Neural Stimulation with Decomposition of Evoked Compound Action Potentials

Abstract

Methods and systems for providing neuromodulation to a patient are disclosed. The disclosed methods and systems use sensed neural responses to construct and optimize models of the neural elements recruited during the neuromodulation. The models are used to estimate neural recruitment associated with a therapeutic effect and/or with side-effects to stimulation. The models can be used to adjust neuromodulation in a closed-loop fashion.

What is claimed is: 
     
         1 . A device comprising:
 a microprocessor programmed to:
 cause a first electrode implanted in a patient to issue a stimulation waveform to the patient's neural tissue, 
 receive a signal from a second electrode implanted in the patient, the signal indicative of a neural response to the stimulation waveform, 
 compare the received signal to a modeled neural response generated using responses of a plurality of modeled neural elements and a weight associated with each of the plurality of modeled neural elements, and 
 adjust the modeled neural response based on the comparison. 
   
     
     
         2 . The device of  claim 1 , wherein adjusting the modeled neural response comprises adjusting the plurality of modeled neural elements or adjusting the weights associated with at least one of the plurality of neural elements. 
     
     
         3 . The device of  claim 1 , wherein the modeled neural response comprises a computed transmembrane current associated with each of the plurality of modeled neural elements. 
     
     
         4 . The device of  claim 3 , wherein the modeled neural response comprises a modeled voltage induced by the transmembrane currents. 
     
     
         5 . The device of  claim 4 , wherein the modeled neural response is a weighted summation of the modeled voltages. 
     
     
         6 . The device of  claim 1 , wherein the microprocessor is further programmed to estimate relative recruitment of the plurality neural elements within the patient based on the comparison. 
     
     
         7 . The device of  claim 6 , wherein the microprocessor is further programmed to adjust the stimulation waveform to selectively recruit a subset of the patient's neural elements. 
     
     
         8 . The device of  claim 7 , wherein adjusting the stimulation waveform comprises adjusting one or more of an amplitude, pulse width, pulse rate, or pulse shape of the stimulation waveform. 
     
     
         9 . The device of  claim 1 , wherein the modeled neural elements comprise modeled neural fibers of a spinal cord. 
     
     
         10 . The device of  claim 1 , wherein the modeled neural response comprises a modeled evoked compound action potential (ECAP). 
     
     
         11 . A non-transitory computer-readable medium comprising instructions configured to cause a microprocessor to:
 receive a signal from an electrode implanted in a patient, the signal indicative of a neural response of the patient to a stimulation waveform,   provide a modeled neural response based on a baseline set of modeled neural elements,   compare the modeled neural response to the received signal, and   adjust the modeled neural response based on the comparison.   
     
     
         12 . The non-transitory computer-readable medium of  claim 11 , wherein providing a modeled neural response comprises:
 determining transmembrane currents for each of the modeled neural elements,   associating a weight with each of the transmembrane currents,   determining a voltage induced by the transmembrane currents, and   determining the modeled neural response as a weighted sum of the voltages for the transmembrane currents.   
     
     
         13 . The non-transitory computer-readable medium of  claim 12 , wherein adjusting the modeled neural response comprises adding neural elements to the baseline set of modeled neural elements. 
     
     
         14 . The non-transitory computer-readable medium of  claim 12 , wherein adjusting the modeled neural response comprises adjusting the weights associated with the transmembrane currents. 
     
     
         15 . The non-transitory computer-readable medium of  claim 12 , wherein adjusting the modeled neural response comprising adjusting one or more parameters of the baseline set of modeled neural elements. 
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the one or more parameters of the baseline set of modeled neural elements is selected from the group consisting of geometry of the modeled neural element, physiology of the modeled neural element, and electrical properties of the neural elements. 
     
     
         17 . The non-transitory computer-readable medium of  claim 11 , wherein receiving a signal from an electrode implanted in a patient comprises receiving a first signal from a first electrode and receiving a second signal from a second electrode. 
     
     
         18 . The non-transitory computer-readable medium of  claim 11 , wherein receiving a signal from an electrode implanted in a patient comprises receiving a first signal from the electrode indicative of the neural response at a first time and receiving a second signal from the electrode indicative of the neural response at a second time. 
     
     
         19 . The non-transitory computer-readable medium of  claim 11 , further comprising instructions to cause the microprocessor to identify a preferred stimulation waveform based on the received signal. 
     
     
         20 . The non-transitory computer-readable medium of  claim 11 , further comprising instructions to cause the microprocessor to identify a stimulation waveform associated with a side-effect based on the received signal.