Development of a Minimally Invasive Seizure Gauge
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Epilepsy
- Sponsor
- Seer Medical Pty Ltd
- Enrollment
- 40
- Locations
- 1
- Primary Endpoint
- Multimodal Assessment of Physiological Signals During Seizure Events Measurable with Wearable Sensors
- Status
- Completed
- Last Updated
- 11 months ago
Overview
Brief Summary
The researchers are trying to assess changes in physiological signals before and during seizures.
Detailed Description
Subjects that are undergoing video EEG monitoring in their home for their epilepsy at Seer Medical will be consented to participate in this study for a minimum of two days and/or the duration of their monitoring period for their clinical care. Subjects will be asked to wear up to 4 different commercially available seizure detection devices and complete surveys. When the subjects clinical EEG monitoring is completed data scientists will analyze the data to identify patterns.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Patients with epilepsy undergoing scalp EEG for clinical care, or an implanted device capable of monitoring brain activity and identifying seizures
- •Patients of age 18 or above
Exclusion Criteria
- •Cognitive or psychiatric condition rendering patient unable to cooperate with data collection, or manage and recharge smart watch and tablet computer devices.
Outcomes
Primary Outcomes
Multimodal Assessment of Physiological Signals During Seizure Events Measurable with Wearable Sensors
Time Frame: 2-7 days approximately
We will collect physiological signals with the three wearable, noninvasive biosensors in Seer Medical patients undergoing scalp-recorded video EEG-ECG as part of their clinical epilepsy evaluation. These signals include temperature, light level, EEG, heart rate, galvanic skin response, PPG, accelerometry. We will evaluate biosignals based on reliability to detect seizures.
Wearable Sensors Comfort Assessment
Time Frame: 2-7 days approximately
We will collect physiological signals with the three wearable, noninvasive biosensors in Seer Medical patients. We will evaluate subject comfort and ease of use for each device, measured through quantitative surveys.
Seizure Detection and Prediction using Multimodal Physiological Data
Time Frame: 2-7 days approximately
We will apply data mining and machine learning methods to identify patterns in the collected physiological signals and correlate these patterns with the timing of seizures identified by the patient's clinical video-EEG monitoring. We will use sensitivity and specificity measures to determine which signals are most useful in detecting and predicting seizure events.