Methods and Systems for Characterizing and Generating a Patient-Specific Seizure Advisory System
First Claim
1. A method of developing a brain state advisory system comprising:
- deriving a brain state advisory algorithm;
applying the brain state advisory algorithm to patient EEG data to identify occurrences of the target patient brain state in the patient EEG data;
determining if a performance measure of the advisory algorithm for the target brain state exceeds the performance measure of a chance predictor for the target brain state; and
if the performance measure of the advisory algorithm for the target brain state exceeds the performance measure of a chance predictor for the target brain state, storing the advisory algorithm in memory of the brain state advisory system.
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Abstract
A method of developing a brain state advisory system including the following steps: deriving a brain state advisory algorithm; applying the brain state advisory algorithm to patient EEG data to identify occurrences of the target patient brain state (such as, e.g., a pro-ictal state or a contra-ictal state) in the patient EEG data; determining if a performance measure of the advisory algorithm for the target brain state exceeds the performance measure of a chance predictor for the target brain state; and if the performance measure of the advisory algorithm for the target brain state exceeds the performance measure of a chance predictor for the target brain state, storing the advisory algorithm in memory of the brain state advisory system. The invention also includes seizure advisory systems.
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Citations
61 Claims
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1. A method of developing a brain state advisory system comprising:
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deriving a brain state advisory algorithm; applying the brain state advisory algorithm to patient EEG data to identify occurrences of the target patient brain state in the patient EEG data; determining if a performance measure of the advisory algorithm for the target brain state exceeds the performance measure of a chance predictor for the target brain state; and if the performance measure of the advisory algorithm for the target brain state exceeds the performance measure of a chance predictor for the target brain state, storing the advisory algorithm in memory of the brain state advisory system. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of monitoring a patient brain state comprising:
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obtaining EEG data from the patient; analyzing the EEG data with a stored brain state advisory algorithm having a performance measure for identification of a target brain state exceeding the performance measure of a chance predictor for the target brain state; and providing an indication of the target brain state. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A seizure advisory system comprising:
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a seizure advisory algorithm stored in memory, the seizure advisory algorithm having a performance measure for identifying a target brain state greater than the performance measure of a chance predictor for the target brain state; patient EEG data input; a microprocessor programmed to apply the algorithm to EEG data from the patient EEG data input to compute patient brain state; and a patient brain state indicator controlled by the microprocessor to indicate patient brain state. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25)
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26. A method of developing a brain state advisory system comprising:
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deriving a brain state advisory algorithm, the deriving step comprising analyzing patient EEG data, identifying all pro-ictal states within the EEG data, and generating pro-ictal state alerts; and placing the advisory algorithm in memory of the brain state advisory system. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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37. A method of monitoring a patient brain state comprising:
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obtaining EEG data from the patient; analyzing the EEG data with a stored brain state advisory algorithm; and providing an indication of a pro-ictal brain state for a predetermined period of time after identification of the pro-ictal brain state. - View Dependent Claims (38, 39)
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40. A seizure advisory system comprising:
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a seizure advisory algorithm stored in memory; patient EEG data input; a microprocessor programmed to apply the algorithm to EEG data from the patient EEG data input to identify and indicate patient brain state; and a patient brain state indicator controlled by the microprocessor to indicate patient brain state for a predetermined period of time after identification of a pro-ictal brain state. - View Dependent Claims (41, 42)
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43. A method of developing a brain state advisory system comprising:
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deriving a brain state advisory algorithm, the deriving step comprising analyzing patient EEG data, identifying pro-ictal states within the EEG data, and generating pro-ictal state alerts; adjusting a pro-ictal state identification sensitivity of the algorithm; and storing the advisory algorithm in memory of the brain state advisory system. - View Dependent Claims (44, 45, 46, 47, 48, 49)
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50. A method of tailoring a seizure advisory system to a patient, the method comprising:
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correlating a first performance measure of the seizure advisory algorithm to a seizure behavior of a subject; modifying an aspect of the seizure advisory algorithm to improve a second performance measure of the seizure prediction system; and storing the algorithm in memory in the seizure advisory system. - View Dependent Claims (51, 52, 53, 54, 55, 56, 57, 58, 59, 60)
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61. A method of improving performance of a seizure advisory system, the seizure advisory system comprising a seizure advisory algorithm, the method comprising:
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applying the seizure advisory algorithm to a dataset to generate alerts; extracting information related to alert duration during a time interval of the dataset; modifying at least one parameter of the seizure advisory algorithm to improve performance of the seizure advisory system; and placing the seizure advisory algorithm in memory of the seizure advisory system.
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Specification