NCT06598189 · Felicia Chu
Ear-Seizure Detection (EarSD) Study
(EarSD001)
What this study is about
The proposed study is an investigator-initiated study that aims to measure the accuracy of a wearable seizure detection and prediction device (Ear-Seizure Detection Device (EarSD)) by simultaneous recording with conventional video-EEG (Electroencephalogram) on patients with epileptic seizures in the Epilepsy Monitoring Unit of the hospital.
View original scientific description
The proposed study is an investigator-initiated study that aims to measure the accuracy of a wearable seizure detection and prediction device (Ear-Seizure Detection Device (EarSD)) by simultaneous recording with conventional video-EEG (Electroencephalogram) on patients with epileptic seizures in the Epilepsy Monitoring Unit of the hospital.
Interventions
DEVICE
Ear-SD
The Ear-SD is a purely EEG recording device Continuous Electroencephalogram (cEEG), Electromyogram (EMG), Electrooculogram (EOG), Photoplethysmogram (PPG), Electrodermoactivity (EDA), and Inertial Measurement Unit (IMU). The Ear-SD device rests on the ears and connects to the scalp by two sticker electrodes.
DIAGNOSTIC_TEST
Electroencephalogram
Standard 21-channel scalp-continuous electroencephalogram (cEEG) with video recording and electrocardiogram (ECG)
Primary outcome measures
Seizure Recording Criteria 1
Time frame: Through study completion, an average of 7 Days
Recordings of Bioelectrical signal of subjects with the wearable device and simultaneous continuous EEG data is collected for the duration of hospitalization of participants. Outcome measures reported include number of seizure events per participant.
Seizure Recording Criteria 2
Time frame: Through study completion, an average of 7 Days
Recordings of Bioelectrical signal of subjects with the wearable device and simultaneous continuous EEG data is collected for the duration of hospitalization of participants. Outcome measures reported include average duration of each seizure in minutes and seconds and total recording time in hours aggregated to arrive at one reported value seizure classification.
Seizure Recording Criteria 3
Time frame: Through study completion, an average of 7 Days
Recordings of Bioelectrical signal of subjects with the wearable device and simultaneous continuous EEG data is collected for the duration of hospitalization of participants. Outcome measures reported include reported value seizure classification. Seizure classification includes Unclassified (UC), Focal Onset Aware (FOA), Focal Onset Impaired (FOIA), Focal to Bilateral Tonic-Clonic (FBTC).
Data Interpretation
Time frame: up to 2 years
EarSD extracted EEG signals from the log file plotted alongside EDF files from cEEG are measured and compared to detect seizure onset and offset times for data interpretation. Two-minute segments of cEEG European Data Format (EDF) consisting of non-seizure signals from periods before and after the seizures, and non-seizure signals from periods of daily activities like talking, eating, and walking are involved in the comparison to detect seizure onset and offset times. Prediction measurement of Seizure Sensitivity (SS) and False Positivity Rate per hour (FPR/h) are measured from the recorded data signals. Seizure Sensitivity (SS) is the ratio between the (number of predicted seizures)/(total number of seizures) = (number of true alarms)/(total number of seizures). FPR/h is the number of alarms that do not correspond to seizures raised in one hour. FPR/h = ((Number of false alarms/Interictal Duration) - (Number of False Alarms × Refractory period)).
Seizure Accuracy/Prediction
Time frame: up to 5 years
EarSD recordings from each electrode are separated and filtered to eliminate noise and artifact and results in 12 output signals (6 signals/ear) for comparison against cEEG EDF files for accuracy and precision. Mean, standard and average deviation, skewness, kurtosis, lowest and highest value, and the root mean square amplitude are measured from the dataset and are normalized between 0 and 1 then passed into the seizure detection and prediction Machine Learning (ML) model. ML model consisting of algorithms using deep neural networks (DNN), recurrent neural networks (RNNs) and Long Short-Term Memory networks (LSTM), classifies whether the signals are a seizure signal vs non-seizure signal, the focal type (left side/right side) and predicts the accuracy of seizures a minute ahead with the goal of achieving 96 percent or better accuracy and reducing the number of false positives.
Who can participate
This study lists these criteria on ClinicalTrials.gov. A study coordinator reviews eligibility during screening — this page does not determine whether you qualify.
Inclusion criteria
- Age ≥ 18 years.
- Patients admitted to UMass Memorial Epilepsy Monitoring Unit (EMU) for long term video-EEG monitoring as part of standard care of both focal and generalized epilepsy.
- Willing to wear the wearable device.
- Ability to provide informed consent
Exclusion criteria
- Subjects wearing other ear devices such as hearing aids.
- Inability or unwillingness to provide informed consent.
- Irritation of the skin where the device is to be placed.
- Patients with intracranial electrodes placement.
- Cognitive impaired individuals
- Pregnant Women
- Children (Age 0-17)
Where
- Worcester, Massachusetts
Collaborators
University of Massachusetts, Amherst
Related conditions & keywords
Frequently asked questions
What is a clinical trial?
A clinical trial is a research study that tests new medical treatments, drugs, devices, or procedures to determine their safety and effectiveness. Trials are carefully designed and monitored to protect participants while advancing medical knowledge.
Is it safe to participate?
Clinical trials follow strict safety guidelines and ethical standards. Trials must be reviewed and approved, and participants are closely monitored by medical professionals throughout the study. You can withdraw at any time if you choose.
Will I be compensated?
Many clinical trials offer compensation for your time, travel expenses, and inconvenience. The specific compensation varies by study and will be discussed during the screening process. All study-related medical care is typically provided at no cost to participants.
Will I receive a placebo instead of treatment?
When effective treatment exists, participants typically receive either the standard treatment plus the study intervention, or the standard treatment plus placebo. You would not be denied effective care. Placebos are primarily used when no proven treatment is available, or in addition to standard care. Your trial consent form will clearly explain what treatments you may receive.
Can I leave a trial if I change my mind?
Absolutely. Participation in clinical trials is completely voluntary. You have the right to withdraw from the study at any time, for any reason, without penalty or loss of benefits to which you are otherwise entitled.
How long does a clinical trial last?
Trial duration varies widely depending on the study design and purpose. Some trials last just a few weeks, while others may continue for months or years. The study coordinator will provide specific timeline information during your screening call.
Data: ClinicalTrials.gov · synced Oct 28, 2025 · Source of record for eligibility and locations