Systems and methods for closed-loop determination of stimulation parameter settings for an electrical simulation system
First Claim
1. A computing system for facilitating programming settings of an implantable pulse generator associated with a patient, comprising:
- a processor;
a memory; and
pulse generator feedback control logic, stored in the memory, and configured, when executed by the processor, to interface with control instructions of the implantable pulse generator (IPG) by performing actions of;
incorporating one or more machine learning engines, automatically generating a proposed set of stimulation parameter values that each effect a stimulation aspect of the IPG;
forwarding the automatically generated proposed set of stimulation parameter values to configure stimulation parameters of the IPG to the proposed set of stimulation parameter values;
receiving one or more clinical response values as a result of the IPG being configured to the proposed set of stimulation parameter values;
predicting, by incorporating one or more machine learning engines and using the one or more clinical response values, one or more therapeutic response values for each of a plurality of sets of untested stimulation parameter values;
selecting, based on the predicted one or more therapeutic response values and on a distance of each set of untested stimulation parameter values from one or more previously tested stimulation parameter values, a revised proposed set of stimulation parameter values from the plurality of sets of untested stimulation parameter values;
forwarding the selected revised proposed set of stimulation parameter values to configure stimulation parameters of the IPG to the revised proposed set of stimulation parameter values; and
repeating the receiving one or more clinical response values as a result of the IPG being configured to the revised proposed set of stimulation parameter values, predicting, by incorporating one or more machine learning engines, the one or more therapeutic response value for each of the plurality of sets of untested stimulation parameter values, selecting the revised proposed set of stimulation parameter values from the plurality of sets of untested stimulation parameter values, and forwarding the selected revised proposed set of stimulation parameter values to configure stimulation parameters of the IPG accordingly, until or unless a stop condition has been reached or the one or more received clinical response values indicates a value that corresponds to a therapeutic response indication within a designated tolerance.
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Abstract
A method or system for facilitating the determining and setting of stimulation parameters for programming an electrical stimulation system using closed loop programming is provided. For example, pulse generator feedback logic is executed by a processor to interface with control instructions of an implantable pulse generator by incorporating one or more machine learning engines to automatically generate a proposed set of stimulation parameter values that each affect a stimulation aspect of the implantable pulse generator, receive one or more clinical responses and automatically generate a revised set of values taking into account the received clinical responses, and repeating the automated receiving of a clinical response and adjusting the stimulation parameter values taking the clinical response into account, until or unless a stop condition is reach or the a therapeutic response is indicated within a designated tolerance.
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Citations
20 Claims
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1. A computing system for facilitating programming settings of an implantable pulse generator associated with a patient, comprising:
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a processor; a memory; and pulse generator feedback control logic, stored in the memory, and configured, when executed by the processor, to interface with control instructions of the implantable pulse generator (IPG) by performing actions of; incorporating one or more machine learning engines, automatically generating a proposed set of stimulation parameter values that each effect a stimulation aspect of the IPG; forwarding the automatically generated proposed set of stimulation parameter values to configure stimulation parameters of the IPG to the proposed set of stimulation parameter values; receiving one or more clinical response values as a result of the IPG being configured to the proposed set of stimulation parameter values; predicting, by incorporating one or more machine learning engines and using the one or more clinical response values, one or more therapeutic response values for each of a plurality of sets of untested stimulation parameter values; selecting, based on the predicted one or more therapeutic response values and on a distance of each set of untested stimulation parameter values from one or more previously tested stimulation parameter values, a revised proposed set of stimulation parameter values from the plurality of sets of untested stimulation parameter values; forwarding the selected revised proposed set of stimulation parameter values to configure stimulation parameters of the IPG to the revised proposed set of stimulation parameter values; and repeating the receiving one or more clinical response values as a result of the IPG being configured to the revised proposed set of stimulation parameter values, predicting, by incorporating one or more machine learning engines, the one or more therapeutic response value for each of the plurality of sets of untested stimulation parameter values, selecting the revised proposed set of stimulation parameter values from the plurality of sets of untested stimulation parameter values, and forwarding the selected revised proposed set of stimulation parameter values to configure stimulation parameters of the IPG accordingly, until or unless a stop condition has been reached or the one or more received clinical response values indicates a value that corresponds to a therapeutic response indication within a designated tolerance. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer-implemented method for automatically determining patient programming settings for an electrical stimulator, comprising:
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receiving an indication of a plurality of stimulation parameters and an indication of a desired therapeutic response value; automatically generating an initial proposed set of stimulation parameter values for testing the electrical stimulator programmed according to these initial values; receiving an indication of clinical results based upon testing the programmed electrical stimulator on a recipient, wherein the received indication indicates a therapeutic response value; automatically generating, using machine learning, one or more predicted therapeutic response values for a plurality of values of the plurality of stimulation parameters for which an indication of clinical results has not yet been received; automatically generating and indicating a next proposed set of stimulation parameter values for testing the electrical stimulator programmed accordingly, based in part on at least one of the one or more predicted therapeutic response values; and repeating the acts of receiving the indication of clinical results based upon testing the programmed electrical simulator, automatically generating using machine learning the one or more predicted therapeutic response values, and automatically generating and indicating a next proposed set of stimulation parameter values for testing the electrical stimulator programmed accordingly, until or unless a stop condition has been reached or the received indication of clinical results indicates a therapeutic response value that is within a designated tolerance. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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19. A computer-readable memory medium containing instructions that control a computer processor, when executed, to automatically determine programming settings of an implantable pulse generator (IPG) associated with a patient by performing a method comprising:
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automatically generating a proposed set of values of a plurality of stimulation parameters that each effect a stimulation aspect of the IPG; causing stimulation parameters of the IPG to be set to the automatically generated proposed set of stimulation parameter values; receiving one or more clinical response values as a result of the IPG being set to the proposed set of stimulation parameter values; predicting, by incorporating one or more machine learning engines and using the one or more clinical response values, at least one therapeutic response value for each of a plurality of sets of untested stimulation parameter values; selecting, based on the at least one predicted therapeutic response value and on a distance of each set of untested stimulation parameter values from one or more previously tested stimulation parameter values, a revised proposed set of stimulation parameter values from the plurality of sets of untested stimulation parameter values; forwarding the selected revised proposed set of stimulation parameter valves to configure stimulation parameters of the IPG to the revised proposed set of stimulation parameter values; and repeating the receiving one or more clinical response values as a result of the IPG being configured to the revised proposed set of stimulation parameter values, predicting, by incorporating one or more machine learning engines, the at least on therapeutic response value for each of the plurality of sets of untested stimulation parameter values, selecting the revised proposed set of stimulation parameter values from the plurality of sets of untested stimulation parameter values, and forwarding the selected revised proposed set of stimulation parameter values to configure stimulation parameters of the IPG accordingly, until or unless a stop condition has been reached or the one or more received clinical response values indicates a value that corresponds to a therapeutic response indication within a designated tolerance. - View Dependent Claims (20)
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Specification