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Age: 12Years - 65Years
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ID05845255

Study to Validate the Mjn-SERAS Device for Detecting and Predicting Seizures in People Aged 12 to 65 with Drug-Resistant Epilepsy Assessing the Devices Impact on Quality of Life and Safety in Everyday Life

Led by MJN Neuroserveis, S.L · Updated on 2024-10-15

130

Participants Needed

6

Research Sites

26 weeks

Total Duration

AI-Summary

What this Trial Is About

This research aims to evaluate a medical device called mjn-SERAS in people aged 12 to 65 years with drug-resistant epilepsy. The study is conducted across multiple centers and countries, including Spain, Germany, and the UK. It focuses on assessing the devices impact on quality of life by detecting epileptic seizures early and providing alerts before seizures occur, helping to improve patient safety and reduce anxiety linked to seizure unpredictability. The intervention involves using the mjn-SERAS device, a wearable, non-invasive EEG recorder paired with a smartphone application. The study includes three phases a baseline phase for initial assessments over two months, an intervention phase with artificial intelligence training lasting 4 to 10 weeks, followed by at least six months of active seizure risk alert monitoring, and a results phase comparing outcomes with baseline data. Participants wear a customized earpiece for EEG recording and use the app to report seizures and receive alerts. Participants will be involved for at least six months, during which their seizure occurrences, types, and related accidents will be monitored and recorded. Various questionnaires will assess quality of life, anxiety, depression, and social functioning. The devices accuracy and safety will also be evaluated. Data are collected through seizure diaries, app reports, and clinical evaluations to understand the devices effect on health resources, mental well-being, and patient safety over time.

CONDITIONS

Brief Title

Evaluation of the Epilepsy-related Quality of Life, Seizure-related Accidents and Validation of the Mjn-SERAS Solution in the Normalised Patient Environment with Real-World Data

Research Team

D

David Blánquez, Engineer

F

Fernando Atienza, QM

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