Electrocardiography, Epilepsy, Seizures
Conditions
Keywords
seizure detection
Brief summary
The aim of our project is to develop an epileptic seizure detection algorithm based on the the continuous analysis of the Electrocardiogram
Detailed description
In a first step, the team will build a multi-parametric algorithm on existing records issued from the Epilepsy Monitoring Units. Each selected record will be analyzed by EMU medical team in order to detect seizure on the EEG. The algorithm will adapt in order to obtain the best sensitivity and specificity regarding seizure detection. in a second step,algorithm will validate on a cohort of other recordings in patients with epilepsy
Interventions
None listed
Sponsors
University Hospital, Lille
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* patients with epilepsy * with a long-term video-EEG recording * 1 (or more) seizure (s) recorded * onset seizure clearly defined on the basis of the EEG
Exclusion criteria
* bad quality of the Electrocardiogram recording * pace-maker * non sinus rhythm
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| ROC curve for seizure detection | 24 months | ROC curve gives the relation between detection probability and false alarm probability of the algorithm that will be developped |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Time of detection of seizures | 24 months | Time of detection of seizures by the algorithm |
| ROC curve for Psychogenic seizure detection | 24 months | ROC curve for Psychogenic seizure detection |
Countries
France
Outcome results
None listed