events that severely affect the lives of patients due to their recurrence and unpredictability. The integration of new wearable and mobile technology to collect EEG and extra-cerebral signals into a portable system might be the solution to prospectively identify times of seizure occurrence or propensity. The performance of several seizure detection devices has 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 patient acceptability and performance of mobile technology, essential to manage chronic disorders such as epilepsy.

Objective:

EEG@HOME is an observational non-randomised and non-interventional study with the aim to develop a new feasible procedure that allows people with epilepsy to independently, continuously and safety acquire non-invasive variables at home. The data collected will be then analysed to develop a general model to predict periods of increased seizure risk.

Methods:

Twelve adult people with a diagnosis of pharmaco-resistant epilepsy and with 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 non-invasive wrist worn device (FitBit Charge3) will be used to collect non-EEG bio-signals (heart rate, sleep quality index and steps) and a smartphone app (Seer App) will be utilized to collect data related to seizure occurrence, medication taken, sleep quality, stress and mood. All the data will be collected continuously for 6 months. Standardized questionnaires (SSPQ & SUS) will be completed to assess the acceptability and feasibility of the procedure. BNI, continuous wristworn sensor biosignals and electronic survey data will be correlated with seizure occurrence as reported in the diary, to investigate their potential value as biomarkers of seizure risk.

Results:

The EEG@HOME project received funding from Epilepsy Research UK in 2018 and and was approved by the Bromley Research Ethics Committee (REC reference: 19/LO/0554) in March 2020. The first participant will be enrolled from October 2020 and we expect to publish the first results by the end of 2022.

Conclusions:

With 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 non-invasively collected personalized risk factors of seizure occurrence and seizure propensity, that may help to mitigate one of the most disabling aspects in refractory epilepsy – unpredictability of seizure occurrence.