Detecting Absence Seizures Using Eye Tracking

Seizures can be difficult to detect outside of the hospital even with careful observation by a caregiver. EEG is the best method that we have to detect seizures- but it is uncomfortable for long term use outside of the hospital. The goal of this study is to develop a comfortable system that uses a wearable eye-tracker similar to eyeglasses to assist people with epilepsy in counting and measuring the severity of seizures. People participating in this study will have a routine EEG performed while an eye tracker measures eye movements. After the EEG is complete the researchers will compare the eye movements to the EEG to develop a software program that can detect seizures from eye movements.

• Eye movement analysis (Diagnostic test): Eye movements will be analyzed to identify if seizures are present and compared to the EEG read

Primary outcomes

• Eysz algorithm to detect absence seizures [1 hour]: EEG is burdensome and limited. The current accepted method of counting seizures is observation which fails to identify > 50% of seizures. The goal is to validate the Eysz absence seizure detection algorithm and show significant improvement over current standard of care

Sex: All, ages: 4 Years to 100 Years

Inclusion Criteria:

1. Provision of signed and dated informed consent form- per local IRB
2. Stated willingness to comply with all study procedures including the clicker test and availability for the duration of the study
3. Male or female, aged 4-100
4. Experience known typical absence seizures as defined by the ILAE 2017 classification or referred to EEG lab for staring spell or concern for absence seizure

   a. This will allow for inclusion of children and adults across the entire spectrum of disease states including new diagnosis (medication naive), medication responsive and non-medication responsive
5. Scheduled for clinical EEG observation

Exclusion Criteria:

1. Intolerant of wearing or unable to wear the eyeglasses
2. Autism or other developmental disorder that the PI thinks will interfere with data collection
3. History of aggression that the PI thinks will interfere with data collection
4. History of not tolerating EEG that the PI thinks will interfere with data collection
5. Unable to give consent (for individuals ≥ 18 years old) unless they have an adult with power of attorney to consent

• Rachel Kuperman, MD, Principal investigator, Eysz, Inc.