Sensor-Dot and Plug 'n Patch Study in Epilepsy

Multimodal Profiling of People With Epilepsy to Determine Which Signals Are Clinically Useful for Long-term Home Monitoring

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.

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.

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.

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.

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).

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)

In the hospital-based study, the investigators will compare the number epileptic seizures measured with the Sensor-Dot and Plug 'n Patch system in comparison with the hospital-based equipment.

In the hospital-based study, the investigators will compare the heartrate of participants measured with the Sensor-Dot and Plug 'n Patch system in comparison with hospital-based equipment.

In the hospital-based study, the investigators will compare oxygen saturation of participants measured with a finger pulse oximetry versus the Sensor-Dot and Plug 'n Patch system.

In the hospital-based study, the investigators will compare the respiration rate of participants measured with a chest belt during videoEEG registration versus the Sensor-Dot and Plug 'n Patch system.

In the hospital-based study, the investigators will compare the skin temperature of participants using axillary measurement with a negative temperature coefficient thermistor versus the Sensor-Dot and Plug 'n Patch system, which is based on infrared thermometry.

In the home-based study, 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

In the home-based study, 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

To study whether cycles in epileptic seizures, interictal epileptic discharges, sleep and skin temperature allow to define a pro-ictal state during which the occurrence of epileptic seizures is more likely, i.e. seizure forecasting

To study changes in EEG, respiration, heart rate, skin temperature and oxygen saturation during tonic-clonic seizures

To determine if changes in IEDs, skin temperature, sleep cycles can define seizure recurrence in women with catamenial epilepsy

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.

We plan to share the individual biosignals (EEG, EMG, ECG, movement, skin temperature, respiration), de-identified demographics and epilepsy-related data two years after the finish of the study upon request to researchers who provide a methodologically sound proposal.

Data will be made available upon request to researchers who provide a methodologically sound proposal. Proposals should be directed to Wim.vanpaesschen@uzleuven.be

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.