Clinical trial NCT06093490: Detecting Absence Seizures Using Hyperventilation and Eye Movement Recordings
Official title: A Mobile Health Application to Detect Absence Seizures Using Hyperventilation and Eye-Movement Recordings
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Absence Epilepsy, Childhood
Absence Seizures
Absence Epilepsy
Epilepsy in Children
Staring
Seizures
Keywords: absence seizures
absence epilepsy
hyperventilation
staring spells
Lead sponsor: Eysz, Inc.
Sponsor class: INDUSTRY
Collaborators: name: National Institute of Neurological Disorders and Stroke (NINDS)
First posted: 2023-10-23
Enrollment: 75
Sex: ALL
Minimum age (years): 4
Maximum age (years): 12
Standard ages: CHILD
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Children undergoing routine EEG as part of clinical care at risk or known to have childhood absence epilepsy who will be undergoing hyperventilation

Brief summary: This study is being done to find out if a smartphone app can identify absence seizures. Children who have a history of absence seizures, as well as children without any seizure history, will be testing out the app. If participating the child will be guided through hyperventilation, an activity that asks the child to take quick, deep breaths. The app will record video of the child's face and sounds they make during hyperventilation. Hyperventilation is a safe and established technique frequently used during EEG (electroencephalogram) to encourage seizure occurrence. The App will be used during a regularly scheduled EEG.

Detailed description: This observational study focuses on validating the use of the Eysz mHealth App - a smartphone-based tool for guided Hyperventilation (HV) and data collection - to aid clinicians in identifying absence seizures in people at risk for childhood absence epilepsy (CAE). The Eysz mHealth app will guide users through HV via interactive graphics while capturing audio and video data using smartphone sensors (e.g., camera, microphone) from which eye movements, facial biometrics/ expressions, number and length of exhales will be extracted.

The goal of this observational study is to determine an epileptologist's performance in identifying HV-induced absence seizures using video data collected from a smartphone when compared to the gold standard interpretation of the EEG. The exploratory goal is to develop machine learning based algorithms to identify HV-induced seizures.

Eligibility criteria: Inclusion Criteria:

* typical absence seizure during use of the Eysz Hyperventilation Recorder or Control

Exclusion Criteria:

* Other seizure type besides typical absence seizure during use of the Eysz Hyperventilation Recorder
* subclinical seizure activity
* inability to participate with study procedures
* contraindications to hyperventilation including history of subarachnoid hemorrhage, sickle cell anemia, recent cerebrovascular accident or myocardial infarction, significant cardiopulmonary disease, active asthma, known aneurysm, known moyamoya disease, or pregnancy.
* People who have a history of generalized tonic clonic convulsions (GTCs) provoked by hyperventilation

Primary outcomes:
measure: Accuracy of Eysz Hyperventilation (HV) Recorder Compared to video EEG (VEEG)
timeFrame: epileptologist review of 5 minutes of use of the Eysz Hyperventilation Recorder
Secondary outcomes:
Other outcomes:
Locations:
city: Cincinnati
country: United States
facility: Cincinnati Children's Hospital
state: Ohio
Study officials:
References: