NCT07835594Not yet recruiting
Studying Heart Rhythms With a Wearable Sensor to Detect and Predict Seizures in People With Epilepsy
Heart Rhythm Analysis, Seizure Detection and Prediction Using a Textile-Based Wearable Sensor in Patients With Epilepsy
Source: ClinicalTrials.gov · Last updated 23 Sept 2026
Brief summary (registry, in English)
The goal of this observational study is to understand heart rhythm changes in adults with epilepsy. It will also explore whether computer programs can use heart recordings to detect or predict seizures. The study will include 20 adults with temporal lobe epilepsy and 20 healthy volunteers. Participants with epilepsy will have ongoing seizures despite treatment with at least two suitable medicines. All participants will be 18 years or older. In temporal lobe epilepsy, seizures start in a specific region of the brain. These seizures may spread to both sides of the brain, causing muscle stiffening and rhythmic jerking. Researchers will focus on these spreading seizures when developing seizure detection and prediction methods. The main questions are: * How do heart rate and heartbeat timing differ between people with and without epilepsy? * How do these measures change before, during, and after seizures? * Can computer programs learn patterns in heart recordings to detect seizures or predict them before they start? Researchers will compare heart rate and heart rate variability between the two groups. Heart rate variability describes changes in the time between one heartbeat and the next. They will compare recordings during rest, wakefulness, and sleep. Participants will: * Wear a fabric chest band that records the heart's electrical activity. * Have brain activity recorded through sensors on the scalp, alongside video recording. * Rest quietly while awake for one hour during the recording period. Participants with epilepsy will have recordings during their usual hospital monitoring. Healthy volunteers will have 24 hours of recording at the same hospital. Researchers will use the brain recordings and video to identify when seizures happen. They will develop and test computer programs that learn patterns in the heart recordings.
- Status (registry)
- Not yet recruiting
- Study type
- Observational
- Enrollment
- 40 (estimated)
- First submitted
- 16 Sept 2026
- Start date
- 15 Oct 2026
- Primary completion date
- 15 Oct 2028
- Lead sponsor
- Acibadem University
- Diseases
- Epilepsy
- NCT number
- NCT07835594
What you commit to
- Study type: Observational
- Planned participants: 40
- From 15 Oct 2026 to the primary completion date, 15 Oct 2028
- 1 site in 1 country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- A concomitant disease or medication use that may substantially affect heart rate or heart rate variability (HRV).
Other illness
- Epilepsy group:
- A neurodevelopmental disorder that prevents cooperation or following instructions.
- A physical condition that prevents placement of the chest band.
- Absence of an epilepsy diagnosis or identification of psychogenic nonepileptic seizures.
- An implanted cardiac or neurostimulation device, such as a pacemaker, vagus nerve stimulator (VNS), or deep brain stimulation (DBS) device.
- Allergy, skin sensitivity, or a skin lesion that prevents use of the electrodes or chest band.
- Having been diagnosed with major depressive disorder.
- Healthy volunteer group:
- A history of epilepsy or seizures.
- Cardiovascular disease, a condition that may cause autonomic neuropathy, or medication use that may substantially affect heart rate or HRV.
- Allergy, skin sensitivity, or a skin lesion that prevents use of the electrodes or chest band.
- Having been diagnosed with major depressive disorder.
- Pregnancy or breastfeeding.
- Analysis-specific provisions:
- The absence of a recorded target seizure during monitoring will not by itself exclude an epilepsy participant from the study; these recordings may contribute to heart rate and HRV analyses. Recordings from participants with one or two target seizures may also contribute to patient-independent machine learning models. Patient-specific machine learning models require at least three recorded target seizures from the same participant.
Other
- Inability to securely attach the electrocardiography (ECG) or EEG sensors for reliable recording.
- Pregnancy or breastfeeding.
Who the study is looking for
- Epilepsy group:
- Age 18 years or older.
- Diagnosis of temporal lobe epilepsy and admission to the epilepsy monitoring unit for video-electroencephalography (video-EEG) monitoring.
- Ongoing seizures despite treatment with at least two appropriately selected and tolerated antiseizure medicines at adequate doses and for adequate durations.
- History or clinical suspicion of focal to bilateral tonic-clonic seizures.
- Provision of written informed consent.
- Healthy volunteer group:
- Age 18 years or older.
- No known epilepsy or history of seizures.
- Provision of written informed consent.
Age in the registry: 18 years to - · Sex: All · Accepts healthy volunteers
Sites (1)
Sites in registry order. Pick your city on the disease page to sort them by distance.
| Site | City | Country | Site status |
|---|---|---|---|
| Sancaktepe Sehit Prof.Dr. Ilhan Varank Training and Research Hospital Coordinator of this site? Confirm its status | Istanbul | Turkey (Türkiye) | Unknown status |
This page is information, not medical advice. Discuss any trial with your doctor.