Ceribell, Inc.

Mehdi Hajinoroozi

Raymond Woo

Josef Parvizi

Xingjuan Chao

Alexander M Grant

Jianchun Yi

Baharan Kamousi

Suganya Karunakaran

The present disclosure provides systems and methods for seizure detection. The method for seizure detection may include receiving a plurality of electroencephalography (EEG) signals over a plurality of channels for a subject, preprocessing the plurality of EEG signals by segmenting the plurality of EEG signals for each channel into a plurality of temporal data segments, extracting a plurality of features from each temporal data segment for each channel, and applying a machine learning algorithm to the plurality of features to perform a seizure binary classification for each temporal data segment for each channel. A control policy may be employed to determine a seizure burden on the aggregated seizure binary classifications. When the seizure burden is equal to or exceeds a threshold, a notification may be generated. The notification may be usable by a healthcare practitioner to assess whether the subject may be at risk of having a seizure.

Systems and methods for seizure prediction and detection

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Santa Clara, CA, United States of America

Mehdi Hajinoroozi