Patents by Inventor Mehdi Hajinoroozi

Mehdi Hajinoroozi has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • SYSTEMS AND METHODS FOR SEIZURE PREDICTION AND DETECTION
    Publication number: 20210085235
    Abstract: 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.
    Type: Application
    Filed: July 8, 2020
    Publication date: March 25, 2021
    Inventors: Baharan Kamousi, Mehdi Hajinoroozi, Suganya Karunakaran, Alexander M. Grant, Jianchun Yi, Raymond Woo, Josef Parvizi, Xingjuan Chao
  • Systems and methods for seizure prediction and detection
    Patent number: 10743809
    Abstract: 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.
    Type: Grant
    Filed: September 20, 2019
    Date of Patent: August 18, 2020
    Assignee: CeriBell, Inc.
    Inventors: Baharan Kamousi, Mehdi Hajinoroozi, Suganya Karunakaran, Alexander Grant, Jianchun Yi, Raymond Woo, Josef Parvizi, Xingjuan Chao