PROGRAMMING OF NEURAL STIMULATION THERAPY WITH MULTIPLE STIMULATION SETS

1 . A neurostimulation system comprising:

a neurostimulation device for controllably delivering a neural stimulus, the neurostimulation device comprising:

a plurality of implantable electrodes including one or more stimulus electrodes and one or more measurement electrodes;

a stimulus source configured to deliver neural stimuli according to a stimulation set to a neural pathway of a patient, wherein the stimulation set comprises a stimulus electrode configuration and a set of stimulus parameters;

measurement circuitry configured to capture signal windows from signals sensed at the one or more measurement electrodes subsequent to respective neural stimuli; and

a control unit configured to control the stimulus source to deliver a neural stimulus according to any one of a plurality of stimulation sets; and

a processor configured to:

instruct the control unit to control the stimulus source to deliver a plurality of neural stimuli according to a first stimulation set of the plurality of stimulation sets and according to respective stimulus intensity parameters;

receive from the measurement circuitry a captured signal window subsequent to each delivered neural stimulus;

measure a characteristic of an evoked neural response in each captured signal window; and

determine a quality metric for the first stimulation set from the measured characteristics.

2 . The neurostimulation system of claim 1 , wherein the processor is configured to determine the quality metric for the first stimulation set from the measured characteristics by computing an independent metric for the first stimulation set.

3 . The neurostimulation system of claim 2 , wherein the independent metric comprises a cross-intensity metric.

4 . The neurostimulation system of claim 3 , wherein the processor is configured to compute the cross-intensity metric by:

measuring an intensity of an evoked neural response in each captured signal window, thereby forming a set of stimulus intensity parameter-response intensity pairs;

fitting an activation plot to the set of stimulus intensity parameter-response intensity pairs; and

computing the cross-intensity metric as a quality metric of the fitted activation plot.

5 . The neurostimulation system of claim 2 , wherein the independent metric comprises a cross-posture metric.

6 . The neurostimulation system of claim 5 , wherein the processor is configured to compute the cross-posture metric from the measured characteristics of evoked neural responses in captured signal windows corresponding to neural stimuli delivered with the patient in a plurality of postures.

7 . The neurostimulation system of claim 6 , wherein the processor is configured to compute the cross-posture metric by computing a coefficient of variation of the measured characteristic across the plurality of postures.

8 . The neurostimulation system of claim 6 , wherein the measured characteristic is a signal-to-noise ratio of the captured signal window.

9 . The neurostimulation system of claim 6 , wherein the measured characteristic is a signal-to-artefact ratio of the captured signal window.

10 . The neurostimulation system of claim 6 , wherein the measured characteristic is an artefact level in the captured signal window.

11 . The neurostimulation system of claim 6 , wherein the measured characteristic is morphological feature of an evoked neural response in the captured signal window.

12 . The neurostimulation system of claim 6 , wherein the processor is configured to compute the cross-posture metric by:

measuring an intensity of an evoked neural response in each captured signal window, thereby forming a set of stimulus intensity parameter-response intensity pairs;

fitting an activation plot to the set of stimulus intensity parameter-response intensity pairs; and

estimating a sensitivity of the fitted activation plot for a posture of the plurality of postures.

13 . The neurostimulation system of claim 12 , wherein the processor is configured to compute the cross-posture metric by computing a coefficient of variation of the estimated sensitivities across the plurality of postures.

14 . The neurostimulation system of claim 12 , wherein the processor is further configured to estimate a threshold of the fitted activation plot for a posture of the plurality of postures.

15 . The neurostimulation system of claim 14 , wherein the processor is configured to compute the cross-posture metric by computing a coefficient of variation of products of the estimated sensitivities and the estimated thresholds across the plurality of postures.

16 . The neurostimulation system of claim 1 , wherein the processor is configured to determine the quality metric for the first stimulation set from the measured characteristics by computing a representativeness metric for the first stimulation set.

17 . The neurostimulation system of claim 16 , wherein the control unit is further configured to:

control the stimulus source to deliver a neural stimulus according to each of the plurality of stimulation sets in a cycle according to respective stimulus intensity parameters;

measure an intensity of an evoked neural response in each captured signal window corresponding to a stimulus delivered according to the first stimulation set;

adjust the stimulus intensity parameter for the first stimulation set based on the measured neural response intensity so as to maintain the measured neural response intensity at a target value; and

adjust the stimulus intensity parameters for the other stimulation sets based on the stimulus intensity parameter for the first stimulation set.

18 . The neurostimulation system of claim 17 , wherein the processor is configured to compute the representativeness metric for the first stimulation set by:

measuring, for each stimulation set of the plurality of stimulation sets, an intensity of an evoked neural response in each captured signal window corresponding to a stimulus delivered according to the stimulation set; and

computing, for each stimulation set of the plurality of stimulation sets, an amount of noise in the measured neural response intensities corresponding to the stimulation set.

19 . The neurostimulation system of claim 18 , wherein the processor is further configured to compute the representativeness metric for the first stimulation set by:

combining the amounts of noise into a single measure of noise across all stimulation sets.

20 . The neurostimulation system of claim 19 , wherein the processor is further configured to compute the representativeness metric for the first stimulation set from the single measure of noise.

21 . The neurostimulation system of claim 19 , wherein the processor is further configured to compute the representativeness metric for the first stimulation set by:

repeating the measuring, computing, and combining with the patient in at least one further posture to obtain a single measure of noise across all stimulation sets for each posture;

combining the single measures of noise for each posture into a single cross-posture measure of noise across all stimulation sets; and

computing the representativeness metric from the single cross-posture measure of noise.

22 . The neurostimulation system of claim 18 , wherein the processor is further configured to compute the representativeness metric for the first stimulation set by:

repeating the measuring and computing with the patient in at least one further posture to obtain a single measure of noise across all stimulation sets for each posture;

constructing a noise matrix from the amounts of noise for each stimulation set and each posture;

computing a noise covariance matrix from the noise matrix; and

computing the representativeness metric from a row of entries of the noise covariance matrix corresponding to the first stimulation set.

23 . The neurostimulation system of claim 17 , wherein the processor is configured to compute the representativeness metric for the first stimulation set by:

measuring, for each stimulation set of the plurality of stimulation sets, a plurality of response intensities of a plurality of evoked neural responses corresponding to respective stimuli delivered according to the stimulation set;

computing, for each stimulation set of the plurality of stimulation sets, a sensitivity corresponding to the stimulation set from the plurality of measured response intensities; and

compute the representativeness metric from the computed sensitivities.

24 . The neurostimulation system of claim 23 , wherein the processor is configured to compute the representativeness metric as a measure of how closely the sensitivity corresponding the first stimulation set satisfies a proportionality condition with the sensitivities corresponding to the other stimsets.

25 . The neurostimulation system of claim 1 , wherein the control unit is further configured to:

control the stimulus source to deliver a neural stimulus according to each of the plurality of stimulation sets in a cycle according to respective stimulus intensity parameters;

measure an intensity of an evoked neural response in each captured signal window corresponding to a stimulus delivered according to an applied stimulation set of the plurality of stimulation sets;

adjust the stimulus intensity parameter for the applied stimulation set based on the measured neural response intensity so as to maintain the measured neural response intensity at a target value; and

adjust the stimulus intensity parameters for the non-applied stimulation sets based on the stimulus intensity parameter for the applied stimulation set.

26 . The neurostimulation system of claim 25 , wherein the quality metric of the first stimulation set is indicative of the suitability of the first stimulation set to be used as the applied stimulation set.

27 . The neurostimulation system of claim 26 , wherein the processor is further configured to repeat the instructing, receiving, measuring, and determining for each stimulation set of the plurality of stimulation sets, to thereby obtain a quality metric for each stimulation set of the plurality of stimulation sets.

28 . The neurostimulation system of claim 27 , wherein the processor is further configured to select a stimulation set to be used as the applied stimulation set based on the determined quality metrics for each stimulation set.

29 . The neurostimulation system of claim 28 , wherein the processor is further configured to program the neurostimulation device to use the selected stimulation set as the applied stimulation set.

30 . The neurostimulation system of claim 1 , wherein the processor is part of the neurostimulation device.

31 . The neurostimulation system of claim 1 , further comprising an external computing device in communication with the neurostimulation device.

32 . The neurostimulation system of claim 31 , wherein the processor is part of the external computing device.

33 . An automated method of controllably delivering neural stimuli, the method comprising:

delivering, according to a first stimulation set of a plurality of stimulation sets, the neural stimuli to a neural pathway of a patient according to respective stimulus intensity parameters, wherein each stimulation set comprises a stimulus electrode configuration and a set of stimulus parameters;

capturing a signal window subsequent to each delivered neural stimulus;

measuring a characteristic of an evoked neural response in each captured signal window; and

determining a quality metric for the first stimulation set from the measured characteristics.

34 . The method of claim 33 , wherein the determining the quality metric for the first stimulation set from the measured characteristics comprises computing an independent metric for the first stimulation set.

35 . The method of claim 33 , wherein the determining the quality metric for the first stimulation set from the measured characteristics comprises computing a representativeness metric for the first stimulation set.

36 . The method of claim 33 , further comprising:

delivering a neural stimulus according to each of the plurality of stimulation sets in a cycle according to respective stimulus intensity parameters;

measure an intensity of an evoked neural response in each captured signal window corresponding to a stimulus delivered according to an applied stimulation set of the plurality of stimulation sets;

adjust a stimulus intensity parameter for the applied stimulation set based on the measured neural response intensity so as to maintain the measured neural response intensity at a target value; and

adjust the stimulus intensity parameters for the non-applied stimulation sets based on the stimulus intensity parameter for the applied stimulation set.

37 . The method of claim 36 , wherein the quality metric of the first stimulation set is indicative of the suitability of the first stimulation set to be used as the applied stimulation set.

38 . The method of claim 37 , further comprising repeating the delivering, capturing, measuring, and determining for each stimulation set of the plurality of stimulation sets, to thereby determine a quality metric for each stimulation set of the plurality of stimulation sets.

39 . The method of claim 38 , further comprising selecting a stimulation set to be used as the applied stimulation set based on the determined quality metrics for each stimulation set.

40 . The method of claim 39 , further comprising using the selected stimulation set as the applied stimulation set.

41 . A neurostimulation system comprising:

a multiple-stimset closed-loop neurostimulation device configured to controllably deliver neural stimuli according to a plurality of stimulation sets to a neural pathway of a patient so as to maintain a neural response intensity for at least an applied stimulation set of the plurality of stimulation sets at a corresponding target value; and

a processor configured to:

instruct the multiple-stimset closed-loop neurostimulation device to deliver a plurality of neural stimuli according to a first stimulation set of the plurality of stimulation sets;

receive a captured signal window corresponding to each delivered neural stimulus;

measure a characteristic of an evoked neural response in each captured signal window; and

determine a quality metric for the first stimulation set from the measured characteristics.

42 . The neurostimulation system of claim 41 , wherein the processor is configured to determine the quality metric for the first stimulation set from the measured characteristics by computing an independent metric for the first stimulation set.

43 . The neurostimulation system of claim 41 , wherein the processor is configured to determine the quality metric for the first stimulation set from the measured characteristics by computing a representativeness metric for the first stimulation set.

44 . The neurostimulation system of claim 41 , wherein the quality metric of the first stimulation set is indicative of the suitability of the first stimulation set to be used as the applied stimulation set.

45 . The neurostimulation system of claim 44 , wherein the processor is further configured to repeat the instructing, receiving, measuring, and determining, to thereby obtain a quality metric for each stimulation set of the plurality of stimulation sets.

46 . The neurostimulation system of claim 45 , wherein the processor is further configured to select a stimulation set to be used as the applied stimulation set based on the determined quality metrics for each stimulation set.

47 . The neurostimulation system of claim 46 , wherein the processor is further configured to program the multiple-stimset closed-loop device to use the selected stimulation set as the applied stimulation set.

48 . The neurostimulation system of claim 41 , wherein the processor is part of the neurostimulation device.

49 . The neurostimulation system of claim 41 , further comprising an external computing device in communication with the neurostimulation device.

50 . The neurostimulation system of claim 49 , wherein the processor is part of the external computing device.