System and method for providing glucose control therapy

Abstract

A system may include an implantable structure with a plurality of electrodes attached thereto, where the implantable structure is configured to be implanted proximate to a nerve that innervates and is proximate to an organ involved with glucose control. The system may further include a controller configured for use to control which of the plurality of electrodes are modulation electrodes and which of the plurality of electrodes are sense electrodes, a modulation energy generator configured to deliver modulation energy using one or more of the modulation electrodes, and a nerve traffic sensor configured to sense nerve traffic in the nerve using one or more of the sense electrodes. The controller may be configured to determine if the delivered modulation energy captures the nerves based on the sensed neural activity.

What is claimed is: 
     
         1 . A system, comprising:
 a controller configured to:
 receive a plurality of therapy inputs to provide indicators of at least a glucose measure and activity; 
 monitor a rate of change for the glucose measure; 
 determine a therapy input index based on the at least the glucose measure, the activity, and the rate of change for the glucose measure, the therapy input index corresponding to an index level from a plurality of index levels, wherein each of the plurality of index levels corresponds to a plurality of graded therapies, the plurality of graded therapies having different therapy targets, different therapy types, and different parameters, wherein different ones of the plurality of graded therapies differ from each other in at least one of the therapy targets, the therapy types or the parameters; and 
 determine a graded therapy from the plurality of graded therapies that correspond to the therapy input index; and 
   a diabetic therapy delivery system configured to deliver the determined graded therapy.   
     
     
         2 . The system of  claim 1 , wherein the different therapy targets include parasympathetic targets and sympathetic targets, and a first one of the plurality of graded therapies delivers neuromodulation to a parasympathetic target and a second one of the plurality of graded therapies delivers neuromodulation to a sympathetic target. 
     
     
         3 . The system of  claim 1 , wherein the different therapy targets include a target for hepatic neuromodulation and a target for pancreatic neuromodulation, and a first one of the plurality of graded therapies delivers neuromodulation to the target for hepatic neuromodulation and a second one of the plurality of graded therapies delivers neuromodulation to the target for pancreatic neuromodulation. 
     
     
         4 . The system of  claim 1 , wherein the different therapy types include a conduction block, a depletion block or neurostimulation, and a first one of the plurality of graded therapies delivers the conduction block, a second one of the plurality of graded therapies delivers the depletion block, and a third one of the plurality of graded therapies delivers the neurostimulation. 
     
     
         5 . The system of  claim 1 , further comprising using artificial intelligence to analyze inputs and applied therapies to personalize the determination of the graded therapy. 
     
     
         6 . The system of  claim 5 , wherein the artificial intelligence is used to determine a rate of glucose change for certain food and determine the graded therapy accordingly. 
     
     
         7 . The system of  claim 1 , wherein the plurality of therapy inputs includes a plurality of therapy inputs selected from: an activity sensor; a posture sensor; a neural activity sensor; a glucose monitor; a diet user input; a patient factor user input; an anticipated activity user input; a glucose level user input; a therapy start and/or stop user input; a therapy scheduling user input; an event; a location; and app-monitored condition using app on a user device. 
     
     
         8 . A method for delivering a diabetic therapy, comprising:
 receiving a plurality of therapy inputs to provide indicators of at least a glucose measure and activity;   monitoring a rate of change for the glucose measure;   determining a therapy input index based on the at least the glucose measure, the activity, and the rate of change for the glucose measure, the therapy input index corresponding to an index level from a plurality of index levels, wherein each of the plurality of index levels corresponds to a plurality of graded therapies, the plurality of graded therapies having different therapy targets, different therapy types, and different parameters, wherein different ones of the plurality of graded therapies differ from each other in at least one of the therapy targets, the therapy types or the parameters;   determining a graded therapy from the plurality of graded therapies that correspond to the therapy input index; and   delivering the determined graded therapy by delivering a corresponding therapy type to a corresponding therapy target using corresponding parameters.   
     
     
         9 . The method of  claim 8 , wherein the different therapy targets include parasympathetic targets and sympathetic targets, and a first one of the plurality of graded therapies delivers neuromodulation to a parasympathetic target and a second one of the plurality of graded therapies delivers neuromodulation to a sympathetic target. 
     
     
         10 . The method of  claim 8 , wherein the different therapy targets include a target for hepatic neuromodulation and a target for pancreatic neuromodulation wherein the different therapy targets include a target for hepatic neuromodulation and a target for pancreatic neuromodulation, and a first one of the plurality of graded therapies delivers neuromodulation to the target for hepatic neuromodulation and a second one of the plurality of graded therapies delivers neuromodulation to the target for pancreatic neuromodulation. 
     
     
         11 . The method of  claim 8 , wherein the different therapy types include a conduction block, a depletion block or a stimulation block, wherein the different therapy types include a conduction block, a depletion block or neurostimulation, and a first one of the plurality of graded therapies delivers the conduction block, a second one of the plurality of graded therapies delivers the depletion block, and a third one of the plurality of graded therapies delivers the neurostimulation. 
     
     
         12 . The method of  claim 8 , further comprising using artificial intelligence to analyze inputs and applied therapies to personalize the determination of the graded therapy. 
     
     
         13 . The method of  claim 12 , wherein the artificial intelligence is used to determine a rate of glucose change for certain food and determine the graded therapy accordingly. 
     
     
         14 . The method of  claim 8 , wherein the plurality of therapy inputs includes a plurality of therapy inputs selected from: an activity sensor; a posture sensor; a neural activity sensor; a glucose monitor; a diet user input; a patient factor user input; an anticipated activity user input; a glucose level user input; a therapy start and/or stop user input; a therapy scheduling user input; an event; a location; and app-monitored condition using app on a user device. 
     
     
         15 . A non-transitory machine-readable medium including instructions, which when executed by a machine, cause the machine to perform a method for delivering a diabetic therapy, comprising:
 receiving a plurality of therapy inputs to provide indicators of at least a glucose measure and activity;   monitoring a rate of change for the glucose measure;   determining a therapy input index based on the at least the glucose measure, the activity, and the rate of change for the glucose measure, the therapy input index corresponding to an index level from a plurality of index levels, wherein each of the plurality of index levels corresponds to a plurality of graded therapies, the plurality of graded therapies having different therapy targets, different therapy types, and different parameters, wherein different ones of the plurality of graded therapies differ from each other in at least one of the therapy targets, the therapy types or the parameters;   determining a graded therapy from the plurality of graded therapies that correspond to the therapy input index; and   delivering the determined graded therapy by delivering a corresponding therapy type to a corresponding therapy target using corresponding parameters.   
     
     
         16 . The non-transitory machine-readable medium of  claim 15 , wherein the different therapy targets include parasympathetic targets and sympathetic targets, and a first one of the plurality of graded therapies delivers neuromodulation to a parasympathetic target and a second one of the plurality of graded therapies delivers neuromodulation to a sympathetic target. 
     
     
         17 . The non-transitory machine-readable medium of  claim 15 , wherein the different therapy targets include a target for hepatic neuromodulation and a target for pancreatic neuromodulation wherein the different therapy targets include a target for hepatic neuromodulation and a target for pancreatic neuromodulation, and a first one of the plurality of graded therapies delivers neuromodulation to the target for hepatic neuromodulation and a second one of the plurality of graded therapies delivers neuromodulation to the target for pancreatic neuromodulation. 
     
     
         18 . The non-transitory machine-readable medium of  claim 15 , wherein the different therapy types include a conduction block, a depletion block or a stimulation block, wherein the different therapy types include a conduction block, a depletion block or neurostimulation, and a first one of the plurality of graded therapies delivers the conduction block, a second one of the plurality of graded therapies delivers the depletion block, and a third one of the plurality of graded therapies delivers the neurostimulation. 
     
     
         19 . The non-transitory machine-readable medium of  claim 15 , wherein the method further comprises using artificial intelligence to analyze inputs and applied therapies to personalize the determination of the graded therapy, wherein the artificial intelligence is used to determine a rate of glucose change for certain food and determine the graded therapy accordingly. 
     
     
         20 . The non-transitory machine-readable medium of  claim 15 , wherein the plurality of therapy inputs includes a plurality of therapy inputs selected from: an activity sensor; a posture sensor; a neural activity sensor; a glucose monitor; a diet user input; a patient factor user input; an anticipated activity user input; a glucose level user input; a therapy start and/or stop user input; a therapy scheduling user input; an event; a location; and app-monitored condition using app on a user device.