Devices and Methods for Stimulating Neural Tissue

Abstract

In some implementations, the device may include a neural stimulation system having: an implantable closed-loop neural stimulation device for controllably delivering neural stimuli via one or more stimulus electrodes, the device having the one or more stimulus electrodes and a feedback controller configured to adjust a stimulus intensity parameter so as to maintain a measured neural response intensity at a target response intensity; and a processor configured to: estimate an out-of-compliance current limit for each of the one or more stimulus electrodes; estimate a closed-loop current requirement for the implantable closed-loop neural stimulation device; compare the out-of-compliance current limit for each of the one or more stimulus electrodes to the closed-loop current requirement; and take a mitigating action based on the comparison.

Claims

1. A neural stimulation system comprising: an implantable device for controllably delivering neural stimuli, the device comprising: a plurality of electrodes including one or more stimulus electrodes and one or more measurement electrodes; a stimulus source configured to provide neural stimuli to be delivered via the one or more stimulus electrodes to a neural pathway of a patient in order to evoke neural responses from the neural pathway; measurement circuitry configured to capture signal windows from signals sensed on the neural pathway via the one or more measurement electrodes subsequent to respective neural stimuli; and a control unit configured to: control the stimulus source to provide a neural stimulus according to a stimulus intensity parameter; measure an intensity of an evoked neural response in a captured signal window subsequent to the neural stimulus; compute a feedback variable from the measured intensity of the evoked neural response; and adjust, using a feedback controller, the stimulus intensity parameter so as to maintain the feedback variable at a target response intensity; and a processor configured to: estimate an out-of-compliance current limit for each of the one or more stimulus electrodes; estimate a closed-loop current requirement for the implantable device; compare the out-of-compliance current limit for each of the one or more stimulus electrodes to the closed-loop current requirement; and take a mitigating action based on the comparison.

2. The system of claim 1, wherein the processor is configured to estimate the out-of-compliance current limit for a stimulus electrode by: measuring an electrode resistance of the stimulus electrode; and estimating the out-of-compliance current limit for the stimulus electrode using the measured electrode resistance of the stimulus electrode.

3. The system of claim 1, wherein the processor is configured to estimate the closed-loop current requirement for the implantable device by: estimating a threshold value of the stimulus intensity parameter; and estimating the closed-loop current requirement by applying a model to the estimated threshold value.

4. The system of claim 1, wherein the processor is configured to estimate the closed-loop current requirement for the implantable device from a pulse width of the provided neural stimuli.

5. The system of claim 1, wherein the processor is configured to take the mitigation action upon the closed-loop current requirement for the implantable device exceeding the out-of-compliance current limit for at least one stimulus electrode of the one or more stimulus electrodes.

6. The system of claim 5, wherein the mitigation action comprises increasing the out-of-compliance current limit for the at least one stimulus electrode of the one or more stimulus electrodes.

7. The system of claim 6, wherein the processor is configured to increase the out-of-compliance current limit by increasing a number of return electrodes via which the neural stimulus current is returned from the neural pathway.

8. The system of claim 6, wherein the processor is configured to increase the out-of-compliance current limit by selecting an alternative stimulus electrode to the at least one stimulus electrode of the one or more stimulus electrodes.

9. The system of claim 5, wherein the mitigation action comprises decreasing the closed-loop current requirement for the implantable device.

10. The system of claim 9, wherein the processor is configured to decrease the closed-loop current requirement by increasing a pulse width of the provided neural stimuli.

11. The system of claim 10, wherein the processor is configured to use population statistics to increase the pulse width such that the out-of-compliance current limit for a stimulus electrode is likely to exceed the closed-loop current requirement for the implantable device.

12. An automated method of controllably delivering neural stimuli to a neural pathway of a patient, the method comprising: delivering a neural stimulus to the neural pathway of the patient in order to evoke a neural response from the neural pathway, the neural stimulus being delivered according to a stimulus intensity parameter via one or more stimulus electrodes; capturing a signal window from a signal sensed on the neural pathway subsequent to the delivered neural stimulus; measuring an intensity of a neural response evoked by the delivered neural stimulus in the captured signal window; computing, from the measured intensity of the evoked neural response, a feedback variable; adjusting the stimulus intensity parameter so as to maintain the feedback variable at a target response intensity; estimating an out-of-compliance current limit for each of the one or more stimulus electrodes; estimating a closed-loop current requirement; comparing the out-of-compliance current limit for each of the one or more stimulus electrodes to the closed-loop current requirement; and taking a mitigating action based on the comparison.

13. The method of claim 12, wherein estimating the out-of-compliance current limit for a stimulus electrode by: measuring an electrode resistance of the stimulus electrode; and estimating the out-of-compliance current limit for the stimulus electrode using the measured electrode resistance of the stimulus electrode.

14. The method of claim 12, wherein estimating the closed-loop current comprises: estimating a threshold value of the stimulus intensity parameter; and estimating the closed-loop current requirement by applying a model to the estimated threshold value.

15. The method of claim 12, wherein taking a mitigating action based on the comparison comprises taking the mitigation action upon the closed-loop current requirement exceeding the out-of-compliance current limit for at least one stimulus electrode of the one or more stimulus electrodes.

16. The method of claim 15, wherein the mitigation action comprises increasing the out-of-compliance current limit for the at least one stimulus electrode of the one or more stimulus electrodes.

17. The method of claim 16, wherein increasing the out-of-compliance current limit comprises increasing a number of return electrodes via which the neural stimulus current is returned from the neural pathway.

18. The method of claim 15, wherein the mitigation action comprises decreasing the closed-loop current requirement.

19. The method of claim 18, wherein decreasing the closed-loop current requirement comprises increasing a pulse width of the neural stimuli.

20. A neural stimulation system comprising: an implantable closed-loop neural stimulation device for controllably delivering neural stimuli via one or more stimulus electrodes, the device comprising the one or more stimulus electrodes and a feedback controller configured to adjust a stimulus intensity parameter so as to maintain a measured neural response intensity at a target response intensity: and a processor configured to: estimate an out-of-compliance current limit for each of the one or more stimulus electrodes;: estimate a closed-loop current requirement for the implantable closed-loop neural stimulation device; compare the out-of-compliance current limit for each of the one or more stimulus electrodes to the closed-loop current requirement; and take a mitigating action based on the comparison.

21. A method of estimating a maximum stimulus current to be delivered to a patient by a neural stimulation device, the method comprising: estimating an evoked compound action potential (ECAP) threshold for the neural stimulation device based on neural stimuli delivered by the neural stimulation device, wherein the ECAP threshold is the intensity of the neural stimuli to be delivered above which neural recruitment occurs in a predetermined posture of the patient; and estimating the maximum stimulus current from the estimated ECAP threshold.

22. The method of claim 21, wherein the estimating the maximum stimulus current comprises applying a model to the estimated ECAP threshold.

23. The method of claim 22, wherein the model comprises a function y=Cx.sup.?, where x represents the estimated ECAP threshold and y represents the maximum stimulus current.

24. The method of claim 21, wherein the predetermined posture is a least sensitive posture.

25. A neural stimulation system comprising: an implantable device for controllably delivering neural stimuli, the device comprising: a plurality of electrodes including one or more stimulus electrodes: a stimulus source configured to provide neural stimuli to be delivered via the one or more stimulus electrodes to a neural pathway of a patient; and a control unit configured to: control the stimulus source to provide a neural stimulus according to a stimulus current and a further stimulus parameter; and a processor configured to: estimate an out-of-compliance current limit for each of the one or more stimulus electrodes: and choose a value for the further stimulus parameter such that the out-of-compliance current limit for each of the one or more stimulus electrodes exceeds a maximum value of the stimulus current.

26. The system of claim 25, wherein the processor is configured to estimate the out-of-compliance current limit for a stimulus electrode by: measuring an electrode resistance of the stimulus electrode; and estimating the out-of-compliance current limit for the stimulus electrode using the measured electrode resistance of the stimulus electrode.

27. The system of claim 25, wherein the processor is configured to choose the value for the further stimulus parameter using population statistics relating the further stimulus parameter to the maximum value of the stimulus current.

28. The system of claim 27, wherein the maximum value of the stimulus current is a closed-loop current requirement for the implantable device.

29. The system of claim 27, wherein the maximum value of the stimulus current is a discomfort threshold.

30. The system of claim 27, wherein the further stimulus parameter is pulse width.

31. An automated method of controllably delivering neural stimuli to a neural pathway of a patient, the method comprising: delivering a neural stimulus to the neural pathway of the patient in order to evoke a neural response from the neural pathway, the neural stimulus being delivered according to a stimulus current and a further stimulus parameter via one or more stimulus electrodes; estimating an out-of-compliance current limit for each of the one or more stimulus electrodes; and choosing a value for the further stimulus parameter such that the out-of-compliance current limit for each of the one or more stimulus electrodes is likely to exceed a maximum value of the stimulus current.

32. The method of claim 31, wherein estimating the out-of-compliance current limit for a stimulus electrode comprises: measuring an electrode resistance of the stimulus electrode; and estimating the out-of-compliance current limit for the stimulus electrode using the measured electrode resistance of the stimulus electrode.

33. The method of claim 31, wherein choosing the value for the further stimulus parameter uses population statistics relating the further stimulus parameter to the maximum value of the stimulus current.

34. The method of claim 33, wherein the maximum value of the stimulus current is a closed-loop current requirement.

35. The method of claim 33, wherein the maximum value of the stimulus current is a discomfort threshold.

36. The method of claim 33, wherein the further stimulus parameter is pulse width.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0025] One or more implementations of the invention will now be described with reference to the accompanying drawings, in which:

[0026] FIG. 1 schematically illustrates an implanted spinal cord stimulator, according to one implementation of the present technology;

[0027] FIG. 2 is a block diagram of the stimulator of FIG. 1;

[0028] FIG. 3 is a schematic illustrating interaction of the implanted stimulator of FIG. 1 with a nerve;

[0029] FIG. 4a illustrates an idealised activation plot for one posture of a patient undergoing neural stimulation;

[0030] FIG. 4b illustrates the variation in the activation plots with changing posture of the patient;

[0031] FIG. 5 is a schematic illustrating elements and inputs of a closed-loop neural stimulation (CLNS) system, according to one implementation of the present technology;

[0032] FIG. 6 illustrates the typical form of an electrically evoked compound action potential (ECAP) of a healthy subject;

[0033] FIG. 7 is a block diagram of a neural stimulation therapy system including the implanted stimulator of FIG. 1 according to one implementation of the present technology;

[0034] FIG. 8 contains a model of the Electrode-Tissue-Electrode interface of an implanted neuromodulation device;

[0035] FIG. 9 illustrates a star network approximation to the resistor mesh in the model of FIG. 8;

[0036] FIG. 10 is a simplified circuit representation of a neuromodulation device configured to source a current from a supply voltage rail to tissue via current sources and a pair of stimulus electrodes, and return the current from the tissue via a pair of return electrodes connected to ground;

[0037] FIG. 11 is a graph showing (as points) the maximum stimulus current produced by the stimulator of a closed-loop neural stimulation device over all postures for a number of patients;

[0038] FIG. 12 is a flow chart illustrating a method of pre-emptively mitigating the risk of out-of-compliance events for the current therapy parameters of a closed-loop neural stimulation device according to one implementation of the present technology;

[0039] FIG. 13 is a graph containing two distributions of measured ECAP thresholds at two different pulse widths; and

[0040] FIG. 14 is a flow chart illustrating a method of pre-emptively mitigating the risk of out-of-compliance events for a neural stimulation device according to one implementation of the present technology.

DETAILED DESCRIPTION OF THE PRESENT TECHNOLOGY

[0041] FIG. 1 schematically illustrates an implanted spinal cord stimulator 100 in a patient 108, according to one implementation of the present technology. Stimulator 100 comprises an electronics module 110 implanted at a suitable location. In one implementation, stimulator 100 is implanted in the patient's lower abdominal area or posterior superior gluteal region. In other implementations, the electronics module 110 is implanted in other locations, such as in a flank or sub-clavicularly. Stimulator 100 further comprises an electrode array 150 implanted within the epidural space and connected to the module 110 by a suitable lead. The electrode array 150 may comprise one or more electrodes such as electrode pads on a paddle lead, circular (e.g., ring) electrodes surrounding the body of the lead, conformable electrodes, cuff electrodes, segmented electrodes, or any other type of electrodes capable of forming unipolar, bipolar or multipolar electrode configurations for stimulation and measurement. The electrodes may pierce or affix directly to the tissue itself.

[0042] Numerous aspects of the operation of implanted stimulator 100 may be programmable by an external computing device 192, which may be operable by a user such as a clinician or the patient 108. Moreover, implanted stimulator 100 serves a data gathering role, with gathered data being communicated to external device 192 via a transcutaneous communications channel 190. Communications channel 190 may be active on a substantially continuous basis, at periodic intervals, at non-periodic intervals, or upon request from the external device 192. External device 192 may thus provide a clinical interface configured to program the implanted stimulator 100 and recover data stored on the implanted stimulator 100. This configuration is achieved by program instructions collectively referred to as the Clinical Programming Application (CPA) and stored in an instruction memory of the clinical interface.

[0043] FIG. 2 is a block diagram of the stimulator 100. Electronics module 110 contains a battery 112 and a telemetry module 114. In implementations of the present technology, any suitable type of transcutaneous communications channel 190, such as infrared (IR), radiofrequency (RF), capacitive and/or inductive transfer, may be used by telemetry module 114 to transfer power and/or data to and from the electronics module 110 via communications channel 190. Module controller 116 has an associated memory 118 storing one or more of clinical data 120, clinical settings 121, control programs 122, and the like. Controller 116 is configured by control programs 122, sometimes referred to as firmware, to control a pulse generator 124 to generate stimuli, such as in the form of electrical pulses, in accordance with the clinical settings 121. Electrode selection module 126 switches the generated pulses to the selected electrode(s) of electrode array 150, for delivery of the pulses to the tissue surrounding the selected electrode(s). Measurement circuitry 128, which may comprise an amplifier and/or an analog-to-digital converter (ADC), is configured to process signals comprising neural responses sensed at measurement electrode(s) of the electrode array 150 as selected by electrode selection module 126.

[0044] FIG. 3 is a schematic illustrating interaction of the implanted stimulator 100 with a nerve 180 in the patient 108. In the implementation illustrated in FIG. 3 the nerve 180 may be located in the spinal cord, however in alternative implementations the stimulator 100 may be positioned adjacent any desired neural tissue including a peripheral nerve, visceral nerve, parasympathetic nerve or a brain structure. Electrode selection module 126 selects a stimulus electrode 2 of electrode array 150 through which to deliver a pulse from the pulse generator 124 to surrounding tissue including nerve 180. A pulse may comprise one or more phases, e.g. a biphasic stimulus pulse 160 comprises two phases. Electrode selection module 126 also selects a return electrode 4 of the electrode array 150 for stimulus current return in each phase, to maintain a zero net charge transfer. The use of two electrodes in this manner for delivering and returning current in each stimulus phase is referred to as bipolar stimulation. Alternative embodiments may apply other forms of bipolar stimulation, or may use a greater number of stimulus and/or return electrodes. The set of stimulus electrodes and return electrodes is referred to as the stimulus electrode configuration. Electrode selection module 126 is illustrated as connecting to a ground 130 of the pulse generator 124 to enable stimulus current return via the return electrode 4. However, other connections for current return may be used in other implementations.

[0045] Delivery of an appropriate stimulus via electrodes 2 and 4 to the nerve 180 evokes a neural response 170 comprising an evoked compound action potential (ECAP) which will propagate along the nerve 180 as illustrated at a rate known as the conduction velocity. The ECAP may be evoked for therapeutic purposes, which in the case of a spinal cord stimulator for chronic pain may be to create paraesthesia at a desired location. To this end, the electrodes 2 and 4 are used to deliver stimuli periodically at any therapeutically suitable frequency, for example 30 Hz, although other frequencies may be used including frequencies as high as the kHz range. In alternative implementations, stimuli may be delivered in a non-periodic manner such as in bursts, or sporadically, as appropriate for the patient 108. To program the stimulator 100 to the patient 108, a clinician may cause the stimulator 100 to deliver stimuli of various configurations which seek to produce a sensation that is experienced by the user as paraesthesia. When a stimulus electrode configuration is found which evokes paraesthesia in a location and of a size which is congruent with the area of the patient's body affected by pain and of a quality that is comfortable for the patient, the clinician or the patient nominates that configuration for ongoing use. The therapy parameters may be loaded into the memory 118 of the stimulator 100 as the clinical settings 121.

[0046] FIG. 6 illustrates the typical form of an ECAP 600 of a healthy subject, as recorded at a single measurement electrode referenced to the system ground 130. The shape and duration of the single-ended ECAP 600 shown in FIG. 6 is predictable because it is a result of the ion currents produced by the ensemble of fibres depolarising and generating action potentials (APs) in response to stimulation. The evoked action potentials (EAPs) generated synchronously among a large number of fibres sum to form the ECAP 600. The ECAP 600 generated from the synchronous depolarisation of a group of similar fibres comprises a positive peak P1, then a negative peak N1, followed by a second positive peak P2. This shape is caused by the region of activation passing the measurement electrode as the action potentials propagate along the individual fibres.

[0047] The ECAP may be recorded differentially using two measurement electrodes, as illustrated in FIG. 3. Differential ECAP measurements are less subject to common-mode noise on the surrounding tissue than single-ended ECAP measurements. Depending on the polarity of recording, a differential ECAP may take an inverse form to that shown in FIG. 6, i.e. a form having two negative peaks NI and N2, and one positive peak PI. Alternatively, depending on the distance between the two measurement electrodes, a differential ECAP may resemble the time derivative of the ECAP 600, or more generally the difference between the ECAP 600 and a time-delayed copy thereof.

[0048] The ECAP 600 may be characterised by any suitable characteristic(s) of which some are indicated in FIG. 6. The amplitude of the positive peak P1 is Ap.sub.1 and occurs at time Tp.sub.1. The amplitude of the positive peak P2 is Ap.sub.2 and occurs at time Tp.sub.2. The amplitude of the negative peak P1 is An.sub.1 and occurs at time Tn.sub.1. The peak-to-peak amplitude is Ap.sub.1+An.sub.1. A recorded ECAP will typically have a maximum peak-to-peak amplitude in the range of microvolts and a duration of 2 to 3 ms.

[0049] The stimulator 100 is further configured to measure the intensity of ECAPs 170 propagating along nerve 180. whether such ECAPs are evoked by the stimulus from electrodes 2 and 4, or otherwise evoked. To this end, any electrodes of the array 150 may be selected by the electrode selection module 126 to serve as recording electrode 6 and reference electrode 8, whereby the electrode selection module 126 selectively connects the chosen electrodes to the inputs of the measurement circuitry 128. Thus, signals sensed by the measurement electrodes 6 and 8 subsequent to the respective stimuli are passed to the measurement circuitry 128, which may comprise a differential amplifier and an analog-to-digital converter (ADC), as illustrated in FIG. 3. The recording electrode and the reference electrode are referred to as the measurement electrode configuration. The measurement circuitry 128 for example may operate in accordance with the teachings of the above-mentioned International Patent Publication No. WO2012/155183.

[0050] Signals sensed by the measurement electrodes 6, 8 and processed by measurement circuitry 128 are further processed by an ECAP detector implemented within controller 116. configured by control programs 122, to obtain information regarding the effect of the applied stimulus upon the nerve 180. In some implementations. the sensed signals are processed by the ECAP detector in a manner which measures and stores one or more characteristics from each evoked neural response or group of evoked neural responses contained in the sensed signal. In one such implementation, the characteristics comprise a peak-to-peak ECAP amplitude in microvolts (?V). For example, the sensed signals may be processed by the ECAP detector to determine the peak-to-peak ECAP amplitude in accordance with the teachings of International Patent Publication No. WO2015/074121. the contents of which are incorporated herein by reference. Alternative implementations of the ECAP detector may measure and store an alternative characteristic from the neural response, or may measure and store two or more characteristics from the neural response.

[0051] Stimulator 100 applies stimuli over a potentially long period such as days, weeks, or months and during this time may store characteristics of neural responses, clinical settings, paraesthesia target level, and other operational parameters in memory 118. To effect suitable SCS therapy, stimulator 100 may deliver tens, hundreds or even thousands of stimuli per second, for many hours each day.

[0052] Each neural response or group of responses generates one or more characteristics such as a measure of the intensity of the neural response. Stimulator 100 thus may produce such data at a rate of tens or hundreds of Hz, or even kHz, and over the course of hours or days this process results in large amounts of clinical data 120 which may be stored in the memory 118. Memory 118 is however necessarily of limited capacity and care is thus required to select compact data forms for storage into the memory 118, to ensure that the memory 118 is not exhausted before such time that the data is expected to be retrieved wirelessly by external device 192, which may occur only once or twice a day, or less.

[0053] An activation plot, or growth curve, is an approximation to the relationship between stimulus intensity (e.g. an amplitude of the current pulse 160) and intensity of neural response 170 evoked by the stimulus (e.g. an ECAP amplitude). FIG. 4a illustrates an idealised activation plot 402 for one posture of the patient 108. The activation plot 402 shows a linearly increasing ECAP amplitude for stimulus intensity values above a threshold 404 referred to as the ECAP threshold. The ECAP threshold exists because of the binary nature of fibre recruitment; if the field strength is too low, no fibres will be recruited. However, once the field strength exceeds a threshold, fibres begin to be recruited, and their individual evoked action potentials are independent of the strength of the field. The ECAP threshold 404 therefore reflects the field strength at which significant numbers of fibres begin to be recruited, and the increase in response intensity with stimulus intensity above the ECAP threshold reflects increasing numbers of fibres being recruited. Below the ECAP threshold 404, the ECAP amplitude may be taken to be zero. Above the ECAP threshold 404, the activation plot 402 has a positive, approximately constant slope indicating a linear relationship between stimulus intensity and the ECAP amplitude. Such a relationship may be modelled as:

[00001] $\begin{matrix} y = {\begin{matrix} S (s - T), & s ? T \\ 0, & s < T \end{matrix}} & (1) \end{matrix}$

[0054] where s is the stimulus intensity, y is the ECAP amplitude, T is the ECAP threshold and Sis the slope of the activation plot (referred to herein as the patient sensitivity). The slope S and the ECAP threshold T are the key parameters of the activation plot 402.

[0055] FIG. 4a also illustrates a discomfort threshold 408, which is a stimulus intensity above which the patient 108 experiences uncomfortable or painful stimulation. FIG. 4a also illustrates a perception threshold 410. The perception threshold 410 corresponds to an ECAP amplitude that is barely perceptible by the patient. There are a number of factors which can influence the position of the perception threshold 410, including the posture of the patient. Perception threshold 410 may correspond to a stimulus intensity that is greater than the ECAP threshold 404, as illustrated in FIG. 4a. if patient 108 does not perceive low levels of neural activation. Conversely, the perception threshold 410 may correspond to a stimulus intensity that is less than the ECAP threshold 404, if the patient has a high perception sensitivity to lower levels of neural activation than can be detected in an ECAP, or if the signal to noise ratio of the ECAP is low.

[0056] For effective and comfortable operation of an implantable neuromodulation device such as the stimulator 100, it is desirable to maintain stimulus intensity within a therapeutic range. A stimulus intensity within a therapeutic range 412 is above the ECAP threshold 404 and below the discomfort threshold 408. In principle, it would be straightforward to measure these limits and ensure that stimulus intensity, which may be closely controlled, always falls within the therapeutic range 412. However, the activation plot, and therefore the therapeutic range 412, varies with the posture of the patient 108.

[0057] FIG. 4b illustrates the variation in the activation plots with changing posture of the patient. A change in posture of the patient may cause a change in impedance of the electrode-tissue interface or a change in the distance between electrodes and the neurons. While the activation plots for only three postures, 502, 504 and 506, are shown in FIG. 4b, the activation plot for any given posture can lie between or outside the activation plots shown, on a continuously varying basis depending on posture. Consequently, as the patient's posture changes, the ECAP threshold changes, as indicated by the ECAP thresholds 508, 510, and 512 for the respective activation plots 502, 504, and 506. Additionally, as the patient's posture changes, the slope of the activation plot also changes, as indicated by the varying slopes of activation plots 502, 504, and 506. In general, as the distance between the stimulus electrodes and the spinal cord increases, the ECAP threshold increases and the slope of the activation plot decreases. The activation plots 502, 504, and 506 therefore correspond to increasing distance between stimulus electrodes and spinal cord, and decreasing patient sensitivity. The posture corresponding to the activation plot 502 may be said to be the most sensitive, while the posture corresponding to the activation plot 506 may be said to be the least sensitive.

[0058] To keep the applied stimulus intensity within the therapeutic range as patient posture varies. in some implementations an implantable neuromodulation device such as the stimulator 100 may adjust the applied stimulus intensity based on a feedback variable that is determined from one or more measured ECAP characteristics. In one implementation, the device may adjust the stimulus intensity to maintain the measured ECAP amplitude at a target response intensity. For example, the device may calculate an error between a target ECAP amplitude and a measured ECAP amplitude, and adjust the applied stimulus intensity to reduce the error as much as possible, such as by adding the scaled error to the current stimulus intensity. A neuromodulation device that operates by adjusting the applied stimulus intensity based on an measured ECAP characteristic is said to be operating in closed-loop mode and will also be referred to as a closed-loop neural stimulation (CLNS) device. By adjusting the applied stimulus intensity to maintain the measured ECAP amplitude at an appropriate target response intensity, such as a target ECAP amplitude 520 illustrated in FIG. 4b, a CLNS device will generally keep the stimulus intensity within the therapeutic range as patient posture varies.

[0059] A CLNS device comprises a stimulator that takes a stimulus intensity value and converts it into a neural stimulus comprising a sequence of electrical pulses according to a predefined stimulation pattern. The stimulation pattern is parametrised by multiple stimulus parameters including stimulus amplitude, pulse width, number of phases, order of phases, number of stimulus electrode poles (two for bipolar, three for tripolar etc.), and stimulus rate or frequency. At least one of the stimulus parameters, for example the stimulus amplitude, is controlled by the feedback loop.

[0060] In an example CLNS system, a user (e.g. the patient or a clinician) sets a target response intensity, and the CLNS device performs proportional-integral-differential (PID) control. In some implementations, the differential contribution is disregarded and the CLNS device uses a first order integrating feedback loop. The stimulator produces stimulus in accordance with a stimulus intensity parameter, which evokes a neural response in the patient. The intensity of an evoked neural response (e.g. an ECAP) is measured by the CLNS device and compared to the target response intensity.

[0061] The measured neural response intensity, and its deviation from the target response intensity. is used by the feedback loop to determine possible adjustments to the stimulus intensity parameter to maintain the neural response at the target intensity. If the target intensity is properly chosen, the patient receives consistently comfortable and therapeutic stimulation through posture changes and other perturbations to the stimulus/response behaviour.

[0062] FIG. 5 is a schematic illustrating elements and inputs of a closed-loop neural stimulation (CLNS) system 300, according to one implementation of the present technology. The system 300 comprises a stimulator 312 which converts a stimulus intensity parameter (for example a stimulus current amplitude) s, in concert with a set of predefined stimulus parameters, to a neural stimulus comprising a sequence of electrical pulses on the stimulus electrodes (not shown in FIG. 5). According to one implementation, the predefined stimulus parameters comprise the number and order of phases. the number of stimulus electrode poles, the pulse width, and the stimulus rate or frequency.

[0063] The generated stimulus crosses from the electrodes to the spinal cord, which is represented in FIG. 5 by the dashed box 308. The box 309 represents the evocation of a neural response y by the stimulus as described above. The box 311 represents the evocation of an artefact signal ?, which is dependent on stimulus intensity and other stimulus parameters, as well as the electrical environment of the measurement electrodes. Various sources of measurement noise n, as well as the artefact ?, may add to the evoked response y at the summing element 313 to form the sensed signal r, including: electrical noise from external sources such as 50 Hz mains power: electrical disturbances produced by the body such as neural responses evoked not by the device but by other causes such as peripheral sensory input: EEG: EMG: and electrical noise from measurement circuitry 318.

[0064] The neural recruitment arising from the stimulus is affected by mechanical changes, including posture changes, walking, breathing, heartbeat and so on. Mechanical changes may cause impedance changes, or changes in the location and orientation of the nerve fibres relative to the electrode array(s). As described above, the intensity of the evoked response provides a measure of the recruitment of the fibres being stimulated. In general, the more intense the stimulus, the more recruitment and the more intense the evoked response. An evoked response typically has a maximum amplitude in the range of microvolts, whereas the voltage resulting from the stimulus applied to evoke the response is typically several volts.

[0065] Measurement circuitry 318, which may be identified with measurement circuitry 128, amplifies the sensed signal r (including evoked neural response, artefact, and measurement noise), and samples the amplified sensed signal r to capture a signal window 319 comprising a predetermined number of samples of the amplified sensed signal r. The ECAP detector 320 processes the signal window 319 and outputs a measured neural response intensity d. In one implementation. the neural response intensity comprises a peak-to-peak ECAP amplitude. The measured response intensity d is input into the feedback controller 310. The feedback controller 310 comprises a comparator 324 that compares the measured response intensity d (an example of a feedback variable) to a target ECAP amplitude as set by the target ECAP controller 304 and provides an indication of the difference between the measured response intensity d and the target ECAP amplitude. This difference is the error value, e.

[0066] The feedback controller 310 calculates an adjusted stimulus intensity parameter, s, with the aim of maintaining a measured response intensity d equal to the target ECAP amplitude. Accordingly, the feedback controller 310 adjusts the stimulus intensity parameter s to minimise the error value, e. In one implementation, the controller 310 utilises a first order integrating function, using a gain element 336 and an integrator 338, in order to provide suitable adjustment to the stimulus intensity parameter s. According to such an implementation, the current stimulus intensity parameter s may be determined by the feedback controller 310 as

s=?Kedt(2)

[0067] where K is the gain of the gain element 336 (the controller gain). This relation may also be represented as

?s=Ke(3)

[0068] where ?s is an adjustment to the current stimulus intensity parameter s.

[0069] A target ECAP amplitude is input to the feedback controller 310 via the target ECAP controller 304. In one embodiment, the target ECAP controller 304 provides an indication of a specific target ECAP amplitude. In another embodiment, the target ECAP controller 304 provides an indication to increase or to decrease the present target ECAP amplitude. The target ECAP controller 304 may comprise an input into the CLNS system 300, via which the patient or clinician can input a target ECAP amplitude, or indication thereof. The target ECAP controller 304 may comprise memory in which the target ECAP amplitude is stored, and from which the target ECAP amplitude is provided to the feedback controller 310.

[0070] A clinical settings controller 302 provides clinical settings to the system 300, including the feedback controller 310 and the stimulus parameters for the stimulator 312 that are not under the control of the feedback controller 310. In one example, the clinical settings controller 302 may be configured to adjust the controller gain K of the feedback controller 310 to adapt the feedback loop to patient sensitivity. The clinical settings controller 302 may comprise an input into the CLNS system 300, via which the patient or clinician can adjust the clinical settings. The clinical settings controller 302 may comprise memory in which the clinical settings are stored, and are provided to components of the system 300.

[0071] In some implementations, two clocks (not shown) are used, being a stimulus clock operating at the stimulus frequency (e.g. 60 Hz) and a sample clock for sampling the sensed signal r (for example, operating at a sampling frequency of 16 kHz). As the ECAP detector 320 is linear, only the stimulus clock affects the dynamics of the CLNS system 300. On the next stimulus clock cycle, the stimulator 312 outputs a stimulus in accordance with the adjusted stimulus intensity s. Accordingly, there is a delay of one stimulus clock cycle before the stimulus intensity is updated in light of the error value e.

[0072] FIG. 7 is a block diagram of a neural stimulation system 700. The neural stimulation system 700 is centred on a neuromodulation device 710. In one example, the neuromodulation device 710 may be implemented as the stimulator 100 of FIG. 1, implanted within a patient (not shown). The neuromodulation device 710 is connected wirelessly to a remote controller (RC) 720. The remote controller 720 is a portable computing device that provides the patient with control of their stimulation in the home environment by allowing control of the functionality of the neuromodulation device 710, including one or more of the following functions: enabling or disabling stimulation: adjustment of stimulus intensity or target response intensity; and selection of a stimulation control program from the control programs stored on the neuromodulation device 710.

[0073] The charger 750 is configured to recharge a rechargeable power source of the neuromodulation device 710. The recharging is illustrated as wireless in FIG. 7 but may be wired in alternative implementations.

[0074] The neuromodulation device 710 is wirelessly connected to a Clinical System Transceiver (CST) 730. The wireless connection may be implemented as the transcutaneous communications channel 190 of FIG. 1. The CST 730 acts as an intermediary between the neuromodulation device 710 and the Clinical Interface (CI) 740, to which the CST 730 is connected. A wired connection is shown in FIG. 7, but in other implementations, the connection between the CST 730 and the CI 740 is wireless.

[0075] The CI 740 may be implemented as the external computing device 192 of FIG. 1. The CI 740 is configured to program the neuromodulation device 710 and recover data stored on the neuromodulation device 710. This configuration is achieved by program instructions collectively referred to as the Clinical Programming Application (CPA) and stored in an instruction memory of the CI 740.

[0076] Assisted Programming System

[0077] As mentioned above, obtaining patient feedback about their sensations is important during programming of closed-loop neural stimulation therapy, but mediation by trained clinical engineers is expensive and time-consuming. It would therefore be advantageous if patients could program their own implantable device themselves, or with some assistance from a clinician. However, interfaces for current programming systems are non-intuitive and generally unsuitable for direct use by patients because of their technical nature. There is therefore a need for a CPA to be as intuitive for non-technical users as possible while avoiding discomfort to the patient. Implementations of an Assisted Programming System (APS) according to the present technology are generally configured to meet this need.

[0078] In some implementations, the APS comprises two elements: the Assisted Programming Module (APM), which forms part of the CPA, and the Assisted Programming Firmware (APF), which forms part of the control programs 122 executed by the controller 116 of the electronics module 110. The data obtained from the patient is analysed by the APM to determine the clinical settings for the neural stimulation therapy to be delivered by the stimulator 100. The APF is configured to complement the operation of the APM by responding to commands issued by the APM via the CST 730 to the stimulator 100 to deliver specified stimuli to the patient, and by returning, via the CST 730, measurements of neural responses to the delivered stimuli.

[0079] In other implementations, all the processing of the APS according to the present technology is done by the APF. In other words, the data obtained from the patient is not passed to the APM, but is analysed by the controller 116 of the device 710, configured by the APF, to determine the clinical settings for the neural stimulation therapy to be delivered by the stimulator 100.

[0080] In implementations of the APS in which the APM analyses the data from the patient, the APS instructs the device 710 to capture and return signal windows to the CI 740 via the CST 730. In such implementations, the device 710 captures the signal windows using the measurement circuitry 128 and bypasses the ECAP detector 320, storing the data representing the raw signal windows temporarily in memory 118 before transmitting the data representing the captured signal windows to the APS for analysis.

[0081] Following the programming, the APS may load the determined program onto the device 710 to govern subsequent neural stimulation therapy. In one implementation, the program comprises clinical settings 121, also referred to as therapy parameters, that are input to the neuromodulation device 710 by, or stored in, the clinical settings controller 302. The patient may subsequently control the device 710 to deliver the therapy according to the determined program using the remote controller 720 as described above. The determined program may also, or alternatively, be loaded into the CPA for validation and modification.

[0082] Estimating the out-of-compliance current limit

[0083] FIG. 8 contains a model 800 of the Electrode-Tissue-Electrode Interface of an implanted neuromodulation device. The model 800 represents the load impedance Z seen by a current source 820 forming part of the pulse generator of a stimulator. The load impedance Z is dominated by the resistance of the tissue (modelled by the resistor mesh 830). The polarisation that occurs at the electrode-tissue interface is represented by the constant phase elements (CPEs) joining the mesh to the current source 820, e.g. the CPE 810. To simplify this analysis, the impedance of the CPEs has been excluded. The resistor mesh 830 in the model 800 may be approximated as a star network, as illustrated in FIG. 9. Each load resistance, e.g. the load resistance 910, in the star network 920 is the resistance to the star point 930 from the corresponding electrode, e.g. the electrode E1. The star point 930 represents a point in the tissue far distant from the electrode, so the resistance to the star point may be referred to as the resistance to infinity of the electrode. The star network model 920 of FIG. 9 loses accuracy as a model of the mesh 830 when the electrodes are physically close to one another due to field overlap.

[0084] To estimate the resistance to infinity of an electrode under test, a predetermined current may be sourced from the electrode under test and returned to ground on all other electrodes, which have first been connected together. When the current is flowing, the voltage difference between the electrode under test and the other electrodes may be measured. The measured impedance, computed as the ratio of the voltage difference and the predetermined current, is an acceptable estimate of the resistance to infinity (electrode resistance) from the electrode under test provided the number of other electrodes is large enough that the measured impedance is dominated by the resistance to infinity of the electrode under test. This condition is satisfied for an electrode array with sixteen electrodes, as is commonly used in a neuromodulation device.

[0085] FIG. 10 is a simplified circuit representation 1000 of a neuromodulation device configured to source a current from the supply voltage rail V.sub.DDHV to tissue via current sources 1020-1 and 1020-2 and a pair of stimulus electrodes, and return the current from the tissue via a pair of return electrodes connected to ground (a sourcing configuration). The point 1010 is the star point of the star network model 920 of tissue illustrated in FIG. 9. The stimulus electrodes have respective electrode resistances of S.sub.1 and S.sub.2, while the return electrodes have respective electrode resistances of R.sub.1 and R.sub.2. The return electrode resistances R.sub.1 and R.sub.2, being in parallel, can be combined into to a single equivalent return electrode resistance R.sub.T:

[00002] $\begin{matrix} R_{T} = \frac{1}{\frac{1}{R_{1}} + \frac{1}{R_{2}}} & (4) \end{matrix}$

[0086] The device has a total stimulus current output that is divided across all the stimulus electrodes according to some predetermined ratio. In FIG. 10, the stimulus current through the tissue is divided between the two current sources 1020-1 and 1020-2 according to respective fractions ?.sub.1 and ?.sub.2 whose sum is unity. The fractions ?.sub.1 and ?.sub.2 are stimulus parameters.

[0087] The current source 1020-x (where x is 1 or 2) goes out of compliance when the voltage across it falls to zero. This occurs at an out-of-compliance current limit I.sub.OOC, which satisfies the equation

V.sub.DDHV=?.sub.xI.sub.OOCS.sub.x+I.sub.OOCR.sub.T(5)

[0088] From Equation (5), the out-of-compliance current limit I.sub.OOC for the stimulus electrode x may be computed as

[00003] $\begin{matrix} I_{OOC} = \frac{V_{DDHV}}{?_{x} S_{x} + R_{T}} & (6) \end{matrix}$

[0089] The APM or the APF, or some combination thereof, may estimate the electrode resistances of the respective electrodes of a given stimulus electrode configuration (SEC) in the manner described above. The APM or the APF, or some combination thereof, may then substitute the estimated electrode resistances, along with values for V.sub.DDHV and the stimulus parameter ax, into equations (4) and (6) to estimate the out-of-compliance current limit I.sub.OOC for each stimulus electrode x of the given SEC. This model works best when there is a large separation between the stimulus electrode(s) and the return electrode(s), but tests carried out using a saline bath to model the tissue have shown that the limit obtained by using the estimated electrode impedances and equation (6) is sufficiently accurate in most circumstances.

[0090] An equivalent simplified circuit representation to the circuit representation 1000 may be constructed for a neuromodulation device configured to sink a current from tissue to ground via two current sinks and a pair of stimulus electrodes, and return the current to the tissue via a pair of return electrodes connected to the supply voltage rail V.sub.DDHV (a sinking configuration). Because of the equivalence of this representation of the sinking configuration to the representation 1000 of a sourcing configuration, the same equations (4) and (6) may be used to estimate the out-of-compliance current limit I.sub.OOC for the sinking configuration for each stimulus electrode x of the given SEC. Therefore, if the neuromodulation device is configured to toggle between the sourcing and sinking configurations over the phases of a multi-phasic stimulus pulse, the out-of-compliance current limit I.sub.OOC is the same for each phase and therefore need only be estimated once for each stimulus electrode x of the given SEC.

[0091] Estimating the closed-loop current requirement

[0092] In a CLNS system, the stimulus current varies in order to maintain the measured neural response intensity at the target ECAP amplitude. The stimulus current required to maintain the measured neural response intensity at the target ECAP amplitude varies with posture, becoming generally greater as the posture becomes less sensitive. The maximum stimulus current required to maintain the measured neural response intensity at a comfortable target ECAP amplitude in the least sensitive posture is referred to herein as the closed-loop current requirement (I.sub.CLC). In order for the patient to receive the full benefit of the CLNS therapy, the closed-loop current requirement (I.sub.CLC) at a comfortable target ECAP amplitude should be less than the out-of-compliance current limit I.sub.OOC.

[0093] FIG. 11 is a graph 1100 showing (as points) the maximum stimulus current produced by the stimulator of a CLNS device at a comfortable target ECAP amplitude over all postures for a number of patients, i.e. the closed-loop current requirement (I.sub.CLC). Each value of the closed-loop current requirement I.sub.CLC is plotted against the ECAP threshold T.sub.LS in the least sensitive posture for that patient. The curve 1110 represents a power law function y=Cx.sup.? fit to the (T.sub.LS. I.sub.CLC) value pairs such that 98% of the I.sub.CLC values fall below the curve 1110. Hence the equation

I.sub.CLC=CT.sub.LS.sup.?(7)

[0094] where ? is a power law parameter with a value in the range 0.0 to 1.0, in the range 0.2 to 0.9, in the range 0.3 to 0.8, or in the range 0.5 to 0.7, and Cis a constant in the range 5 to 50, or in the range 10 to 40, or in the range 15 to 35, represents a conservative (high-sided) estimate of the closed-loop current requirement I.sub.CLC as a function of the least-sensitive-posture ECAP threshold T.sub.LS. A similar model, with different parameter values, may be fit to values of the closed-loop current requirement I.sub.CLC as a function of the ECAP threshold T.sub.LS in other predetermined postures for that patient.

[0095] FIG. 12 is a flow chart illustrating a method 1200 of pre-emptively mitigating the risk of out-of-compliance events according to one aspect of the present technology. The method 1200 may be carried out during programming of a neuromodulation device 710 for CLNS therapy by the APM, the APF, or a combination of both as described above.

[0096] The method 1200 starts at step 1210, which measures the electrode resistances of the stimulus electrode(s) and return electrode(s) of the current SEC specified by the current therapy parameters. Step 1220 then applies equation (6), and possibly equation (4) if there is more than one return electrode in the SEC, to estimate the out-of-compliance current limit I.sub.OOC or for each stimulus electrode in the SEC.

[0097] The method 1200 then proceeds to step 1230, which measures the ECAP threshold T.sub.LS of the patient in the least sensitive posture. Methods of measuring the ECAP threshold are disclosed in, for example, the above-mentioned International Patent Publication No. WO2012/155188, the contents of which are herein incorporated by reference. Step 1240) then estimates the closed-loop current requirement I.sub.CLC of the patient from the least-sensitive-posture ECAP threshold Tis and Equation (7). Step 1250 then checks whether the closed-loop current requirement I.sub.CLC of the patient exceeds the out-of-compliance current limit I.sub.OOC for any stimulus electrode in the current SEC according to the current therapy parameters. If not (N), the risk of an out-of-compliance event is low, and the method 1200 ends (step 1260). If so (Y), there is a significant risk of an out-of-compliance event during CLNS therapy using the current therapy parameters. Step 1270 therefore takes an action to pre-emptively mitigate the risk. If step 1270 adjusts the therapy parameters, the method 1200 may then return to step 1210 to predict and possibly further mitigate any residual risk of out-of-compliance events with the new therapy parameters.

[0098] In some implementations, the mitigation action of step 1270 is simply to raise an indication to a user of the CPA that there is a risk of an out-of-compliance event. The user may then take whatever steps they deem suitable to mitigate that risk.

[0099] In some implementations of step 1270, the risk of out-of-compliance events is mitigated by increasing the out-of-compliance current limit I.sub.OOC. In one such implementation, an alternative stimulus electrode configuration may be selected. In one example, more return electrodes are added to the SEC, and/or alternative return electrodes with lower electrode resistances are selected, to reduce the equivalent return electrode resistance R.sub.T and thereby increase I.sub.OOC. Alternatively or additionally, an alternative stimulus electrode with a lower electrode resistance may be selected to replace the stimulus electrode whose electrode resistance is causing its out-of-compliance current limit I.sub.OOC to exceed the closed-loop current requirement I.sub.CLC of the patient in the current SEC.

[0100] In other implementations of step 1270, the risk of out-of-compliance events is mitigated by decreasing the patient's closed-loop current requirement I.sub.CLC. Such implementations may be combined with, or employed as an alternative to, implementations which increase the out-of-compliance current limit I.sub.OOC as described above. In one such implementation, the stimulus pulse width may be increased to decrease the patient's closed-loop current requirement I.sub.CLC. There is a relationship between the pulse width and the ECAP threshold T in a given posture such that increasing the stimulus pulse width generally decreases the ECAP threshold T. Therefore, in such an implementation, step 1270) may increase the stimulus pulse width by a small amount, say 80 ?s, and the method 1200 may return to step 1230 to re-measure the ECAP threshold Tus in the least sensitive posture, and continue with steps 1240 to 1270.

[0101] Alternatively, to avoid having to re-measure the ECAP threshold, population statistics may be used to select an appropriate pulse width to mitigate the risk of OOC events during CLNS therapy.

[0102] FIG. 13 is a graph 1300 containing two distributions 1310, 1320 of measured least-sensitive-posture ECAP thresholds Tis at two different pulse widths pw1 and pw2, where pw1 <pw2. Also shown on each distribution is the 90th-percentile value of T.sub.LS, written as T.sub.LS(pw1, 90) and T.sub.LS(pw2, 90). Tus(pw1, 90) is the value below which 90% of patients' least-sensitive-posture thresholds T.sub.LS lie when stimulated at the pulse width pw1. The shaded area 1330 therefore represents 10% of the total area under the distribution 1310. It may be seen that increasing the pulse width from pw1 to pw2 compresses the distribution of Tus and thereby decreases the 90th percentile value of T.sub.LS from T.sub.LS(pw1, 90) to T.sub.LS(pw2, 90). Using such population statistics, a model T.sub.LS(pw, P) may be constructed allowing T.sub.LS to be estimated for any values of pw and P within certain ranges. The model T.sub.LS(pw, P) will be monotonic with respect to both pw and P within certain ranges.

[0103] Equation (7) may then be applied to the estimated value of T.sub.LS to estimate the closed-loop current requirement I.sub.CLC of the patient for any values of pw and P within certain ranges.

[0104] Step 1270 may therefore choose a near-unity value of P and apply the model T.sub.LS(pw, P) together with Equation (7) to find a pulse width such the closed-loop current requirement I.sub.CLC of the patient is likely to be less than the out-of-compliance current limit I.sub.OOC. For example, if P is set to 95%, a value of pulse width may be selected such that there is only a 1 in 20 (1-P) chance that the closed-loop current requirement I.sub.CLC of the patient will exceed the out-of-compliance current limit I.sub.OOC.

[0105] In an alternative implementation, the ECAP threshold need not be measured at all. Instead, the population statistics may be used to prospectively set the stimulus parameters, in particular the pulse width, to mitigate the risk of OOC events during neural stimulation programming or therapy. FIG. 14 is a flow chart illustrating a method 1400 of pre-emptively mitigating the risk of out-of-compliance events in a neural stimulation device according to such an implementation of the present technology. The method 1400 may be carried out during programming of a neuromodulation device by the APM, the APF, or a combination of both as described above.

[0106] The method 1400 starts at step 1410, which measures the electrode resistances of the stimulus electrode(s) and return electrode(s) of the current SEC specified by the current therapy parameters. Step 1420 then applies equation (6), and possibly equation (4) if there is more than one return electrode in the SEC, to estimate the out-of-compliance current limit I.sub.OOC for each stimulus electrode in the SEC.

[0107] The method 1400 then proceeds to step 1430, which uses population statistics to choose one or more stimulus parameters such that the out-of-compliance current limit I.sub.OOC is likely to exceed a maximum stimulus current expected to be used during neural stimulation device programming or therapy. In one implementation, suitable for closed-loop neural stimulation devices, the maximum stimulus current is the closed-loop current requirement I.sub.CLC for closed-loop neural stimulation therapy. In such an implementation, step 1430 uses a model of I.sub.CLC as a function of percentile and pulse width to select a pulse width such that the out-of-compliance current limit I.sub.OOC is likely to exceed the closed-loop current requirement I.sub.CLC. For example, if I.sub.OOC is equal to 20 mA, step 1430 may set P to 95% and thereby select a pulse width such that there is only a 1 in 20 chance that the closed-loop current requirement I.sub.CLC of the patient will exceed 20 mA.

[0108] In other implementations, step 1430 uses population statistics to choose one or more stimulus parameters such that the out-of-compliance current limit I.sub.OOC is likely to exceed a maximum stimulus current expected to be used during programming a neural stimulation device, whether the device is closed-loop or open-loop. In one example, programming a neural stimulation device comprises ramping stimulus intensity to a patient's discomfort threshold, which is not known in advance. In such an example, the maximum stimulus current is the discomfort threshold, and step 1430 may use population statistics about discomfort thresholds at different pulse widths to infer a pulse width at which I.sub.OOC is likely to exceed the discomfort threshold. In other examples of step 1430, population statistics of discomfort thresholds in relation to parameters other than pulse width that influence discomfort threshold may be used to set a value for such parameters at which I.sub.OOC is likely to exceed the discomfort threshold.

[0109] It will be appreciated by persons skilled in the art that numerous variations and/or modifications may be made to the invention as shown in the specific embodiments without departing from the spirit or scope of the invention as broadly described. The present embodiments are, therefore, to be considered in all respects as illustrative and not limiting or restrictive.

TABLE-US-00001 LABEL LIST stimulator 100 patient 108 electronics module 110 battery 112 telemetry module 114 controller 116 memory 118 clinical data 120 clinical settings 121 control programs 122 pulse generator 124 electrode selection module 126 measurement circuitry 128 system ground 130 electrode array 150 biphasic stimulus pulse 160 neural response 170 nerve 180 communications channel 190 external computing device 192 system 300 clinical settings controller 302 target ECAP controller 304 box 308 box 309 controller 310 box 311 stimulator 312 element 313 measurement circuitry 318 signal window 319 ECAP detector 320 comparator 324 gain element 336 integrator 338 activation plot 402 ECAP threshold 404 discomfort threshold 408 perception threshold 410 therapeutic range 412 activation plot 502 activation plot 504 activation plot 506 ECAP threshold 508 ECAP threshold 510 ECAP threshold 512 ECAP target 520 ECAP 600 neural stimulation system 700 device 710 remote controller 720 CST 730 CI 740 charger 750 model 800 CPE 810 current source 820 resistor mesh 830 load resistance 910 star network 920 star point 930 circuit representation 1000 current source 1020 - 1 current source 1020 - 2 current source 1020 - x point 1010 graph 1100 curve 1110 method 1200 step 1210 step 1220 step 1230 step 1240 step 1250 step 1260 step 1270 graph 1300 distribution 1310 distribution 1320 area 1330 method 1400 step 1410 step 1420 step 1430

Devices and Methods for Stimulating Neural Tissue

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Abstract

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