Method and system for concentration detection
First Claim
1. A method for concentration detection, the method comprising the steps of:
- extracting temporal features from brain signals;
classifying the extracted temporal features using a classifier to give a score x1;
extracting spectral-spatial features from brain signals;
selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features;
classifying the selected spectral-spatial features using a classifier to give a score x2;
combining the scores x1 and x2 to give a single score; and
determining whether the subject is in a concentration state based on the single score;
wherein the step of extracting spectral-spatial features of brain signals further comprises the steps of;
extracting respective brain signal components in discrete frequency windows using filter banks to obtain spectral features of brain signals; and
applying a common spatial pattern (CSP) algorithm to each of the spectral features using a CSP array to obtain the spectral-spatial features of brain signals.
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Abstract
There is a method and a system for concentration detection. The method for concentration detection includes the steps of extracting temporal features from brain signals; classifying the extracted temporal features using a classifier to give a score x1; extracting spectral-spatial features from brain signals; selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; classifying the selected spectral-spatial features using a classifier to give a score x2; combining the scores x1 and x2 to give a single score; and determining if the subject is in a concentration state based on the single score.
31 Citations
19 Claims
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1. A method for concentration detection, the method comprising the steps of:
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extracting temporal features from brain signals; classifying the extracted temporal features using a classifier to give a score x1; extracting spectral-spatial features from brain signals; selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; classifying the selected spectral-spatial features using a classifier to give a score x2; combining the scores x1 and x2 to give a single score; and determining whether the subject is in a concentration state based on the single score; wherein the step of extracting spectral-spatial features of brain signals further comprises the steps of; extracting respective brain signal components in discrete frequency windows using filter banks to obtain spectral features of brain signals; and applying a common spatial pattern (CSP) algorithm to each of the spectral features using a CSP array to obtain the spectral-spatial features of brain signals. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A system for concentration detection, the system comprising:
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an input device for receiving brain signals; a temporal feature extracting unit for extracting temporal features from the brain signals; a temporal feature classifying unit for classifying the extracted temporal features using a classifier to give a score x1; a spectral-spatial feature extracting unit for extracting spectral-spatial features from the brain signals; a spectral-spatial feature selecting unit for selecting spectral-spatial features containing discriminative information between the concentration and non-concentration states from the set of extracted spectral-spatial features; a spectral-spatial feature classifying unit for classifying the selected spectral-spatial features using a classifier to give a score x2; and a processing unit, including a memory, coupled to said temporal feature classifying unit and said spectral-spatial feature classifying unit for combining the scores x1 and x2 to give a single score and for determining whether the subject is in a concentration state based on the single score; wherein the spectral-spatial feature extracting unit comprises; filter banks to extract respective brain signal components in discrete frequency windows to obtain spectral features of the brain signals; and a common spatial pattern (CSP) array to apply a CSP algorithm to each of the spectral features to obtain the spectral-spatial features of the brain signals. - View Dependent Claims (15)
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16. A non-transitory computer-readable medium having stored thereon computer code means comprising executable instruction for instructing a computer system to execute a method for concentration detection, the method comprising the steps of:
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extracting temporal features from brain signals; classifying the extracted temporal features using a classifier to give a score x1; extracting spectral-spatial features from brain signals; selecting spectral-spatial features containing discriminative information between the concentration and non-concentration states from the set of extracted spectral-spatial features; classifying the selected spectral-spatial features using a classifier to give a score x2; combining the scores x1 and x2 to give a single score; and determining whether the subject is in a concentration state based on the single score; wherein the step of extracting spectral-spatial features of brain signals further comprises the steps of; extracting respective brain signal components in discrete frequency windows using filter banks to obtain spectral features of brain signals; and applying a common spatial pattern (CSP) algorithm to each of the spectral features using a CSP array to obtain the spectral-spatial features of brain signals.
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17. A method for concentration detection, the method comprising the steps of:
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extracting features from brain signals; selecting features containing discriminative information between concentration and non-concentration states from the set of extracted features; classifying the selected features using a classifier to give a score; wherein subject dependant training data is used to generate parameters for a Common Spatial Pattern (CSP) algorithm for extracting the features from the brain signals, for selecting the features containing discriminative information between the concentration and non-concentration states from the set of extracted features and for classifying the selected features using a classifier; and determining whether the subject is in a concentration state based on the score, wherein the step of determining whether the subject is in a concentration state based on the score comprises determining that the subject is in a concentration state when the score is higher than a threshold and that the subject is not in a concentration state when the score is lower than a threshold.
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18. A system for concentration detection, the system comprising:
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an input device for receiving brain signals; a feature extracting unit for extracting features from the brain signals; a feature selecting unit for selecting features containing discriminative information between concentration and non-concentration states from the set of extracted features; a feature classifying unit for classifying the selected features using a classifier to give a score; wherein subject dependant training data is used to generate parameters for a common spatial pattern (CSP) algorithm for extracting the features from the brain signals, for selecting the features containing discriminative information between the concentration and non-concentration states from the set of extracted features and for classifying the selected features using a classifier; and a processing unit, including a memory, for determining whether the subject is in a concentration state based on the score, wherein determining whether the subject is in a concentration state based on the score comprises determining that the subject is in a concentration state when the score is higher than a threshold and that the subject is not in a concentration state when the score is lower than a threshold.
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19. A non-transitory computer-readable medium having stored thereon computer code means comprising executable instructions for instructing a computer system to execute a method for concentration detection, the method comprising the steps of:
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extracting features from brain signals; selecting features containing discriminative information between concentration and non-concentration states from the set of extracted features; classifying the selected features using a classifier to give a score; wherein subject dependant training data is used to generate parameters for a common spatial pattern (CSP) algorithm for extracting the features from the brain signals, for selecting the features containing discriminative information between the concentration and non-concentration states from the set of extracted features and for classifying the selected features using a classifier; and determining whether the subject is in a concentration state based on the score, wherein the step of determining whether the subject is in a concentration state based on the score comprises determining that the subject is in a concentration state when the score is higher than a threshold and that the subject is not in a concentration state when the score is lower than a threshold.
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Specification