Abstract
BackgroundIn recent years, a growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. In clinical practice, seizure assessment typically relies on self-report, which is known to be highly unreliable. Moreover, most people with epilepsy self-identify factors that lead to increased seizure likelihood, including mood, behavior, sleep pattern, and cognitive alterations, all of which are amenable to measurement via multiparametric RMT.ObjectiveThe primary aim of this multicenter prospective cohort study is to assess the usability, feasibility, and acceptability of RMT in the community setting. In addition, this study aims to determine whether multiparametric RMT collected in populations with epilepsy can prospectively estimate variations in seizure occurrence and other outcomes, including seizure frequency, quality of life, and comorbidities.MethodsPeople with a diagnosis of pharmacoresistant epilepsy will be recruited in London, United Kingdom, and Freiburg, Germany. Participants will be asked to wear a wrist-worn device and download ad hoc apps developed on their smartphones. The apps will be used to collect data related to sleep, physical activity, stress, mood, social interaction, speech patterns, and cognitive function, both passively from existing smartphone sensors (passive remote measurement technology [pRMT]) and actively via questionnaires, tasks, and assessments (active remote measurement technology [aRMT]). Data will be collected continuously for 6 months and streamed to the Remote Assessment of Disease and Relapse-base (RADAR-base) server.ResultsThe RADAR Central Nervous System project received funding in 2015 from the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No. 115902. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and European Federation of Pharmaceutical Industries and Associations. Ethical approval was obtained in London from the Bromley Research Ethics Committee (research ethics committee reference: 19/LO/1884) in January 2020. The first participant was enrolled on September 30, 2020. Data will be collected until September 30, 2021. The results are expected to be published at the beginning of 2022.ConclusionsRADAR Epilepsy aims at developing a framework of continuous data collection intended to identify ictal and preictal states through the use of aRMT and pRMT in the real-life environment. The study was specifically designed to evaluate the clinical usefulness of the data collected via new technologies and compliance, technology acceptability, and usability for patients. These are key aspects to successful adoption and implementation of RMT as a new way to measure and manage long-term disorders.International Registered Report Identifier (IRRID)PRR1-10.2196/21840
Highlights
BackgroundThe last decade has seen an explosion in the capability of monitoring individuals via sensors in smartphones or wearable devices, and the range of parameters that can be measured by such technologies will continue to grow [1]
RADAR Epilepsy aims at developing a framework of continuous data collection intended to identify ictal and preictal states through the use of active remote measurement technology CSRI (aRMT) and pRMT in the real-life environment
The personal, social, and economic costs of uncontrolled epilepsy are considerable: seizure recurrence and unpredictability worsen the quality of life (QoL) of people with epilepsy and their families [7], people with active epilepsy have 4 to 5 times higher standardized mortality ratios compared with seizure-free individuals [8,9,10,11,12], and the economic burden for the health system is significant across countries [13,14]
Summary
BackgroundThe last decade has seen an explosion in the capability of monitoring individuals via sensors in smartphones or wearable devices, and the range of parameters that can be measured by such technologies will continue to grow [1]. Remote measurement technologies (RMTs) can unobtrusively measure human behavior and physiology and, combined with active measurement of daily experiences via smartphone apps, is an innovation that could be used to provide real-time information about the current clinical state of patients and information potentially predictive of future deterioration [1]. The gold standard for seizure detection is electroencephalography (EEG) in combination with video monitoring. This method has, by definition, a high sensitivity and a positive predictive value close to 100%. A growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. Most people with epilepsy self-identify factors that lead to increased seizure likelihood, including mood, behavior, sleep pattern, and cognitive alterations, all of which are amenable to measurement via multiparametric RMT
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