Sensory-evoked potential (SEP) classification/detection in the time domain
First Claim
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1. A method for sensory-evoked potential signal classification, comprising:
- generating a pattern of stimulus characterized by a frequency that updates randomly;
determining in real-time the frequency of the pattern of stimulus, the determined frequency of the pattern of stimulus being the current frequency of the pattern of stimulus;
receiving a plurality of electroencephalography signal samples from a current user evoked in response to the pattern of stimulus;
synchronizing the plurality of electroencephalography signal samples in time domain without conversion to a frequency domain to the pattern of stimulus in time domain;
generating a stimulus-locked electroencephalography signal sample using a processor; and
performing a determination using a time domain classifier in real-time of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus using the processor,wherein the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus being performed dynamically or adaptively in real-time in a manner such that the current user'"'"'s electroencephalography pattern determined in real-time is used, the current user'"'"'s electroencephalography response pattern determined before the current user'"'"'s current electroencephalography response pattern is not used, the frequency of the pattern of stimulus determined in real-time is used, and a frequency of the pattern of stimulus determined before the current determined frequency of the pattern of stimulus is not used in the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus; and
wherein the sensory-evoked potential signal classification is computed by calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample, determining a statistical measure of the mutual relationship for each stimulus, and determining if a stimulus is being attended to by the current user according to the statistical measure of the mutual relationship for each stimulus user the time domain classifier.
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Abstract
Techniques are disclosed for sensory-evoked potential (SEPs, e.g., visual-evoked potentials) signal detection/classification by synchronizing EEG to the repeated presentation of sensory stimuli in the time domain. In some embodiments, a system receives a plurality of EEG signal samples, generates a stimulus-locked EEG and determines whether the plurality of EEG signal samples are evoked in response to a pattern of stimulus. In some embodiments, no prior knowledge about the update pattern (such as the flashing frequency of a visual stimulus) of the stimulus and no prior knowledge about an individual user'"'"'s EEG pattern are required.
72 Citations
16 Claims
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1. A method for sensory-evoked potential signal classification, comprising:
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generating a pattern of stimulus characterized by a frequency that updates randomly; determining in real-time the frequency of the pattern of stimulus, the determined frequency of the pattern of stimulus being the current frequency of the pattern of stimulus; receiving a plurality of electroencephalography signal samples from a current user evoked in response to the pattern of stimulus; synchronizing the plurality of electroencephalography signal samples in time domain without conversion to a frequency domain to the pattern of stimulus in time domain; generating a stimulus-locked electroencephalography signal sample using a processor; and performing a determination using a time domain classifier in real-time of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus using the processor, wherein the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus being performed dynamically or adaptively in real-time in a manner such that the current user'"'"'s electroencephalography pattern determined in real-time is used, the current user'"'"'s electroencephalography response pattern determined before the current user'"'"'s current electroencephalography response pattern is not used, the frequency of the pattern of stimulus determined in real-time is used, and a frequency of the pattern of stimulus determined before the current determined frequency of the pattern of stimulus is not used in the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus; and wherein the sensory-evoked potential signal classification is computed by calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample, determining a statistical measure of the mutual relationship for each stimulus, and determining if a stimulus is being attended to by the current user according to the statistical measure of the mutual relationship for each stimulus user the time domain classifier. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system for sensory-evoked potential signal classification, comprising:
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a processor configured to; generate a pattern of stimulus characterized by a frequency that updates randomly; determine in real-time the frequency of the pattern of stimulus, the determined frequency of the pattern of stimulus being the current determined frequency of the pattern of stimulus; receive a plurality of electroencephalography signal samples from a current user evoked in response to the pattern of stimulus; synchronize the plurality of electroencephalography signal samples in time domain without conversion to a frequency domain to the pattern of stimulus in time domain; generate a stimulus-locked electroencephalography signal sample; and perform a determination using a time domain classifier in real-time of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus, wherein the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus being performed dynamically or adaptively in real-time in a manner such that the current user'"'"'s electroencephalography pattern determined in real-time is used, the current user'"'"'s electroencephalography response pattern determined before the current user'"'"'s current electroencephalography response pattern is not used, the frequency of the pattern of stimulus determined in real-time is used, and a frequency of the pattern of stimulus determined before the current determined frequency of the pattern of stimulus is not used in the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus; and wherein the sensory-evoked potential signal classification is computed by calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample, determine a statistical measure of the mutual relationship for each stimulus, and determine if a stimulus is being attended to by the current user according to the statistical measure of the mutual relationship for each stimulus user the time domain classifier; and a memory coupled to the processor and configured to provide the processor with instructions. - View Dependent Claims (14)
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15. A computer program product for sensory-evoked potential signal classification, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:
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generating a pattern of stimulus characterized by a frequency that updates randomly; determining the frequency of the pattern of stimulus determined in real-time, the determined frequency of the pattern of stimulus being the current determined frequency of the pattern of stimulus; receiving a plurality of electroencephalography signal samples from a current user evoked in response to the pattern of stimulus; synchronizing the plurality of electroencephalography signal samples in time domain without conversion to a frequency domain to the pattern of stimulus in time domain; generating a stimulus-locked electroencephalography signal sample using a processor; and performing a determination using a time domain classifier in real-time of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus using the processor, wherein the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus being performed dynamically or adaptively in real-time in a manner such that the current user'"'"'s electroencephalography pattern determined in real-time is used, the current user'"'"'s electroencephalography response pattern determined before the current user'"'"'s current electroencephalography response pattern is not used, the frequency of the pattern of stimulus determined in real-time is used, and a frequency of the pattern of stimulus determined before the current determined frequency of the pattern of stimulus is not used in the determination of whether the plurality of electroencephalography signal samples are evoked in response to the pattern of stimulus; and wherein the sensory-evoked potential signal classification is computed by calculating a mutual relationship between pairs of segments for the stimulus-locked electroencephalography signal sample, determining a statistical measure of the mutual relationship for each stimulus, and determining if a stimulus is being attended to by the current user according to the statistical measure of the mutual relationship for each stimulus user the time domain classifier. - View Dependent Claims (16)
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Specification