Search All Applications in Brain Machine Interface
Application US20180049896
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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- 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 component; a monitor configured to monitor a response of the person to a stimulus and a characteristic of the stimulus; a 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 characteristic; a 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 intent; and wherein the processor is further configured to determine the behavioral intent of the person based on the feature vectors.
- 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 component; an eye tracking monitor configured to determine that the person is looking at a first stimulus; an auditory monitor configured to determine the presence of a second stimulus based on an auditory volume corresponding to the second stimulus; a 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 stimulus; wherein 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 intent; and 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.
- 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 component; detecting, by a monitor, an eye movement of the person and a volume of an auditory stimulus, wherein the eye movement corresponds to a visual stimulus; extracting, 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 intent; and 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.
