Selection of neurostimulator parameter configurations using decision trees
First Claim
1. A method comprising:
- selecting a first parameter configuration for a neurostimulator;
receiving an indication of observed efficacy of the first parameter configuration;
selecting a branch of a decision tree based on the indication of observed efficacy and a position of the first parameter configuration within the decision tree, wherein the decision tree comprises a plurality of nodes and branches and defines a hierarchy of possible parameter configurations for a neurostimulator, wherein each node defines an alternative parameter configuration from each of the other nodes, and each branch links one of the nodes to another of the nodes; and
selecting a second parameter configuration for the neurostimulator based on the selected branch of the decision tree.
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Abstract
A selection of parameter configurations for a neurostimulator using decision trees may be employed by a programming device to allow a clinician or other user to select parameter configurations, and then program an implantable neurostimulator to deliver therapy using the selected parameter configurations. The programming device executes a parameter configuration search algorithm to guide the clinician in selection of parameter configurations. The search algorithm relies on a decision tree to identify optimum parameter configurations. A decision tree is useful in classifying observations in a data set based upon one or more attributes or fields within the data. The data set includes parameter configurations matched with observed ratings of efficacy on patients of a similar indication. The learned attribute, on which classification occurs, will be the optimum parameter configuration for a set of rated configurations used to produce the classification. The decision trees may be especially useful in identifying electrode configurations.
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Citations
18 Claims
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1. A method comprising:
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selecting a first parameter configuration for a neurostimulator; receiving an indication of observed efficacy of the first parameter configuration; selecting a branch of a decision tree based on the indication of observed efficacy and a position of the first parameter configuration within the decision tree, wherein the decision tree comprises a plurality of nodes and branches and defines a hierarchy of possible parameter configurations for a neurostimulator, wherein each node defines an alternative parameter configuration from each of the other nodes, and each branch links one of the nodes to another of the nodes; and selecting a second parameter configuration for the neurostimulator based on the selected branch of the decision tree. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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Specification