Sensor-Dot and Plug 'n Patch Study in Epilepsy

NCT ID: NCT04642105

Last Updated: 2024-05-08

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

54 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-03-01

Study Completion Date

2024-05-06

Brief Summary

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The investigators plan to determine whether it is possible to use a small, unobtrusive wearable device (the Sensor Dot with Plug 'n Patch system) to follow-up epilepsy in the home environment through measurement of different biosignals (EEG, ECG, EMG, motion, skin temperature, respiration and oxygen saturation) for prolonged periods in patients with epilepsy. If this is possible, the investigators will study the chronobiology of epilepsy.

Detailed Description

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In this study, the investigators will make use of a small, discrete and unobtrusive wearable, the Sensor-Dot (https://www.byteflies.com/) and newly developed electrode patches (Plug 'n Patch system). The aim is multimodal profiling of people with epilepsy to determine which signals are clinically useful for long-term home monitoring. Biosignals that will be registered include EEG, EMG, and ECG, respiration, oxygen saturation, skin temperature and motion.

The first part of the study is hospital-based and will last 5 days. The investigators will compare the biosignals of the Sensor Dot and the Plug 'n Patch system with those measured with hospital equipment. Participants are 15 patients with refractory focal epilepsy who will be admitted to the hospital for long-term videoEEG registration of epileptic seizures as part of a presurgical evaluation.

The second part of the study is home-based and will last for a maximum of 1 year. Sixty participants will be selected with refractory idiopathic generalized epilepsy (n=15), refractory focal epilepsy (n=30) and frequent nocturnal tonic-clonic seizures (n=15). The aim is to determine and improve usability of the Sensor Dot and Plug 'n Patch system upon long-term use in the home environment. The investigators will determine the number of patients with side effects and adverse events of the Sensor Dot and Plug 'n Patch system, e.g. contact allergic eczema. The investigators will determine the total time that participants wear the Sensor Dot and Plug 'n Patch system, and the reason why participants do not wear it.

The investigators further aim to determine whether epileptic seizures occur in cycles, and will study interactions between epilepsy and sleep. The investigators will also study whether body temperature occurs in recurring cycles and is related with the occurrence of epileptic seizures. The investigators will study changes in EEG, respiration, heart rate, skin temperature and oxygen saturation during tonic-clonic seizures. The investigators will determine whether it is possible that the Sensor-Dot and Plug 'n Patch system can be used as a seizure forecaster.

Conditions

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Epilepsy

Study Design

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Allocation Method

NON_RANDOMIZED

Intervention Model

PARALLEL

Hospital-based study: 15 patients will be selected in this study which will last 5 days.

Home-based study: 60 patients will be selected in this study which will last a maximum of 1 year.
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Study Groups

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Hospital-based study

The investigators will select 15 patients with refractory focal epilepsy who are admitted to the videoEEG room for longterm videoEEG recording as part of a presurgical evaluation. The Sensor-Dot and Plug 'n Patch recordings will be compared with the gold-standard videoEEG recordings.

Group Type EXPERIMENTAL

Sensor-Dot and Plug 'n Patch system

Intervention Type DEVICE

We will use a small, unobtrusive wearable (Sensor-Dot) to measure different biosignals (EEG, ECG, EMG, motion, skin temperature, respiration and oxygen saturation) for up to one year using newly developed skin adhesives and patches (Plug 'n Patch system)

Home-based study

The investigators will select 30 patients with refractory focal epilepsy, 15 patients with refractory idiopathic generalized epilepsy and 15 patients with frequent tonic-clonic seizures, i.e. a group at increased risk for sudden unexpected death in epilepsy (SUDEP).

Group Type EXPERIMENTAL

Sensor-Dot and Plug 'n Patch system

Intervention Type DEVICE

We will use a small, unobtrusive wearable (Sensor-Dot) to measure different biosignals (EEG, ECG, EMG, motion, skin temperature, respiration and oxygen saturation) for up to one year using newly developed skin adhesives and patches (Plug 'n Patch system)

Interventions

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Sensor-Dot and Plug 'n Patch system

We will use a small, unobtrusive wearable (Sensor-Dot) to measure different biosignals (EEG, ECG, EMG, motion, skin temperature, respiration and oxygen saturation) for up to one year using newly developed skin adhesives and patches (Plug 'n Patch system)

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Patients who are 18 years of age or older, who signed an informed consent form, and teenagers over 16 years of age who assent, with their parents signing an informed consent form, and:
* Epilepsy syndrome: idiopathic generalized epilepsy (n=15), patients at increased risk for SUDEP, i.e. have more than 1 nocturnal tonic clonic seizures (TCS) per month (n=15), refractory focal epilepsy with a presurgical evaluation at UZ Leuven (n=30)
* Minimum one seizure per month
* Patient is able and motivated to handle the Sensor-Dot and Plug 'n Patch system independently, to fill out the Helpilepsy app on a daily basis and to wear the Sensor-Dot and Plug 'n Patch system for a full year 24/24-7/7; fallback option for patients for whom wearing the device during the day is too obtrusive: measurement only during the evening and nighttime.

Exclusion Criteria

* Inability to provide written informed consent or assent.
* Known allergy to electrodes and patches.
* Implanted device, such as a pacemaker, cardioverter defibrillator (ICD), and/or neural stimulation device.
Minimum Eligible Age

16 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Byteflies

INDUSTRY

Sponsor Role collaborator

Universitaire Ziekenhuizen KU Leuven

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Wim Van Paesschen, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

UZ Leuven

Locations

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UZ Leuven

Leuven, Vlaams-Brabant, Belgium

Site Status

Countries

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Belgium

References

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Paesschen WV. The future of seizure detection. Lancet Neurol. 2018 Mar;17(3):200-202. doi: 10.1016/S1474-4422(18)30034-6. No abstract available.

Reference Type BACKGROUND
PMID: 29452676 (View on PubMed)

Verdru J, Van Paesschen W. Wearable seizure detection devices in refractory epilepsy. Acta Neurol Belg. 2020 Dec;120(6):1271-1281. doi: 10.1007/s13760-020-01417-z. Epub 2020 Jul 6.

Reference Type BACKGROUND
PMID: 32632710 (View on PubMed)

Mikkelsen KB, Ebajemito JK, Bonmati-Carrion MA, Santhi N, Revell VL, Atzori G, Della Monica C, Debener S, Dijk DJ, Sterr A, de Vos M. Machine-learning-derived sleep-wake staging from around-the-ear electroencephalogram outperforms manual scoring and actigraphy. J Sleep Res. 2019 Apr;28(2):e12786. doi: 10.1111/jsr.12786. Epub 2018 Nov 13.

Reference Type BACKGROUND
PMID: 30421469 (View on PubMed)

Gu Y, Cleeren E, Dan J, Claes K, Van Paesschen W, Van Huffel S, Hunyadi B. Comparison between Scalp EEG and Behind-the-Ear EEG for Development of a Wearable Seizure Detection System for Patients with Focal Epilepsy. Sensors (Basel). 2017 Dec 23;18(1):29. doi: 10.3390/s18010029.

Reference Type BACKGROUND
PMID: 29295522 (View on PubMed)

De Cooman T, Vandecasteele K, Varon C, Hunyadi B, Cleeren E, Van Paesschen W, Van Huffel S. Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning. Front Neurol. 2020 Feb 26;11:145. doi: 10.3389/fneur.2020.00145. eCollection 2020.

Reference Type BACKGROUND
PMID: 32161573 (View on PubMed)

Vandecasteele K, De Cooman T, Dan J, Cleeren E, Van Huffel S, Hunyadi B, Van Paesschen W. Visual seizure annotation and automated seizure detection using behind-the-ear electroencephalographic channels. Epilepsia. 2020 Apr;61(4):766-775. doi: 10.1111/epi.16470. Epub 2020 Mar 11.

Reference Type BACKGROUND
PMID: 32160324 (View on PubMed)

Other Identifiers

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S64726

Identifier Type: -

Identifier Source: org_study_id

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