Method and apparatus for detection of nervous system disorders
First Claim
1. A method of predicting a seizure event, the method comprising:
- acquiring an electroencephalograph (EEG) signal and extracting one or more EEG features;
acquiring a cardiovascular (CV) signal and extracting one or more CV features;
comparing at least one of the EEG and CV features to one or more features extracted from a reference seizure to form at least one similarity measure;
comparing at least one of the EEG and CV features to one or more features extracted from a reference baseline to form at least one dissimilarity measure;
deriving a discriminant measure, the discriminant measure being a function of the at least one similarity measure and the at least one dissimilarity measure;
comparing the discriminant measure to a predetermined threshold; and
predicting a seizure event when the discriminant measure exceeds the predetermined threshold.
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Abstract
Systems and methods for detecting and/or treating nervous system disorders, such as seizures, are disclosed. Certain embodiments of the invention relate generally to implantable medical devices (IMDs) adapted to detect and treat nervous system disorders in patients with an IMD. Certain embodiments of the invention include detection of seizures based upon comparisons of long-term and short-term representations of physiological signals. Other embodiments include prediction of seizure activity based upon analysis of physiological signal levels. An embodiment of the invention monitors the quality of physiological signals, and may be able to compensate for signals of low signal quality. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.
102 Citations
33 Claims
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1. A method of predicting a seizure event, the method comprising:
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acquiring an electroencephalograph (EEG) signal and extracting one or more EEG features; acquiring a cardiovascular (CV) signal and extracting one or more CV features; comparing at least one of the EEG and CV features to one or more features extracted from a reference seizure to form at least one similarity measure; comparing at least one of the EEG and CV features to one or more features extracted from a reference baseline to form at least one dissimilarity measure; deriving a discriminant measure, the discriminant measure being a function of the at least one similarity measure and the at least one dissimilarity measure; comparing the discriminant measure to a predetermined threshold; and predicting a seizure event when the discriminant measure exceeds the predetermined threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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Specification