Patents by Inventor Syed Faraz Naqvi

Syed Faraz Naqvi 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).

  • Patent number: 11559232
    Abstract: Methods, systems and wearable devices for real-time mental stress assessment are provided. The methods and systems employ deep learning using a Gated Recurrent Unit (GRU) gating mechanism in a recurrent neural network with a sliding window approach applied to raw EEG data.
    Type: Grant
    Filed: February 27, 2022
    Date of Patent: January 24, 2023
    Assignee: KING ABDULAZIZ UNIVERSITY
    Inventors: Ubaid M. Al-Saggaf, Muhammad Moinuddin, Syed Saad Azhar Ali, Syed Faraz Naqvi, Sulhi Ali Alfakeh
  • Patent number: 11344248
    Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.
    Type: Grant
    Filed: September 20, 2021
    Date of Patent: May 31, 2022
    Assignee: King Abdulaziz University
    Inventors: Ubaid M. Al-Saggaf, Mohammed U. Alsaggaf, Muhammad Moinuddin, Syed Saad Azhar Ali, Syed Faraz Naqvi
  • Patent number: 11337639
    Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.
    Type: Grant
    Filed: September 20, 2021
    Date of Patent: May 24, 2022
    Assignee: King Abdulaziz University
    Inventors: Ubaid M. Al-Saggaf, Mohammed U. Alsaggaf, Muhammad Moinuddin, Syed Saad Azhar Ali, Syed Faraz Naqvi
  • Patent number: 11179089
    Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.
    Type: Grant
    Filed: May 19, 2021
    Date of Patent: November 23, 2021
    Assignee: King Abdulaziz University
    Inventors: Ubaid M. Al-Saggaf, Mohammed U. Alsaggaf, Muhammad Moinuddin, Syed Saad Azhar Ali, Syed Faraz Naqvi