METHOD AND APPARATUS FOR DETECTION OF NERVOUS SYSTEM DISORDERS
First Claim
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1. A method of detecting a neurological event, comprising:
- acquiring EEG signal data comprising a stream of data values;
determining a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the short-term representation being determined by applying the data values to a first filter, the first filter adapted to produce an intermediate output value for each block of N data values, and applying a rolling window of M intermediate output values to a second filter, the second filter adapted to produce the short-term representation;
determining a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;
calculating a ratio of the short-term representation to the long-term representation;
comparing the ratio to an onset threshold; and
detecting a neurological event when the ratio exceeds the onset 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. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.
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Citations
60 Claims
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1. A method of detecting a neurological event, comprising:
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acquiring EEG signal data comprising a stream of data values;
determining a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the short-term representation being determined by applying the data values to a first filter, the first filter adapted to produce an intermediate output value for each block of N data values, and applying a rolling window of M intermediate output values to a second filter, the second filter adapted to produce the short-term representation;
determining a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;
calculating a ratio of the short-term representation to the long-term representation;
comparing the ratio to an onset threshold; and
detecting a neurological event when the ratio exceeds the onset 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, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48)
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49. A computer-readable medium programmed with instructions for performing a method of detecting a neurological event, the medium comprising instructions for causing a programmable processor to:
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acquire EEG signal data comprising a stream of data values;
determine a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the short-term representation being determined by applying the data values to a first filter, the first filter adapted to produce an intermediate output value for each block of N data values, and applying a rolling window of M intermediate output values to a second filter, the second filter adapted to produce the short-term representation;
determine a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;
calculate a ratio of the short-term representation to the long-term representation;
compare the ratio to an onset threshold; and
detect a neurological event when the ratio exceeds the onset threshold. - View Dependent Claims (50, 51)
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52. An implantable medical device system for detecting a neurological event, the system comprising:
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an implantable medical device (IMD); and
at least one electrode adapted to sense EEG signals from a brain of a patient and communicate the EEG signals to the device, wherein the device is adapted to acquire EEG signal data comprising a stream of data values;
determine a short-term representation of the EEG signal data based on data values acquired over a first sample interval, the short-term representation being determined by applying the data values to a first filter, the first filter adapted to produce an intermediate output value for each block of N data values, and applying a rolling window of M intermediate output values to a second filter, the second filter adapted to produce the short-term representation;
determine a long-term representation of the EEG signal data based on data values acquired over a second sample interval, the second sample interval being longer than the first sample interval;
calculate a ratio of the short-term representation to the long-term representation;
compare the ratio to an onset threshold; and
detect a neurological event when the ratio exceeds the onset threshold. - View Dependent Claims (53, 54, 55, 56, 57, 58, 59, 60)
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Specification