Patents by Inventor Sean Wood

Sean Wood 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).

  • Publication number: 20240150318
    Abstract: Provided herein are compounds of Formula (I), their pharmaceutically acceptable salts, and their pharmaceutical compositions: wherein R1, R2, R3a, R3b, R4, R5, and A are defined in the present disclosure. The compounds are potent inhibitors of the main protease (Mpro) of severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2), and they are useful in treating or preventing COVID-19 in a subject.
    Type: Application
    Filed: June 12, 2023
    Publication date: May 9, 2024
    Inventors: Arnab K. Chatterjee, Jian Jeffrey Chen, Elshan Nakath, Alireza Rahimi, Anil Kumar Gupta, Gennadii Grabovyi, Katy Wilson, Sourav Ghorai, Armen Nazarian, James Pedroarena, Wrickban Mazumdar, Frank Weiss, Lirui Song, Malina A. Bakowski, Laura Riva, Karen Wolff, Case W. McNamara, Thomas F. Rogers, Jacqueline Malvin, Shuangwei Li, Sean Joseph, Ashley Woods, Yuyin Liu, Neechi Okwor
  • Publication number: 20230309887
    Abstract: Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.
    Type: Application
    Filed: May 24, 2023
    Publication date: October 5, 2023
    Inventors: Christopher AIMONE, Graeme MOFFAT, Hubert JACOB BANVILLE, Sean WOOD, Subash PADMANABAN, Sam KERR, Aravind RAVI
  • Patent number: 11696714
    Abstract: Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.
    Type: Grant
    Filed: April 24, 2020
    Date of Patent: July 11, 2023
    Assignee: INTERAXON INC.
    Inventors: Christopher Allen Aimone, Graeme Moffat, Hubert Jacob Banville, Sean Wood, Subash Padmanaban, Sam Kerr, Aravind Ravi
  • Publication number: 20200337625
    Abstract: Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.
    Type: Application
    Filed: April 24, 2020
    Publication date: October 29, 2020
    Inventors: Christopher Allen Aimone, Graeme Moffat, Hubert JACOB BANVILLE, Sean Wood, Subash PADMANABAN, Sam KERR, Aravind RAVI