Patents by Inventor Brandi T. MARSH

Brandi T. MARSH 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: 20210282696
    Abstract: A reinforcement learning brain-machine interface (RL-BMI) can have a policy that governs how detected signals, emanating from a motor cortex of a subject's brain, are translated into action. The policy can be improved by detecting a motor signal having a characteristic and emanating from the motor cortex. The system can provide, to a device and based on (i) the motor signal and (ii) an instruction policy, a command signal resulting in a first action by a device. Additionally, an evaluation signal, emanating from the motor cortex in response to the first action, can also be detected. With the foregoing information, the system can adjust the policy based on the evaluation signal such that a subsequent motor signal, from the subject's brain, having the characteristic results in a second action, by the device, different from the first action, as needed.
    Type: Application
    Filed: November 16, 2020
    Publication date: September 16, 2021
    Inventors: Joseph T. FRANCIS, Venkata S. Aditya TARIGOPPULA, Brandi T. MARSH
  • Patent number: 10835146
    Abstract: A reinforcement learning brain-machine interface (RL-BMI) can have a policy that governs how detected signals, emanating from a motor cortex of a subject's brain, are translated into action. The policy can be improved by detecting a motor signal having a characteristic and emanating from the motor cortex. The system can provide, to a device and based on (i) the motor signal and (ii) an instruction policy, a command signal resulting in a first action by a device. Additionally, an evaluation signal, emanating from the motor cortex in response to the first action, can also be detected. With the foregoing information, the system can adjust the policy based on the evaluation signal such that a subsequent motor signal, from the subject's brain, having the characteristic results in a second action, by the device, different from the first action, as needed.
    Type: Grant
    Filed: December 11, 2015
    Date of Patent: November 17, 2020
    Assignee: THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK
    Inventors: Joseph T. Francis, Venkata S. Aditya Tarigoppula, Brandi T. Marsh
  • Publication number: 20190025917
    Abstract: A reinforcement learning brain-machine interface (RL-BMI) can have a policy that governs how detected signals, emanating from a motor cortex of a subject's brain, are translated into action. The policy can be improved by detecting a motor signal having a characteristic and emanating from the motor cortex. The system can provide, to a device and based on (i) the motor signal and (ii) an instruction policy, a command signal resulting in a first action by a device. Additionally, an evaluation signal, emanating from the motor cortex in response to the first action, can also be detected. With the foregoing information, the system can adjust the policy based on the evaluation signal such that a subsequent motor signal, from the subject's brain, having the characteristic results in a second action, by the device, different from the first action, as needed.
    Type: Application
    Filed: December 11, 2015
    Publication date: January 24, 2019
    Inventors: Joseph T. FRANCIS, Aditya TARIGOPPULA, Brandi T. MARSH