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NCT05637762: DetecTeppe

Development of a Seizure Detection Algorithm Based on Heart Rate and Movement Analysis

Completed Last updated 17 December 2025
What this trial tests

trial testing - EEG video recording or extension of an EEG video recording planned as part of the care - Wearing a connected heart rate and motion recording patch in Epilepsy in 13 participants. Completed in 24 April 2025.

Timeline
5 June 2023
Primary endpoint
24 April 2025
24 April 2025

Quick facts

Lead sponsorFondation Ophtalmologique Adolphe de Rothschild
StatusCompleted
Study typeOBSERVATIONAL
Enrollment13
Start date5 June 2023
Primary completion24 April 2025
Estimated completion24 April 2025
Sites1 location across France

Drugs / interventions tested

Conditions studied

Sponsor

Fondation Ophtalmologique Adolphe de Rothschild — full company profile →

Who can join

18 and older, any sex, with Epilepsy. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Epilepsy is the 3rd neurological pathology after migraines and dementia syndromes with a high estimate of nearly 600,000 people affected in France. The disease is characterized by the repetition of epileptic seizures on the one hand, but also by the cognitive, behavioral, psychological and social consequences of this condition, especially when the epileptic disease is not stabilized. Epileptic patients feel a great deal of stress due to the unpredictability of the occurrence of seizures. Seizure detection is of great interest to bioinformatics researchers and to people with epilepsy and their caregivers. Recent advances in physiological sensor technologies and artificial intelligence have opened the possibility of developing systems capable of closely monitoring the frequency of epileptic seizures with a direct impact on therapeutic adaptations. This may eventually allow for seizure prediction and/or "seizure weather" (i.e., seizure forecasting) if there is a particular chronotype of seizure occurrence for a given individual. Currently, few devices have a sufficient level of evidence regarding their effectiveness to be recommended. Those that seem to be the most advanced are those that allow the identification of hypermotor seizures, including tonic-clonic generalized seizures and tonic-clonic secondary generalized focal seizures, mostly occurring at night. The latter represent only a small part of epileptic seizures. The objective of the present study is to build a real life database in order to develop a seizure detection algorithm. The recorded data will be heart rate via ECG and movement data via 9 variables measured on 3 axes x, y, z, with 3 sensors: accelerometer, gyroscope, magnetometer. These data will be collected using a connected patch available on the market (CE marking). At the same time, the patients will benefit from a long term video-EEG examination which will be annotated by the doctors and will be used as a gold standard for the identification of seizures in order to train the algorithm. This more complete base will be used to develop an algorithm previously developed from retrospective data.

Publications & conference data

No peer-reviewed publications indexed yet for this trial. Completed trials usually publish results within 12-18 months.

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Other recruiting trials for Epilepsy

Currently open trials in the same condition.

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Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05637762.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing