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 features extracted from a reference seizure to form at least one similarity measure;
deriving a discriminant measure, the discriminant measure being a function of the at least one similarity measure and the EEG and CV features;
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.
181 Citations
39 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 features extracted from a reference seizure to form at least one similarity measure;
deriving a discriminant measure, the discriminant measure being a function of the at least one similarity measure and the EEG and CV features;
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, 34)
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35. A computer-readable medium programmed with instructions for performing a method of predicting a seizure event, the medium comprising instructions for causing a programmable processor to:
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acquire an electroencephalograph (EEG) signal;
extract one or more EEG features from the EEG signal;
acquire a cardiovascular (CV) signal;
extract one or more CV features from the CV signal;
derive a discriminant measure from the EEG and CV features, including comparing at least one of the EEG and CV features to features extracted from a reference seizure to form at least one similarity measure, the discriminant measure being a logical function of the at least one similarity measure and the EEG and CV features. compare the discriminant measure to a predetermined threshold; and
predict a seizure event when the discriminant measure exceeds the predetermined threshold. - View Dependent Claims (36, 37, 38)
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39. A system for predicting a seizure event, comprising:
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means for acquiring electroencephalograph (EEG) signals;
means for acquiring cardiovascular (CV) signals; and
an implantable medical device (IMD) having a power supply, housing, memory, and a processor, the processor being adapted to receive EEG signals and extract one or more EEG features;
receive CV signals and extract one or more CV features;
derive a discriminant measure from the EEG and CV features, including comparing at least one of the EEG and CV features to features extracted from a reference seizure to form at least one similarity measure, the discriminant measure being a logical function of the at least one similarity measure and the EEG and CV features; and
predict a seizure event when the discriminant measure exceeds a predetermined threshold.
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Specification