Study Results
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Basic Information
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COMPLETED
NA
54 participants
INTERVENTIONAL
2021-03-01
2024-05-06
Brief Summary
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Detailed Description
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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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Study Design
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NON_RANDOMIZED
PARALLEL
Home-based study: 60 patients will be selected in this study which will last a maximum of 1 year.
DIAGNOSTIC
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.
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)
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).
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)
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)
Eligibility Criteria
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Inclusion Criteria
* 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
* Known allergy to electrodes and patches.
* Implanted device, such as a pacemaker, cardioverter defibrillator (ICD), and/or neural stimulation device.
16 Years
ALL
No
Sponsors
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Byteflies
INDUSTRY
Universitaire Ziekenhuizen KU Leuven
OTHER
Responsible Party
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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
Countries
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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.
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.
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.
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.
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.
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.
Other Identifiers
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S64726
Identifier Type: -
Identifier Source: org_study_id
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