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

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 so...

Full description

Bibliographic Details
Main Authors: Biondi, Andrea, Laiou, Petroula, Bruno, Elisa, Viana, Pedro F, Schreuder, Martijn, Hart, William, Nurse, Ewan, Pal, Deb K, Richardson, Mark P
Format: Article
Language:English
Published: JMIR Publications 2021-03-01
Series:JMIR Research Protocols
Online Access:https://www.researchprotocols.org/2021/3/e25309
_version_ 1818883302610698240
author Biondi, Andrea
Laiou, Petroula
Bruno, Elisa
Viana, Pedro F
Schreuder, Martijn
Hart, William
Nurse, Ewan
Pal, Deb K
Richardson, Mark P
author_facet Biondi, Andrea
Laiou, Petroula
Bruno, Elisa
Viana, Pedro F
Schreuder, Martijn
Hart, William
Nurse, Ewan
Pal, Deb K
Richardson, Mark P
author_sort Biondi, Andrea
collection DOAJ
description 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
first_indexed 2024-12-19T15:31:30Z
format Article
id doaj.art-d52882b4a87e43739bc69d9b8826dec5
institution Directory Open Access Journal
issn 1929-0748
language English
last_indexed 2024-12-19T15:31:30Z
publishDate 2021-03-01
publisher JMIR Publications
record_format Article
series JMIR Research Protocols
spelling doaj.art-d52882b4a87e43739bc69d9b8826dec52022-12-21T20:15:43ZengJMIR PublicationsJMIR Research Protocols1929-07482021-03-01103e2530910.2196/25309Remote and Long-Term Self-Monitoring of Electroencephalographic and Noninvasive Measurable Variables at Home in Patients With Epilepsy (EEG@HOME): Protocol for an Observational StudyBiondi, AndreaLaiou, PetroulaBruno, ElisaViana, Pedro FSchreuder, MartijnHart, WilliamNurse, EwanPal, Deb KRichardson, Mark PBackgroundEpileptic 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)PRR1-10.2196/25309https://www.researchprotocols.org/2021/3/e25309
spellingShingle Biondi, Andrea
Laiou, Petroula
Bruno, Elisa
Viana, Pedro F
Schreuder, Martijn
Hart, William
Nurse, Ewan
Pal, Deb K
Richardson, Mark P
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
JMIR Research Protocols
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
url https://www.researchprotocols.org/2021/3/e25309
work_keys_str_mv AT biondiandrea remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT laioupetroula remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT brunoelisa remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT vianapedrof remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT schreudermartijn remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT hartwilliam remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT nurseewan remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT paldebk remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy
AT richardsonmarkp remoteandlongtermselfmonitoringofelectroencephalographicandnoninvasivemeasurablevariablesathomeinpatientswithepilepsyeeghomeprotocolforanobservationalstudy