Method and apparatus for extraction of low-frequency artifacts from brain waves for alertness detection
First Claim
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1. A method for automatically extracting low-frequency artifact data from brain wave data comprising the steps of:
- (a) utilizing a standard method selected from the group of methods consisting of electroencephalogram method and magnetoencephalogram method to provide at least one channel of raw brain wave data, called e-data, selected from the group consisting of electroencephalogram data and magnetoencephalogram data; and
(b) separating artifact data, called f-data, from the e-data while preventing phase distortions in the data, by passing the e-data through a zero-phase filter means for providing an output of f-data, whereby the f-data may be further analyzed to detect alertness.
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Abstract
Methods and apparatus automatically detect alertness in humans by monitoring and analyzing brain wave signals. Steps include: acquiring the brain wave (EEG or MEG) data from the subject, digitizing the data, separating artifact data from raw data, and comparing trends in f-data to alertness indicators, providing notification of inadequate alertness.
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Citations
14 Claims
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1. A method for automatically extracting low-frequency artifact data from brain wave data comprising the steps of:
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(a) utilizing a standard method selected from the group of methods consisting of electroencephalogram method and magnetoencephalogram method to provide at least one channel of raw brain wave data, called e-data, selected from the group consisting of electroencephalogram data and magnetoencephalogram data; and (b) separating artifact data, called f-data, from the e-data while preventing phase distortions in the data, by passing the e-data through a zero-phase filter means for providing an output of f-data, whereby the f-data may be further analyzed to detect alertness. - View Dependent Claims (2, 3)
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4. Apparatus for automatically extracting low-frequency artifact data from brain wave data comprising:
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(a) data provision means selected from the group of means consisting of electroencephalogram means and magnetoencephalogram means for providing at least one channel of raw brain wave data, called e-data, selected from the group consisting of electroencephalogram data and magnetoencephalogram data; and (b) separation means for separating artifact data, called f-data, from the e-data while preventing phase distortions in the data, said separation means comprising a zero-phase filter means for providing an output of f-data, said separation means communicably connected to said data provision means, whereby the f-data may be further analyzed to detect alertness. - View Dependent Claims (5, 6)
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- 7. A zero-phase filter for separating artifact brain wave data, called f-data, from raw brain wave data, called e-data, selected from the group consisting of electroencephalogram data and magnetoencephalogram data, said zero-phase filter comprising an integrated circuit chip zero-phase filter for separating artifact brain wave data from raw brain wave data while preventing phase distortions in the data.
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9. A method for automatically detecting a subject'"'"'s state of alertness from the subject'"'"'s brain wave data comprising the steps of:
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(A) utilizing a standard method selected from the group of methods consisting of electroencephalogram method and magnetoencephalogram method to provide at least one channel of raw brain wave data, called e-data, selected from the group consisting of electroencephalogram data and magnetoencephalogram data; (B) separating artifact data, called f-data, from the e-data while preventing phase distortions in the data, by passing the e-data through a zero-phase filter means for providing an output of f-data; (C) analyzing the f-data to detect indications of fatigue or drowsiness, thereby detecting a lack of alertness; and (D) providing an indication of the lack of alertness. - View Dependent Claims (10, 11)
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12. Apparatus for automatically detecting a subject'"'"'s state of alertness from the subject'"'"'s brain wave data comprising:
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(A) data provision means selected from the group of means consisting of electroencephalogram means and magnetoencelaphogram means for providing at least one channel of raw brain wave data, called e-data, selected from the group consisting of electroencephalogram data and magnetoencephalogram data; (B) separation means for separating artifact data, called f-data, from the e-data while preventing phase distortions in the data, said separation means comprising a zero-phase filter means for providing an output of f-data, said separation means communicably connected to said data provision means; (C) analysis means for analyzing the f-data to detect indications of fatigue or drowsiness, thereby detecting a lack of alertness, said analysis means communicably connected to said separation means; and (D) indication means for providing an indication of the lack of alertness, said indicator means communicably connected to said analysis means. - View Dependent Claims (13, 14)
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Specification