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Recruiting NCT06598189

Ear-Seizure Detection (EarSD) Study

No phase Interventional Seizures Epilepsy

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: Ear-SD, Electroencephalogram.
Who it may be relevant to
Registry conditions: Seizures, Epilepsy. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
United States
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

Real-time Seizure Detection, Classification, and Prediction Using a Low-Cost Low-Burden Ear-worn System

Overview

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.

Detailed description

A wearable seizure detection and prediction device (EarSD) is worn by patients with epileptic seizures. In this study, the goal is to validate the accuracy of a newly developed portable seizure detection device by examining if the Ear-SD device can (1) provide more comfort, (2) be unobtrusive to the subject during daily activities, and (3) be able to provide additional insight on a patients' seizure control.

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]
  • Seizure Recording Criteria 2 [Time frame: Through study completion, an average of 7 Days]
  • Seizure Recording Criteria 3 [Time frame: Through study completion, an average of 7 Days]
  • Data Interpretation [Time frame: up to 2 years]
  • Seizure Accuracy/Prediction [Time frame: up to 5 years]
Secondary outcome measures (1)
  • Qualitative Satisfaction Survey [Time frame: Through study completion, an average of 7 Days]

Eligibility criteria

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.
  • Prisoners
  • Cognitive impaired individuals
  • Pregnant Women
  • Children (Age 0-17)

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Allocation
N/A
Model
Single group
Masking
Open label
Primary purpose
Diagnostic

Study locations

United States · 2 centers
  • Ummmc-Memorial Campus — Worcester
  • Ummmc-University Campus — Worcester

Publications

  • Barranco R, Caputo F, Molinelli A, Ventura F. Review on post-mortem diagnosis in suspected SUDEP: Currently still a difficult task for Forensic Pathologists. J Forensic Leg Med. 2020 Feb;70:101920. doi: 10.1016/j.jflm.2020.101920. Epub 2020 Feb 5. PMID 32090969
  • Blachut B, Hoppe C, Surges R, Elger C, Helmstaedter C. Subjective seizure counts by epilepsy clinical drug trial participants are not reliable. Epilepsy Behav. 2017 Feb;67:122-127. doi: 10.1016/j.yebeh.2016.10.036. Epub 2017 Jan 28. PMID 28139449
  • Prior PF, Virden RS, Maynard DE. An EEG device for monitoring seizure discharges. Epilepsia. 1973 Dec;14(4):367-72. doi: 10.1111/j.1528-1157.1973.tb03975.x. No abstract available. PMID 4521092
  • Manabe, H., Fukumoto, M., & Yagi, T. (2015a). Conductive rubber electrodes for earphone-based eye gesture input interface. Personal and Ubiquitous Computing, 19(1), 143-154. doi:10.1007/s00779-014-0818-8
  • A. H. Shoeb and J. Guttag, "Application of Machine Learning To Epileptic Seizure Detection," in 2010 International Conference on Machine Learning (ICML), Jun. 2010. [Online]. Available: https://www.semanticscholar.org/paper/Application-of-Machine-Learning-ToEpileptic-Shoeb-Guttag/57e4afe9ca74414fa02f2e0a929b64dc9a03334d.
  • Zandi AS, Javidan M, Dumont GA, Tafreshi R. Automated real-time epileptic seizure detection in scalp EEG recordings using an algorithm based on wavelet packet transform. IEEE Trans Biomed Eng. 2010 Jul;57(7):1639-51. doi: 10.1109/TBME.2010.2046417. PMID 20659825
  • Doyle OM, Temko A, Marnane W, Lightbody G, Boylan GB. Heart rate based automatic seizure detection in the newborn. Med Eng Phys. 2010 Oct;32(8):829-39. doi: 10.1016/j.medengphy.2010.05.010. Epub 2010 Jul 1. PMID 20594899
  • Jansen K, Varon C, Van Huffel S, Lagae L. Peri-ictal ECG changes in childhood epilepsy: implications for detection systems. Epilepsy Behav. 2013 Oct;29(1):72-6. doi: 10.1016/j.yebeh.2013.06.030. Epub 2013 Aug 10. PMID 23939031

Identifiers

NCT: NCT06598189 · STUDY00001889

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗