Epilepsy Clinical Trial
Official title:
Development of a Minimally Invasive Seizure Gauge
Verified date | September 2022 |
Source | Seer Medical Pty Ltd |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
The researchers are trying to assess changes in physiological signals before and during seizures.
Status | Enrolling by invitation |
Enrollment | 40 |
Est. completion date | December 31, 2023 |
Est. primary completion date | December 31, 2023 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 18 Years and older |
Eligibility | 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. |
Country | Name | City | State |
---|---|---|---|
Australia | Seer Medical | Melbourne | Victoria |
Lead Sponsor | Collaborator |
---|---|
Seer Medical Pty Ltd |
Australia,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Multimodal Assessment of Physiological Signals During Seizure Events Measurable with Wearable Sensors | 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. | 2-7 days approximately | |
Primary | Wearable Sensors Comfort Assessment | 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. | 2-7 days approximately | |
Primary | Seizure Detection and Prediction using Multimodal Physiological Data | 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. | 2-7 days approximately |
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