Abstract: The systems and methods can automatically determine a patient-specific set of stimulation parameters using optimization for exploring and/or programming a neurostimulation device, e.g., deep brain stimulation (DBS). In one implementation, the method may include receiving patient data and set of stimulation parameters associated stimulation delivered to a patient by a neurostimulation device. The method may include determining one or more objective metrics using the patient data for each set of stimulation parameters. The one or more objective metrics may be a quantitative value that represents a rating or score of tremor severity and/or side effect severity. The method may further include generating a patient specific response model using the one or more objective metrics and the associated set of stimulation parameters. The method may also include applying an optimization algorithm to the generated response model to determine a candidate set of one or more stimulation parameters.

Abstract: The disclosures relates to systems and methods for automatically determining a patient-specific set of stimulation parameters using optimization for exploring and/or programming a neurostimulation device, e.g., deep brain stimulation (DBS). In one implementation, the method may include receiving patient data and set of stimulation parameters associated stimulation delivered to a patient by a neurostimulation device. The method may include determining one or more objective metrics using the patient data for each set of stimulation parameters. The one or more objective metrics may be a quantitative value that represents a rating or score of tremor severity and/or ide effect severity associated. The method may further include generating a patient specific response model using the one or more objective metrics and the associated set of stimulation parameters.

Abstract: In some embodiments, the systems and methods of the disclosure can efficiently and accurately classify neurodegenerative disorder(s) and/or movement disorder(s) of a subject (e.g., a patient) using at least quantitative features associated with one or more regions of interest determined from one or more sets of image data of the subjects brain. The method may include processing one or more sets of MRI image data of the subjects brain to extract one or more quantitative features for one or more regions. The one or more quantitative features may include a first quantitative and a second quantitative feature. The method may further include classifying at least the one or more quantitative features into one or more classes associated with neurodegenerative dementia disorder, neurodegenerative movement disorder, non-neurodegenerative movement disorder and/or heathy control. The method may include generating a report including a classification of at least the one or more quantitative features.

Abstract: A Brain Machine Interface (BMI) agent (110) is provided, that when operatively coupled to a subject during a mental task by the subject to control a prosthetic device (130), monitors one or more states (125) of neural activity of the subject, receives feedback associated with a behavior of the prosthetic device responsive to the control, learns a functional mapping between the mental task and the behavior in view of the feedback, and applies at least one control action (115) to the prosthetic device in accordance with the learning to control the prosthetic device for a targeted behavior.

Abstract: A Brain Machine Interface (BMI) agent (110) is provided, that when operatively coupled to a subject during a mental task by the subject to control a prosthetic device (130), monitors one or more states (125) of neural activity of the subject, receives feedback associated with a behavior of the prosthetic device responsive to the control, learns a functional mapping between the mental task and the behavior in view of the feedback, and applies at least one control action (115) to the prosthetic device in accordance with the learning to control the prosthetic device for a targeted behavior.