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Brain Machine Interface

Search All Patents in Brain Machine Interface


Application 20180049896


Published 2018-02-22

System And Method For Noninvasive Identification Of Cognitive And Behavioral Goals

A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person is disclosed. The system includes an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person. The electromagnetic signals include a time component and a frequency component. A monitor monitors a response of the person to a stimulus and a characteristic of the stimulus. A synchronization module synchronizes the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response and the characteristic. A processor processes the set of electromagnetic signals and extracts feature vectors. The feature vectors define a class of behavioral intent. The processor determines the behavioral intent of the person based on the feature vectors. A brain machine interface and a method for identifying a behavioral intent of a person is also disclosed.


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3 Independent Claims

  • Independent Claim 1. A brain machine interface system for use with an electroencephalogram to identify a behavioral intent of a person, the system comprising: an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person, wherein the electromagnetic signals comprise a time component and a frequency componenta monitor configured to monitor a response of the person to a stimulus and a characteristic of the stimulusa synchronization module configured to synchronize the sensed electromagnetic signals with the response and the characteristic to determine a set of electromagnetic signals corresponding to the monitored response of the person and the characteristica processor configured to process the set of electromagnetic signals and to extract feature vectors, wherein each of the feature vectors define a class of behavioral intentand wherein the processor is further configured to determine the behavioral intent of the person based on the feature vectors.

  • Independent Claim 8. A brain machine interface comprising: an electroencephalogram configured to sense electromagnetic signals generated by a brain of a person, wherein the electromagnetic signals comprise a time component and a frequency componentan eye tracking monitor configured to determine that the person is looking at a first stimulusan auditory monitor configured to determine the presence of a second stimulus based on an auditory volume corresponding to the second stimulusa processor configured to segment the electromagnetic signals into a first segment and a second segment, wherein the first segment corresponds to the first stimulus and the second segment corresponds to the second stimuluswherein the processor is further configured to process the first segment and the second segment and wherein the processor is configured to: extract a first set of feature vectors from the first segment and a second set of feature vectors from the second segment, wherein each of the first set and the second set of feature vectors define a class of behavioral intentand determine a first behavioral intent based on the first set of feature vectors and a second behavioral intent based on the second set of feature vectors.

  • Independent Claim 15. A method for identifying a behavioral intent of a person, the method comprising: sensing, by an electroencephalogram attached to a person, electromagnetic signals generated by a brain of the person, wherein the electromagnetic signals comprise a time component and a frequency componentdetecting, by a monitor, an eye movement of the person and a volume of an auditory stimulus, wherein the eye movement corresponds to a visual stimulusextracting, by a processor, a first set of feature vectors corresponding to the visual stimulus and a second set of feature vectors corresponding to the auditory stimulus, wherein each of the feature vectors define a class of behavioral intentand determining, by the processor, a behavioral intent of the person based on the first set of feature vectors and the second set of feature vectors.