Programming of neural stimulation therapy
Disclosed is a method of computing a probability distribution of the suitability of measurement electrode configurations for a neuromodulation device. The method comprises: computing the probability distribution of suitability of measurement electrode configurations from: a predetermined stimulus program vector of the neuromodulation device; and prior patient data. Also disclosed is an automated method of setting a measurement electrode configuration for a neuromodulation device configured to deliver a neural stimulus to a neural pathway of a patient. The method comprises: obtaining an initial measurement electrode configuration for a predetermined stimulus program vector from a prior probability distribution of suitability of measurement electrode configurations; delivering a plurality of neural stimuli of different stimulus intensities to the neural pathway according to the stimulus program vector; measuring intensities of neural responses evoked by the neural stimuli using a current measurement electrode configuration; computing one or more quality measures of the evoked neural responses using the measured neural response intensities and the respective stimulus intensities; refining the probability distribution of suitability of measurement electrode configurations using the one or more quality measures; and obtaining a new measurement electrode configuration for the predetermined stimulus program vector using the refined probability distribution of suitability of measurement electrode configurations.
1 . A neuromodulation system comprising:
a neuromodulation device for controllably delivering a neural stimulus, the neuromodulation device comprising:
a stimulus source configured to provide a neural stimulus to be delivered to a neural pathway of a patient in order to evoke a neural response on the neural pathway;
measurement circuitry configured to process a signal sensed at a measurement electrode configuration subsequent to the delivered neural stimulus, the sensed signal including an evoked neural response; and
a control unit configured to:
control the stimulus source to provide the neural stimulus according to a predetermined stimulus program vector; and
measure an intensity of the evoked neural response in the sensed signal using a measurement parameter vector; and
a processor configured to:
obtain an initial measurement electrode configuration for the predetermined stimulus program vector from a prior probability distribution of suitability of measurement electrode configurations;
instruct the control unit to control the stimulus source to provide a plurality of neural stimuli of different stimulus intensities to the neural pathway according to the predetermined stimulus program vector;
measure intensities of neural responses evoked by the neural stimuli and sensed via a current measurement electrode configuration;
compute one or more quality measures of the evoked neural responses using the measured neural response intensities and the respective stimulus intensities;
refine the prior probability distribution of suitability of measurement electrode configurations using the one or more quality measures; and
obtain a new measurement electrode configuration for the predetermined stimulus program vector from the refined prior probability distribution of suitability of measurement electrode configurations.
2 . The neuromodulation system of claim 1 , wherein the processor is further configured to repeat the instructing, measuring, computing, refining, and obtaining until a stopping criterion is reached.
3 . The neuromodulation system of claim 1 , wherein the processor is further configured to compute the prior probability distribution of suitability of measurement electrode configurations from:
the predetermined stimulus program vector of the neuromodulation device; and
prior patient data.
4 . The neuromodulation system of claim 1 , wherein the processor is further configured to:
obtain an initial measurement parameter vector for the predetermined stimulus program vector and the initial measurement electrode configuration from one of a plurality of prior probability distributions of suitability of measurement parameters corresponding to the initial measurement electrode configuration and the stimulus program vector;
measure the intensities of the neural responses evoked by the neural stimuli and sensed via the initial measurement electrode configuration using the initial measurement parameter vector; and
refine the prior probability distribution of suitability of measurement parameters corresponding to the initial measurement electrode configuration using the one or more quality measures.
5 . The neuromodulation system of claim 4 , wherein the processor is further configured to obtain a new measurement parameter vector for the neuromodulation device using the refined probability distribution of suitability of measurement parameters corresponding to the new measurement electrode configuration.
6 . The neuromodulation system of claim 4 , wherein the processor is further configured to compute the plurality of probability distributions of suitability of measurement parameters for respective measurement electrode configurations using:
the predetermined stimulus program vector of the neuromodulation device; and
prior patient data.
7 . The neuromodulation system of claim 1 , further comprising an external computing device in communication with the neuromodulation device.
8 . The neuromodulation system of claim 7 , wherein the processor forms part of the external computing device.
9 . The neuromodulation system of claim 1 , wherein the processor forms part of the neuromodulation device.