Seizures Detection in Real Life Setting (ECEME)

A Prospective, Multicenter, Exploratory Study for Epileptic Seizures Detection Through Multimodal Analysis of Cardiorespiratory and Actimetry Parameters

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).

Study Overview

• Status: Not yet recruiting
• Conditions: Focal Epilepsy; Epilepsy; Seizure
• Intervention / Treatment: Device: Wearable, non invasive sensor for seizure detection

• Study Type: Interventional
• Enrollment (Anticipated): 12
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Laurent RIBIERE; Phone Number: +33 (0)6 52 27 52 02; Email: l.ribiere@reliev.io

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 7 years and older (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Wearable, non invasive sensor for vital signs recording.; All included patients will be provided with a wearable, non invasive sensor for vital signs recording.	Device: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Number of true positive seizures.	The number of true positive seizures will be measured, ie. seizures detected through the sensor and reported in a seizures diary completed in real time by care giver.	From baseline up to 4 weeks.
Number of false positive seizures.	The number of false positive seizures will be measured, ie. seizures detected through the sensor but not reported in the seizures diary completed in real time by care giver.	From baseline up to 4 weeks.
Number of false negative seizures.	The number of false negative seizures will be measured, ie. seizures not detected through the sensor but reported in the seizures diary completed in real time by care giver.	From baseline up to 4 weeks.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Changes in Number of true positive, true negative and false negative seizures throughout the study duration.	Data from sensor will be analysed and compared to seizures diary.	From baseline up to 4 weeks.
Changes in number of true positive, true negative and false negative seizures depending on patients' characteristics.	Number of true positive, true negative and false negative seizures will be analysed and compared between patients based on patients' clinical characteristics.	From baseline up to 4 weeks.
Sensor tolerability from patients' perspective.	The French Version of the System Usability Scale (F-SUS) will be used. It is a self-questionnaire including 10 questions, ranging from 0 "I do not agree at all" up to 10 "I completely agree".	At 4 weeks after baseline.
Sensor tolerability from care givers' perspective.	A self-questionnaire including 5 questions will be used, ranging from 0 "I do not agree at all" up to 10 "I completely agree".	At 4 weeks after baseline.
Electrocardiogram signal quality in real life setting.	Electrocardiogram signal quality will be compared between data obtained from sensor (real life setting) and data obtained from video-EEG monitoring (hospital setting).	From baseline up to 4 weeks.
ECG data impact (ECG characteristics) on seizures detection.	Contribution from ECG data will be analysed as stand-alone parameter and as associated parameter in multimodal monitoring.	From baseline up to 4 weeks.
Heart rate impact on seizures detection.	Contribution of data from heart rate will be analysed as stand-alone parameter and as associated parameter in multimodal monitoring.	From baseline up to 4 weeks.
Respiration rate impact on seizures detection.	Contribution of data from respiration rate will be analysed as stand-alone parameter and as associated parameter in multimodal monitoring.	From baseline up to 4 weeks.
Body orientation impact on seizures detection.	Contribution from body orientation data will be analysed as stand-alone parameter and as associated parameter in multimodal monitoring.	From baseline up to 4 weeks.
Activity impact on seizures detection.	Contribution of activity data will be analysed as stand-alone parameter and as associated parameter in multimodal monitoring.	From baseline up to 4 weeks.

Collaborators and Investigators

• Sponsor: Reliev Technologies
• Investigators: Principal Investigator: Silvia NAPURI, MD, Chu Rennes

Study record dates

Study Major Dates

• Study Start (Anticipated): December 15, 2022
• Primary Completion (Anticipated): March 15, 2023
• Study Completion (Anticipated): March 15, 2023

Study Registration Dates

• First Submitted: November 4, 2022
• First Submitted That Met QC Criteria: November 22, 2022
• First Posted (Actual): December 2, 2022

Study Record Updates

• Last Update Posted (Actual): December 2, 2022
• Last Update Submitted That Met QC Criteria: November 22, 2022
• Last Verified: November 1, 2022

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Neurologic Manifestations; Epilepsy; Seizures; Epilepsies, Partial
• Other Study ID Numbers: ECEME; 2022-A01565-38 (Other Identifier: ANSM)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No