Method and apparatus for detection of nervous system disorders
First Claim
1. A method of detecting a neurological event, the method comprising:
- acquiring an EEG signal comprising a stream of sampled data values;
transforming the stream of sampled data values into a stream of data magnitude values;
determining, with processing circuitry, a long-term representation of the EEG signal from the data magnitude values, comprising comparing a data magnitude value to a previous value of the long-term representation, and incrementing the previous value by a predetermined increment amount if the data magnitude value equals or exceeds the previous value, and decrementing the previous value by a predetermined decrement amount if the data magnitude value is less than the previous value;
deriving a magnitude threshold from the long-term representation;
comparing the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold;
calculating an event monitoring parameter based on a rolling window of comparator output values;
comparing the event monitoring parameter to an onset threshold; and
detecting a neurological event when the event monitoring parameter exceeds the onset threshold.
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Abstract
Systems and methods for detecting and/or treating nervous system disorders, such as seizures. 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.
86 Citations
32 Claims
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1. A method of detecting a neurological event, the method comprising:
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acquiring an EEG signal comprising a stream of sampled data values; transforming the stream of sampled data values into a stream of data magnitude values; determining, with processing circuitry, a long-term representation of the EEG signal from the data magnitude values, comprising comparing a data magnitude value to a previous value of the long-term representation, and incrementing the previous value by a predetermined increment amount if the data magnitude value equals or exceeds the previous value, and decrementing the previous value by a predetermined decrement amount if the data magnitude value is less than the previous value; deriving a magnitude threshold from the long-term representation; comparing the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold; calculating an event monitoring parameter based on a rolling window of comparator output values; comparing the event monitoring parameter to an onset threshold; and detecting a neurological event when the event monitoring parameter 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)
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25. A non-transitory 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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sample an EEG signal at a sample rate to form a stream of sampled data values; transform the stream of sampled data values into a stream of data magnitude values; determine, with the programmable processor, a long-term representation of the EEG signal from the data magnitude values, comprising comparing a data magnitude value to a previous value of the long-term representation, and incrementing the previous value by a predetermined increment amount if the data magnitude value equals or exceeds the previous value, and decrementing the previous value by a predetermined decrement amount if the data magnitude value is less than the previous value; derive a magnitude threshold from the long-term representation; compare the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold; calculate an event monitoring parameter based on a rolling window of comparator output values; compare the event monitoring parameter to an onset threshold; and detect a neurological event when the event monitoring parameter exceeds the onset threshold.
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26. A method of detecting a neurological event, the method comprising:
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acquiring an EEG signal comprising a stream of sampled data values; transforming the stream of sampled data values into a stream of data magnitude values; determining a long-term representation of the EEG signal from the data magnitude values; deriving a magnitude threshold from the long-term representation; comparing the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value consisting of a binary value indicating whether a given data magnitude value exceeds the magnitude threshold; calculating an event monitoring parameter with processing circuitry, consisting of summing the comparator output values within a rolling window; comparing the event monitoring parameter to an onset threshold; and detecting a neurological event when the event monitoring parameter exceeds the onset threshold. - View Dependent Claims (27, 28, 29, 30, 31)
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32. A method of detecting a neurological event, the method comprising:
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acquiring an EEG signal comprising a stream of sampled data values; transforming the stream of sampled data values into a stream of data magnitude values; determining, with processing circuitry, a long-term representation of the EEG signal from the data magnitude values, wherein determining the long-term representation comprises comparing a data magnitude value to a previous value of the long-term representation, and incrementing the previous value by a predetermined increment amount if the data magnitude value equals or exceeds the previous value, and decrementing the previous value by a predetermined decrement amount if the data magnitude value is less than the previous value; deriving a magnitude threshold from the long-term representation; comparing the data magnitude values to the magnitude threshold to produce a stream of comparator output values, each comparator output value indicating whether a given data magnitude value exceeds the magnitude threshold; calculating an event monitoring parameter based on a sum of comparator output values within a rolling window; comparing the event monitoring parameter to an onset threshold; and detecting a neurological event when the event monitoring parameter exceeds the onset threshold.
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Specification