Patents by Inventor Christopher Keane

Christopher Keane 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: 20220061736
    Abstract: Methods, systems, and techniques for providing neurofeedback and for training brain wave function are provided. Example embodiments provide a Brain Training Feedback System (“BTFS”), which enables participants involved in brain training activities to learn to evoke/increase or suppress/inhibit certain brain wave activity based upon the desired task at hand. In one embodiment, the BTFS provides a brain/computer interaction feedback loop which monitors and measures EEG signals (brain activity) received from participant and provides feedback to participant. The BTFS may use an FFT based system or machine learning engines to deconstruct and classify brain wave signals. The machine learning based BTFS enable optimized feedback and rewards, adaptive feedback, and an ability to trigger interventions to assist in desired brain transitions.
    Type: Application
    Filed: July 2, 2021
    Publication date: March 3, 2022
    Inventor: Christopher Keane
  • Patent number: 11051748
    Abstract: Methods, systems, and techniques for providing neurofeedback and for training brain wave function are provided. Example embodiments provide a Brain Training Feedback System (“BTFS”), which enables participants involved in brain training activities to learn to evoke/increase or suppress/inhibit certain brain wave activity based upon the desired task at hand. In one embodiment, the BTFS provides a brain/computer interaction feedback loop which monitors and measures EEG signals (brain activity) received from participant and provides feedback to participant. The BTFS may use an FFT based system or machine learning engines to deconstruct and classify brain wave signals. The machine learning based BTFS enable optimized feedback and rewards, adaptive feedback, and an ability to trigger interventions to assist in desired brain transitions.
    Type: Grant
    Filed: July 24, 2018
    Date of Patent: July 6, 2021
    Assignee: 40 YEARS, INC.
    Inventor: Christopher Keane
  • Publication number: 20200077941
    Abstract: Methods, systems, and techniques for providing neurofeedback and for training brain wave function are provided. Example embodiments provide a Brain Training Feedback System (“BTFS”), which enables participants involved in brain training activities to learn to evoke/increase or suppress/inhibit certain brain wave activity based upon the desired task at hand. In one embodiment, the BTFS provides a brain/computer interaction feedback loop which monitors and measures EEG signals (brain activity) received from participant and provides feedback to participant. The BTFS may use an FFT based system or machine learning engines to deconstruct and classify brain wave signals. The machine learning based BTFS enable optimized feedback and rewards, adaptive feedback, and an ability to trigger interventions to assist in desired brain transitions.
    Type: Application
    Filed: July 27, 2018
    Publication date: March 12, 2020
    Inventor: Christopher Keane
  • Publication number: 20200069209
    Abstract: Methods, systems, and techniques for providing neurofeedback and for training brain wave function are provided. Example embodiments provide a Brain Training Feedback System (“BTFS”), which enables participants involved in brain training activities to learn to evoke/increase or suppress/inhibit certain brain wave activity based upon the desired task at hand. In one embodiment, the BTFS provides a brain/computer interaction feedback loop which monitors and measures EEG signals (brain activity) received from participant and provides feedback to participant. The BTFS may use an FFT based system or machine learning engines to deconstruct and classify brain wave signals. The machine learning based BTFS enable optimized feedback and rewards, adaptive feedback, and an ability to trigger interventions to assist in desired brain transitions. In addition, synchrony only based training is supported with the use of surround sound.
    Type: Application
    Filed: July 26, 2018
    Publication date: March 5, 2020
    Inventor: Christopher Keane
  • Publication number: 20200073475
    Abstract: Methods, systems, and techniques for providing neurofeedback and for training brain wave function are provided. Example embodiments provide a Brain Training Feedback System (“BTFS”), which enables participants involved in brain training activities to learn to evoke/increase or suppress/inhibit certain brain wave activity based upon the desired task at hand. In one embodiment, the BTFS provides a brain/computer interaction feedback loop which monitors and measures EEG signals (brain activity) received from participant and provides feedback to participant. The BTFS may use an FFT based system or machine learning engines to deconstruct and classify brain wave signals. The machine learning based BTFS enable optimized feedback and rewards, adaptive feedback, and an ability to trigger interventions to assist in desired brain transitions.
    Type: Application
    Filed: July 25, 2018
    Publication date: March 5, 2020
    Inventor: Christopher Keane
  • Publication number: 20200069208
    Abstract: Methods, systems, and techniques for providing neurofeedback and for training brain wave function are provided. Example embodiments provide a Brain Training Feedback System (“BTFS”), which enables participants involved in brain training activities to learn to evoke/increase or suppress/inhibit certain brain wave activity based upon the desired task at hand. In one embodiment, the BTFS provides a brain/computer interaction feedback loop which monitors and measures EEG signals (brain activity) received from participant and provides feedback to participant. The BTFS may use an FFT based system or machine learning engines to deconstruct and classify brain wave signals. The machine learning based BTFS enable optimized feedback and rewards, adaptive feedback, and an ability to trigger interventions to assist in desired brain transitions.
    Type: Application
    Filed: July 24, 2018
    Publication date: March 5, 2020
    Inventor: Christopher Keane