Seizures Detection in Real Life Setting

NCT ID: NCT05635396

Last Updated: 2022-12-02

Basic Information

• Recruitment Status: UNKNOWN
• Clinical Phase: NA
• Total Enrollment: 12 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-12-15
• Study Completion Date: 2023-03-15

Brief Summary

Epilepsy is a disabling neurological disease that affects tens of millions of people worldwide. Despite therapeutic advances, about a third of these patients suffer from treatment-resistant forms of epilepsy and still experience regular seizures.All seizures can last and lead to status epilepticus, which is a major neurological emergency. Epilepsy can also be accompanied with cognitive or psychiatric comorbidities.

Reliable seizures count is an essential indicator for estimating the care quality and for optimizing treatment. Several studies have highlighted the difficulty for patients to keep a reliable seizure diary due for example to memory loss or perception alterations during crisis. Whatever the reasons, it has been observed that at least 50% of seizures are on average missed by patients.

Seizure detection has been widely developed in recent decades and are generally based on physiological signs monitoring associated with biomarkers search and coupled with detection algorithms. Multimodal approaches, i.e. combining several sensors at the same time, are considered the most promising.

Mobile or wearable non invasive devices, allowing an objective seizures documentation in daily life activities, appear to be of major interest for patients and care givers, in detecting and anticipating seizures occurence.

This single-arm exploratory, multicenter study aims at assessing whether the use of such a non-invasive, wearable device can be useful in a real life setting in detecting seizures occurence through multimodal analysis of various parameters (heart rate, respiratory and accelerometry).

Conditions

Epilepsy; Seizure; Focal Epilepsy

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: OTHER
• Blinding Strategy: NONE

Study Groups

Wearable, non invasive sensor for vital signs recording.

All included patients will be provided with a wearable, non invasive sensor for vital signs recording.

Group Type: EXPERIMENTAL

Wearable, non invasive sensor for seizure detection

Intervention Type: DEVICE

The device consists of a chest strap and an electronics module that attaches to the strap. The device stores and transmits vital sign data including ECG, heart rate, respiration rate, body orientation and activity. This sensor will be worn every day (on a 24 hours basis) excepted during weekends for up to 4 weeks.

Interventions

Wearable, non invasive sensor for seizure detection

The device consists of a chest strap and an electronics module that attaches to the strap. The device stores and transmits vital sign data including ECG, heart rate, respiration rate, body orientation and activity. This sensor will be worn every day (on a 24 hours basis) excepted during weekends for up to 4 weeks.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Patients aged 7 years old or more
• Patients with drug-resistant focal epilepsy
• Patients with high frequency seizures according to investigator's judgement
• Patients that can be followed 4 weeks after inclusion
• Informed consent form signed.

Exclusion Criteria

• Generalised tonic-clonic seizures
• Frequent psychogenic non-epileptic seizures
• Pregnant or breastfeeding patients
• Patients displaying sensor contraindications

• Minimum Eligible Age: 7 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Reliev Technologies

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Silvia NAPURI, MD

Role: PRINCIPAL_INVESTIGATOR

CHU Rennes

Central Contacts

Laurent RIBIERE

Role: CONTACT

l.ribiere@reliev.io

(0)6 52 27 52 02 ext. +33

Other Identifiers

2022-A01565-38

Identifier Type: OTHER

Identifier Source: secondary_id

ECEME

Identifier Type: -

Identifier Source: org_study_id