Determining parameters for sensing ECAP signals

Abstract

Systems, devices, and techniques are described for sensing signals from a patient using fractional contributions of at least one polarity of sensing electrodes. In one example, a system includes sensing circuitry configured to generate a sensed signal and processing circuitry configured to select a plurality of electrode combinations for sensing the one or more sensed signals, wherein the plurality of electrode combinations include one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity, and determine fractional contributions for each electrode combination for sensing the one or more sensed signals. The processing circuitry can receive information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations, and generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

Description

DETERMINING PARAMETERS FOR SENSING ECAP SIGNALSTECHNICAL FIELD

[0001] This disclosure generally relates to electrical stimulation, and more specifically, programming sensing for electrical stimulation.BACKGROUND

[0002] Medical devices may be external or implanted and may be used to deliver electrical stimulation therapy to patients via various tissue sites to treat a variety of symptoms or conditions such as chronic pain, tremor, Parkinson’s disease, epilepsy, urinary or fecal incontinence, sexual dysfunction, obesity, or gastroparesis. A medical device may deliver electrical stimulation therapy via one or more leads that include electrodes located proximate to target locations associated with the brain, the spinal cord, pelvic nerves, peripheral nerves, or the gastrointestinal tract of a patient. Stimulation proximate the spinal cord, proximate the sacral nerve, within the brain, and proximate peripheral nerves are often referred to as spinal cord stimulation (SCS), sacral neuromodulation (SNM), deep brain stimulation (DBS), and peripheral nerve stimulation (PNS), respectively.

[0003] Electrical stimulation may be delivered to a patient by the medical device in a train of electrical pulses, and parameters of the electrical pulses may include a frequency, an amplitude, a pulse width, and a pulse shape. An evoked compound action potential (ECAP) is synchronous firing of a population of neurons which occurs in response to the application of a stimulus including, in some cases, an electrical stimulus by a medical device. The ECAP may be detectable as being a separate event from the stimulus itself, and the ECAP may reveal characteristics of the effect of the stimulus on the nerve fibers.SUMMARY

[0004] In general, systems, devices, and techniques are described for determining a sensing electrode combination, fractional contributions of each electrode when sensing a signal from the sensing electrode combination, and / or other sensing parameters that enable a system to sense a physiological signal from a patient (e.g., an evoked compound action potential (ECAP) signal). For example, the system may determine and utilize fractional contributions from at least some sensing electrodes in order to aligning sensing electrodes to one or more components of the ECAP signal. An electrical signal of a patient may be detected by sensing a voltage difference between two electrodes. These two electrodes may be referenced has having different, or opposite, polarities because the electrical potential between the electrodes is used as the basis forthe sensed signal. Propagating signals may pass by the sense electrodes in a wave, and the potential over time between the electrodes is used to generate the sensed signal that can be output over time, e.g., a voltage over time. However, if the maximum potential difference of the signal, such as a peak to a trough in an ECAP, does not align with the two sense electrodes, the system may not be able to detect the actual maximum difference in the signal.

[0005] The system may test different electrodes and different fractional contributions from these electrodes in order to identify a sensing electrode combination (or sensing electrode combinations) and fractional contributions from two or more of the electrodes that can align one or more features of a physiological signal to the sensing electrodes. The result of these fractionalized contributions may be referred to as using a “virtual” electrode because the composite signal is reflective of the position of an electrode that is not physically at that location. The system may use the fractional contributions to weight multiple signals sensed from respective electrode combinations and respective stimuli delivered close in time. Alternatively, the system may sense the signal using the multiple electrode combinations at the same time but sensed through respective amplifier circuits for later fractionalizing each signal sensed at the same time. With respect to an ECAP signal, the fractional contributions may be selected in order to improve the signal to noise ratio by capturing as large of electrical potentials as possible from the available electrodes. The fractional contributions may be acquired using hardware that acquires proportional signals from each electrode of the same polarity in the sensing electrode combination or using post processing from multiple sensed signals. The system may use the fractional contributions to acquire ECAP signals that can be used by the system as feedback for controlling subsequently delivered electrical stimulation. In some examples, the system may perform the fractional contribution technique over time to identify changes to the sensed signal and determine, from any changes, various changes to the patient such as lead migration and / or changes to disease state.

[0006] In one example, this disclosure describes a system that includes sensing circuitry configured to generate one or more sensed signals; and processing circuitry configured to select a plurality of electrode combinations for sensing the one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determine fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receive information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

[0007] In another example, this disclosure describes a method that includes selecting, by processing circuitry, a plurality of electrode combinations for sensing, by sensing circuitry one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determining, by the processing circuitry, fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receiving, by the processing circuitry, information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generating, by the processing circuitry, a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

[0008] In another example, this disclosure describes a non-transitory computer-readable medium including instructions that, when executed, control processing circuitry to: select a plurality of electrode combinations for sensing, by sensing circuitry, one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determine fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receive information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

[0009] The summary is intended to provide an overview of the subject matter described in this disclosure. It is not intended to provide an exclusive or exhaustive explanation of the systems, device, and methods described in detail within the accompanying drawings and description below. Further details of one or more examples of this disclosure are set forth in the accompanying drawings and in the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.BRIEF DESCRIPTION OF DRAWINGS

[0010] FIG. l is a conceptual diagram illustrating an example system that includes an implantable medical device (IMD) configured to deliver spinal cord stimulation (SCS) therapy and an external programmer.

[0011] FIG. 2 is a block diagram illustrating an example configuration of components of the IMD of FIG. 1.

[0012] FIG. 3 is a block diagram illustrating an example configuration of components of an example external programmer.

[0013] FIG. 4 is a graph of example evoked compound action potentials (ECAPs) sensed for respective stimulation pulses.

[0014] FIG. 5 is a conceptual diagram of an example ECAP signal superimposed to an example lead carrying a plurality of electrodes.

[0015] FIG. 6 is an example user interface configured to display sense electrode configurations and fractional contributions from each sense electrode to a sensed signal.

[0016] FIG. 7 is a flow diagram illustrating an example technique for determining a fractional contributions for each electrode of a sense electrode combination.

[0017] FIG. 8 is a flow diagram illustrating an example testing different sense electrodes and fractional contributions from each electrode for determining a sense electrode combination for sensing subsequent signals from a patient.

[0018] FIG. 9 is a flow diagram illustrating an example technique for determining an ECAP threshold and controlling electrical stimulation using an ECAP characteristic of the ECAP signal.

[0019] FIG. 10 is a flow diagram illustrating an example technique for tracking any changes to patient sensing over time.DETAILED DESCRIPTION

[0020] The disclosure describes examples of medical devices, systems, and techniques for determining a sensing electrode combination, fractional contributions of each electrode when sensing a signal from the sensing electrode combination, and / or other sensing parameters that enable a system to sense a physiological signal from a patient (e.g., an evoked compound action potential (ECAP) signal). A system can then leverage the sensed signal as feedback for selecting one or more stimulation parameter values that define subsequent stimulation. Electrical stimulation therapy is typically delivered to a target tissue (e.g., nerves of the spinal cord or muscle) of a patient via two or more electrodes. Parameters of the electrical stimulation therapy (e.g., electrode combination, voltage or current amplitude, pulse width, pulse frequency, etc.) are selected by a clinician and / or the patient to provide relief from various symptoms, such as pain, systems from nervous system disorders, symptoms from muscle disorders, etc. Various thresholds, such as a perception threshold and / or discomfort threshold, associated with patient feedback on stimulation may be determined for the patient and used to select and / or recommend parameters of the stimulation therapy.

[0021] Physiological signals can be used as feedback to select or adjust stimulation parameters that define the stimulation therapy. In one example, ECAPs can be used as feedback because ECAPs are a measure of neural recruitment. Each ECAP signal represents the superposition of electrical potentials generated from a population of axons (or nerves) firing inresponse to an electrical stimulus (e.g., a stimulation pulse). Changes to a characteristic (e.g., an amplitude of a portion of the signal or area under the curve of the signal) of an ECAP signal occurs as a function of how many axons have been activated by the delivered stimulation pulse. For a given set of parameter values that define the stimulation pulse and a given distance between the electrodes and target nerve, the detected ECAP signal may have a certain characteristic value (e.g., amplitude).

[0022] However, these characteristics of the ECAP signal may not be detected as well as they could be given implanted electrode positioning. An ECAP signal includes a series of peaks and troughs representative of the number of nerves activated by the delivered stimulus. The conduction velocity of the volume of activated nerves determines the timing and width of the peaks and troughs of an ECAP signal and when electrodes can detect these peaks and troughs. For a consistent volume of nerves, such as in the case of dorsal column nerves under an epidural SCS lead, the conduction velocity should remain relatively consistent. Therefore, there will be a consistent distance between the peaks and troughs of the wave during depolarization and repolarization. Although the distance (and timing) between the peaks and troughs (or any components of the ECAP signal) may remain constant, these peaks and / or troughs may not line up with the spacing of the electrodes implanted to detect the ECAP signal. In other words, the voltage between the two electrodes for detecting the signal may line up well with the maximum difference in voltage between depolarization and the repolarization of the ECAP signal (resulting in a larger ECAP signal) or the voltage difference may line up poorly with features of the ECAP signal (resulting in a smaller ECAP signal than may be possible). If the voltage difference of the ECAP signal does not line up well with the features of the ECAP signal, the signal to noise ratio may be lower and the system may not be able to correctly identify or characterize ECAP signals for use as feedback.

[0023] As described herein, systems, devices, and techniques are described for selecting sensing parameters in order to improve detection of sensed physiological signals, such as ECAP signals. For example, the system may determine and utilize fractional contributions from at least some sensing electrodes in order to aligning sensing electrodes to one or more components of the ECAP signal. An electrical signal of a patient may be detected by sensing a voltage difference between two electrodes. These two electrodes may be referenced has having different, or opposite, polarities because the electrical potential between the electrodes is used as the basis for the sensed signal. Propagating signals may pass by the sense electrodes in a wave, and the potential over time between the electrodes is used to generate the sensed signal that can be output over time, e.g., a voltage over time. However, if the maximum potential difference of the signal,such as a peak to a trough in an ECAP, does not align with the two sense electrodes, the system may not be able to detect the actual maximum difference in the signal.

[0024] The system may be configured to utilize fractional contributions from two or more electrodes of the same polarity to shift the detection of the signal towards or away from an electrode of the other polarity in the sensing electrode configuration. For example, the system may sense the electrical signal using a percentage of one electrode and a percentage of another electrode for one polarity, where the two percentages equal 100% of the contribution for that polarity. The other polarity may use a single electrode or two or more electrodes with fractional contributions as well. In this manner, the system may operate to “steer” the voltage detection between multiple electrodes to enable the system to match the electrode detection to peaks and / or troughs of the electrical signal being sensed. Matching the electrode distance to the signal may result in the system to increase the signal to noise ratio of the signal and improved ECAP detection.

[0025] ECAP signals sensed from the patient can then be used to determine one or more characteristic values of the ECAP signals, and determining one or more ECAP thresholds from the ECAP characteristic values. In one example, the system may calculate the absolute value of the difference between two adjacent peaks in the ECAP signal (e.g., between a negative peak and a positive peak, such as the N1 and P2 peaks) to determine an ECAP characteristic value from each ECAP signal from respective stimulation pulses having different parameter values. The IMD may utilize the characteristic values of the ECAP signals as feedback for adjusting electrical stimulation provided to the patient.

[0026] In some examples, the ECAPs detected by an IMD may be ECAPs elicited by stimulation pulses intended to contribute to therapy of a patient or separate pulses (e.g., control pulses) configured to elicit ECAPs that are detectable by the IMD. Nerve impulses detectable as the ECAP signal travel quickly along the nerve fiber after the delivered stimulation pulse first depolarizes the nerve. If the stimulation pulse delivered by first electrodes has a pulse width that is too long, or the stimulation pulses have a pulse frequency to high, different electrodes configured to sense the ECAP will sense the stimulation pulse itself or the next stimulation pulse as an artifact (e.g., detection of delivered charge itself as opposed to detection of a physiological response to the delivered stimulus) that obscures the lower amplitude ECAP signal. However, the ECAP signal loses fidelity as the electrical potentials propagate from the electrical stimulus, because different nerve fibers propagate electrical potentials at different speeds, and fibers in the spine contributing to the ECAP are pruned off. Therefore, sensing the ECAP at a long distance from the stimulating electrodes may help avoid the artifact caused by a stimulation pulse with a long pulse width, but the ECAP signal may be too small or lose fidelity needed to detect changesto the ECAP signal that occur when the electrode-to-target-tissue distance changes. In other words, the system may not be able to identify, at any distance from the stimulation electrodes, ECAPs from stimulation pulses configured to provide a therapy to the patient. Therefore, the system may use a control pulse configured to elicit ECAP signals in certain situations. The control pulse may or may not contribute to a therapeutic benefit to the patient.

[0027] In addition to determining the fractional contribution of two or more electrodes for sensing a signal, the system may determine a sensing window that has a duration sized for the peak or trough of the sensed signal. For example, the system may narrow one or more sensing windows for anticipated trough and peak detection based on patient-specific conduction velocities. These narrowed, or adjusted, windows may be used set the sensing duration to the appropriate time from a delivered evoking stimulus in order to reduce the total amount of sensed voltage and decrease the amount of introduced noise. If the sensing window is too narrow, the system may not detect the entire target portion of the signal. If the sensing window is too wide, there is increased opportunity for the system to detect noise or other unwanted signals. Although the examples herein are directed to ECAP signals, the system may apply these signal detection concepts to any electrical physiological signal (e.g., a muscle signal or neural signal) in which a voltage difference is desired to be sensed from the subject.

[0028] In some examples, the determined fractional contributions may be used by the system to monitor various aspects of therapy. For example, determining the fractional contributions for a sensing electrode combination may be used an automated check for lead migration. If, in subsequent checks over time, the trough and peak of the ECAP moved forward or backward with respect to the electrodes, the system could conclude that a new volume of neural tissue being activated. For example, the moved stimulus electrodes and / or sensing electrodes may capture a population of nerves that includes a greater percentage of faster fibers or a greater percentage of slower fibers.

[0029] The determination of the fractional contributions of sensing electrodes can be performed by first sensing a resting ECAP, and then performing sensing of subsequent ECAPs with a sweep of different sensing electrodes and / or contributions of different sets of electrodes of the same polarity. In one example, the distal electrode could remain fixed in the sweep while more proximal electrodes are tested using different fractional contributions to the voltage potential. In other examples, the system could alternatively or additionally be expanded to include an algorithm where the distal electrode is moved closer to proximal electrodes, such as in systems where there are larger distances between the stimulation and sensing electrode combinations.

[0030] Other than lead migration, the system may determine other changes with the patient may re-determining fractional contributions for sensing electrode combinations. For example, the system may be configured to identify a change in disease state (e.g., chronic pain or other disease), physiology (such as fatigue), administration of medical, or wearing off of medications. In the example of medication, this process could be used by the system to monitor or prescribe appropriate dosing through measuring the half-life of a medication. In some patients, there could be variability in the distance between depolarization and repolarization of the sensed signal, and this variability could be used as a measure of different medication impact that might provide more information than merely just depolarization of the ECAP signal. In some examples, the system may include an alert feature in which the system delivers an alert via a user interface that suggests the patient take a dose of medication or alert the physician if a patient is over-dosing or under-dosing a medication.

[0031] FIG. 1 is a conceptual diagram illustrating an example system 100 that includes an implantable medical device (IMD) 110 configured to deliver spinal cord stimulation (SCS) therapy, and an external programmer 150. Although the techniques described in this disclosure are generally applicable to a variety of medical devices including external devices and IMDs, application of such techniques to IMDs and, more particularly, implantable electrical stimulators (e.g., neurostimulators) will be described for purposes of illustration. More particularly, the disclosure will refer to an implantable SCS system for purposes of illustration, but without limitation as to other types of medical devices or other therapeutic applications of medical devices.

[0032] As shown in FIG. 1, system 100 includes IMD 110, leads 130A and 130B, and external programmer 150, shown in conjunction with a patient 105, who is ordinarily a human patient. In the example of FIG. 1, IMD 110 is an implantable electrical stimulator that is configured to generate and deliver electrical stimulation therapy to patient 105 via one or more electrodes of leads 130A and / or 130B (collectively, “leads 130”), e.g., for relief of chronic pain or other symptoms. In other examples, IMD 110 may be coupled to a single lead carrying multiple electrodes or more than two leads each carrying multiple electrodes. In some examples, the stimulation signals, or pulses, may be configured to elicit detectable ECAP signals that IMD 110 may use as feedback for adjusting stimulation parameter values, such as amplitude or electrode combination that defines subsequent stimulation pulses. IMD 110 may be a chronic electrical stimulator that remains implanted within patient 105 for weeks, months, or even years. In other examples, IMD 110 may be a temporary, or trial, stimulator used to screen or evaluate the efficacy of electrical stimulation for chronic therapy. In one example, IMD 110 is implanted within patient 105, while in another example, IMD 110 is an external device coupled topercutaneously implanted leads. In some examples, IMD 110 uses one or more leads, while in other examples, IMD 110 is leadless.

[0033] IMD 110 may be constructed of any polymer, metal, or composite material sufficient to house the components of IMD 110 (e.g., components illustrated in FIG. 2) within patient 105. In this example, IMD 110 may be constructed with a biocompatible housing, such as titanium or stainless steel, or a polymeric material such as silicone, polyurethane, or a liquid crystal polymer, and surgically implanted at a site in patient 105 near the pelvis, abdomen, or buttocks. In other examples, IMD 110 may be implanted within other suitable sites within patient 105, which may depend, for example, on the target site within patient 105 for the delivery of electrical stimulation therapy. The outer housing of IMD 110 may be configured to provide a hermetic seal for components, such as a rechargeable or non-rechargeable power source. Additionally or alternatively, the outer housing of IMD 110 may be selected from a material that facilitates receiving energy to charge the rechargeable power source.

[0034] Electrical stimulation energy, which may be constant-current or constant-voltage- based pulses, for example, is delivered from IMD 110 to one or more target tissue sites of patient 105 via one or more electrodes (not shown) of implantable leads 130. In the example of FIG. 1, leads 130 carry electrodes that are placed adjacent to the target tissue of spinal cord 120. One or more of the electrodes may be disposed at a distal tip of a lead 130 and / or at other positions at intermediate points along the lead. Leads 130 may be implanted and coupled to IMD 110. The electrodes may transfer electrical stimulation generated by an electrical stimulation generator of IMD 110 to tissue of patient 105. Although leads 130 may each be a single lead, lead 130 may include a lead extension or other segments that may aid in implantation or positioning of lead 130. In some other examples, IMD 110 may be a leadless stimulator with one or more arrays of electrodes arranged on a housing of the stimulator rather than leads that extend from the housing. In some other examples, system 100 may include one lead or more than two leads, each coupled to IMD 110 and directed to similar or different target tissue sites. In some examples, the housing, or a portion of the housing, of IMD 110 may be configured to operate as an electrode to deliver stimulation and / or sensing signals. In this manner, the housing, or a portion of the housing, of IMD 110 may be part of any electrode combination, and any polarity, as described herein.

[0035] The electrodes of leads 130 may be electrode pads on a paddle lead, circular (e.g., ring) electrodes surrounding the body of the lead, conformable electrodes, cuff electrodes, segmented electrodes (e.g., electrodes disposed at different circumferential positions around the lead instead of a continuous ring electrode), any combination thereof (e.g., ring electrodes and segmented electrodes), or any other type of electrodes capable of forming unipolar, bipolar, ormultipolar electrode combinations for therapy. Ring electrodes arranged at different axial positions at the distal ends of lead 130 will be described for purposes of illustration.

[0036] The deployment of electrodes via leads 130 is described for purposes of illustration, but arrays of electrodes may be deployed in different ways. For example, a housing associated with a leadless stimulator may carry arrays of electrodes, e.g., rows and / or columns (or other patterns), to which shifting operations may be applied. Such electrodes may be arranged as surface electrodes, ring electrodes, or protrusions. As a further alternative, electrode arrays may be formed by rows and / or columns of electrodes on one or more paddle leads. In some examples, electrode arrays include electrode segments, which are arranged at respective positions around a periphery of a lead, e.g., arranged in the form of one or more segmented rings around a circumference of a cylindrical lead. In other examples, one or more of leads 130 are linear leads having eight ring electrodes along the axial length of the lead. In another example, the electrodes are segmented rings arranged in a linear fashion along the axial length of the lead and at the periphery of the lead.

[0037] The stimulation parameter set of a therapy stimulation program, which defines the stimulation pulses of electrical stimulation therapy by IMD 110 through the electrodes of leads 130, may include information identifying which electrodes have been selected (e.g., electrode combination) for delivery of stimulation according to a stimulation program, the polarities of the selected electrodes, voltage or current amplitude, pulse frequency, pulse width, and / or a pulse shape of stimulation delivered by the electrodes. These stimulation parameter values may be predetermined parameter values defined by a user and / or automatically determined by system 100 based on one or more factors or user input.

[0038] Although FIG. 1 is directed to SCS therapy, e.g., stimulation delivered to the spinal cord and configured to treat pain, in other examples system 100 may be configured to treat any other condition that may benefit from electrical stimulation therapy. For example, system 100 may be used to treat tremor, Parkinson’s disease, epilepsy, a pelvic floor disorder (e.g., urinary incontinence or other bladder dysfunction, fecal incontinence, pelvic pain, bowel dysfunction, or sexual dysfunction), obesity, gastroparesis, or psychiatric disorders (e.g., depression, mania, obsessive compulsive disorder, anxiety disorders, and the like). In this manner, system 100 may be configured to provide therapy taking the form of deep brain stimulation (DBS), peripheral nerve stimulation (PNS), peripheral nerve field stimulation (PNFS), cortical stimulation (CS), pelvic floor stimulation, gastrointestinal stimulation, or any other stimulation therapy capable of treating a condition of patient 105.

[0039] In some examples, lead 130 includes one or more sensors configured to allow IMD 110 to monitor one or more parameters of patient 105, such as patient activity, pressure,temperature, or other characteristics. The one or more sensors may be provided in addition to, or in place of, therapy delivery by lead 130.

[0040] IMD 110 is configured to deliver electrical stimulation therapy to patient 105 via selected combinations of electrodes carried by one or both of leads 130, alone or in combination with an electrode carried by or defined by an outer housing of IMD 110. The target tissue for the electrical stimulation therapy may be any tissue affected by electrical stimulation, which may be in the form of electrical stimulation pulses or continuous waveforms. In some examples, the target tissue includes nerves, smooth muscle, or skeletal muscle. In the example illustrated by FIG. 1, the target tissue is tissue proximate spinal cord 120, such as within an intrathecal space or epidural space of spinal cord 120, or, in some examples, adjacent nerves that branch off spinal cord 120. Leads 130 may be introduced into spinal cord 120 in via any suitable region, such as the thoracic, cervical, or lumbar regions. Stimulation of spinal cord 120 may, for example, prevent pain signals from traveling through spinal cord 120 and to the brain of patient 105. Patient 105 may perceive the interruption of pain signals as a reduction in pain and, therefore, efficacious therapy results. In other examples, stimulation of spinal cord 120 may produce paresthesia, which may reduce the perception of pain by patient 105, and thus, provide efficacious therapy results.

[0041] IMD 110 is configured to generate and deliver electrical stimulation therapy to a target stimulation site within patient 105 via the electrodes of leads 130 according to one or more therapy stimulation programs. A therapy stimulation program defines values for one or more parameters (e.g., a parameter set) that define an aspect of the therapy delivered by IMD 110. For example, a therapy stimulation program that controls delivery of stimulation by IMD 110 in the form of pulses may define values for voltage or current pulse amplitude, pulse width, pulse rate (e.g., pulse frequency), electrode combination (which may also specify electrode polarity), pulse shape, etc., for stimulation pulses delivered by IMD 110.

[0042] Furthermore, IMD 110 may be configured to deliver stimulation to patient 105 via a combination of electrodes of leads 130, alone or in combination with an electrode carried by or defined by an outer housing of IMD 110, in order to detect ECAP signals. The tissue targeted by the stimulation may be the same or similar tissue targeted by the electrical stimulation therapy, but IMD 110 may deliver stimulation pulses for ECAP signal detection via the same, at least some of the same, or different electrodes.

[0043] IMD 110 can deliver stimulation to a target stimulation site within patient 105 via the electrodes of leads 130 according to one or more ECAP stimulation programs. The one or more ECAP stimulation programs may be stored in a storage device of IMD 110 and / or external programmer 150. Each ECAP stimulation program of the one or more ECAP stimulationprograms includes values for one or more parameters that define an aspect of the stimulation delivered by IMD 110 according to that program, such as current or voltage amplitude, pulse width, pulse frequency, electrode combination, etc. Although these functions are described with respect to IMD 110, other devices, such as external programmer 150, may perform these functions, such as determining sensing electrode combinations and fractional contributions of at least some electrodes.

[0044] A user, such as a clinician or patient 105, may interact with a user interface of an external programmer 150 to program IMD 110. Programming of IMD 110 may refer generally to the generation and transfer of commands, programs, or other information to control the operation of IMD 110. In this manner, IMD 110 may receive the transferred commands and programs from external programmer 150 to control stimulation, such as electrical stimulation therapy to develop the growth curve. For example, external programmer 150 may transmit therapy stimulation programs, ECAP stimulation programs, stimulation parameter adjustments, therapy stimulation program selections, ECAP program selections, user input, or other information to control the operation of IMD 110, e.g., by wireless telemetry or wired connection.

[0045] In some cases, external programmer 150 may be characterized as a “physician programmer” or a “clinician programmer” if it is primarily intended for use by a physician or clinician. In other cases, external programmer 150 may be characterized as a “patient programmer” if it is primarily intended for use by a patient. A patient programmer may be generally accessible to patient 105 and, in many cases, may be a portable device that accompanies patient 105 throughout the patient’s daily routine. For example, a patient programmer may receive input from patient 105 when the patient wishes to terminate or change electrical stimulation therapy, when a patient perceives stimulation being delivered or when a patient terminates therapy due to comfort level. In general, a physician or clinician programmer may support selection and generation of programs by a clinician for use by IMD 110, whereas a patient programmer may support adjustment and selection of such programs by a patient during ordinary use. In other examples, external programmer 150 may include, or be part of, an external charging device that recharges a power source of IMD 110. In this manner, a user may program and charge IMD 110 using one device, or multiple devices.

[0046] As described herein, information may be transmitted between external programmer 150 and IMD 110. For instance, IMD 110 and external programmer 150 may communicate via wireless communication using any techniques known in the art. Examples of communication techniques may include, for example, radiofrequency (RF) telemetry and inductive coupling, but other techniques are also contemplated. In some examples, external programmer 150 includes a communication head that may be placed proximate to the patient’s body near the implant site ofIMD 110 in order to improve the quality and / or security of communication between IMD 110 and external programmer 150. Communication between external programmer 150 and IMD 110 may occur during power transmission or separate from power transmission.

[0047] In some examples, IMD 110, in response to commands from external programmer 150, delivers electrical stimulation therapy according to a plurality of therapy stimulation programs to a target tissue site of the spinal cord 120 of patient 105 via electrodes (not depicted) on leads 130. In some examples, IMD 110 modifies therapy stimulation programs as therapy needs of patient 105 evolve over time. For example, the modification of the therapy stimulation programs may cause the adjustment of at least one parameter of the plurality of therapy pulses. When patient 105 receives the same therapy for an extended period, the efficacy of the therapy may be reduced. In some cases, parameters of the plurality of therapy pulses may be automatically updated. In some examples, IMD 110 may detect ECAP signals from pulses delivered for the purpose of providing therapy to the patient.

[0048] In some examples, efficacy of electrical stimulation therapy may be indicated by one or more characteristics of an action potential that is evoked by a stimulation pulse delivered by IMD 110, for example, by determining an ECAP characteristic value of the ECAP signal. Electrical stimulation therapy delivery by leads 130 of IMD 110 may cause neurons within the target tissue to evoke a compound action potential that travels up and down the target tissue, eventually arriving at sensing electrodes of IMD 110. Furthermore, stimulation pulses may also elicit at least one ECAP signal, and ECAPs responsive to stimulation may also be a surrogate for the effectiveness of the therapy and / or the intensity perceived by the patient. The amount of action potentials (e.g., number of neurons propagating action potential signals) that are evoked may be based on the various parameters of electrical stimulation pulses such as amplitude, pulse width, frequency, pulse shape (e.g., slew rate at the beginning and / or end of the pulse), etc. The slew rate may define the rate of change of the voltage and / or current amplitude of the pulse at the beginning and / or end of each pulse or each phase within the pulse. For example, a very high slew rate indicates a steep or even near-vertical edge of the pulse, and a low slew rate indicates a longer ramp up (or ramp down) in the amplitude of the pulse. In some examples, these parameters contribute to an intensity of the electrical stimulation. In addition, a characteristic of the ECAP signal (e.g., an amplitude) may change based on the distance between the stimulation electrodes and the nerves subject to the electrical field produced by the delivered control stimulation pulses.

[0049] Example techniques for adjusting stimulation parameter values for pulses (e.g., pulses configured to contribute to therapy for the patient) are based on comparing the value of a characteristic of a measured ECAP signal to a target ECAP characteristic value. In someexamples, the target ECAP characteristic value may be an ECAP threshold (e.g., a neural threshold) or a value calculated based on the neural threshold (e.g., a percentage below or above 100% of the neural threshold). During delivery of control stimulation pulses defined by one or more ECAP test stimulation programs, IMD 110, via two or more electrodes interposed on leads 130, senses electrical potentials of tissue of the spinal cord 120 of patient 105 to measure the electrical activity of the tissue. IMD 110 senses ECAPs from the target tissue of patient 105, e.g., with electrodes on one or more leads 130 and associated sensing circuitry. In some examples, IMD 110 receives a signal indicative of the ECAP from one or more sensors, e.g., one or more electrodes and circuitry, internal or external to patient 105. Such a signal may indicate an ECAP of the tissue of patient 105.

[0050] In the examples described above, IMD 110 is described as performing a plurality of processing and computing functions. However, external programmer 150 instead may perform one, several, or all of these functions. In this alternative example, IMD 110 relays sensed signals to external programmer 150 for analysis, and external programmer 150 transmits instructions to IMD 110 to adjust the one or more parameters defining the electrical stimulation therapy based on analysis of the sensed signals. For example, IMD 110 may relay the sensed signal indicative of an ECAP to external programmer 150. External programmer 150 may compare the parameter value of the ECAP to the target ECAP characteristic value, and in response to the comparison, external programmer 150 may instruct IMD 110 to adjust one or more stimulation parameters that define subsequent electrical stimulation pulses delivered to patient 105.

[0051] In some examples, the stimulation parameters and the target ECAP characteristic values associated with the ECAP threshold may initially be set at the clinic, but may be subsequently set and / or adjusted at home by patient 105. For example, the target ECAP characteristics may be changed to match, or to be a fraction of, or a multiplier of, an ECAP threshold. In some examples, target ECAP characteristics may be specific to respective different posture states of the patient (which the system may detect via the ECAP signal and / or a posture sensor which may include an accelerometer). Once the target ECAP characteristic values are set, the example techniques allow for automatic adjustment of parameter values that define stimulation pulses to maintain a consistent volume of neural activation and consistent perception of therapy for the patient. The ability to change the stimulation parameter values may also allow the therapy to have long-term efficacy, with the ability to keep the intensity of the stimulation (e.g., as indicated by the ECAP) consistent by comparing the measured ECAP values to the target ECAP characteristic value. In addition, or alternatively, to maintaining stimulation intensity, IMD 110 may monitor the characteristic values of the ECAP signals to limit one or moreparameter values that define stimulation pulses. IMD 110 may perform these changes without intervention by a physician or patient 105.

[0052] In some examples, system 100 changes the target ECAP characteristic value over a period of time, such as according to a change to an ECAP threshold (e.g., a perception threshold or detection threshold). The system may be programmed to change the target ECAP characteristic in order to adjust the intensity of stimulation pulses to provide varying sensations to the patient (e.g., increase or decrease the volume of neural activation). Although the system may change the target ECAP characteristic value, received ECAP signals may still be used by the system to adjust one or more parameter values of the stimulation pulse in order to meet the target ECAP characteristic value.

[0053] One or more devices within system 100, such as IMD 110 and / or external programmer 150, may perform various functions as described herein. For example, IMD 110 may include stimulation circuitry configured to deliver electrical stimulation, sensing circuitry configured to sense a plurality ECAP signals, and processing circuitry. The processing circuitry may be configured to control the stimulation circuitry to deliver a plurality of electrical stimulation pulses having different amplitude values and control the sensing circuitry to detect, after delivery of each electrical stimulation pulse, a respective ECAP signal, and to determine ECAP characteristic values for each of the ECAP signals. The processing circuitry of IMD 110 may then determine, based on the plurality of ECAP characteristic values, an ECAP threshold (e.g., a neural threshold) of a patient. The neural threshold may be similar to a perception threshold that the patient would have manually identified during the sweep of pulses defined by increasing amplitude values within the sweep. As such, IMD 110, or another device such as external programmer 150, may automatically determine the neural threshold, e.g., without patient input.

[0054] In some examples, IMD 110 may include the stimulation circuitry, the sensing circuitry, and the processing circuitry. However, in other examples, one or more additional devices may be part of the system that performs the functions described herein. For example, IMD 110 may include the stimulation circuitry and the sensing circuitry, but external programmer 150 or another external device may include the processing circuitry that at least determines the neural threshold of the patient. IMD 110 may transmit the sensed ECAP signals, or data representing the ECAP signal, to external programmer 150, for example. Therefore, the processes described herein may be performed by multiple devices in a distributed system. In some examples, system 100 may include one or more electrodes that deliver and / or sense electrical signals. Such electrodes may be configured to sense the ECAP signals. In some examples, the same electrodes may be configured to sense signals representative of transientmovements of the patient. In other examples, other sensors, such as accelerometers, gyroscopes, or other movement sensors may be configured to sense movement of the patient that indicates that the patient may have transitioned to a different posture state.

[0055] As described herein, the processing circuitry of IMD 110 may be configured to determine characteristic values for each of the plurality of ECAP signals detected after each of the plurality of electrical stimulation pulses. A plurality of stimulation pulses is delivered, where each stimulation pulse may be defined by a different respective value of a stimulation parameter. The plurality of stimulation pulses may include increasing amplitudes to elicit different responses of ECAP signal information. In one or more examples, the characteristic value for each ECAP signal is a representation of the ECAP signal according to some metric, and is determined by IMD 110, for example, by removing an artifact from the ECAP signal. These characteristic values may thus be used as a metric derived from the ECAP signal that represents the relative nerve fiber activation caused by the delivered stimulation pulse. In this manner, each ECAP signal is associated with a respective characteristic value of the characteristic values. As long as the distance between the electrodes and target nerve remains relatively constant during delivery of the pulses and sensing of the respective ECAP signals, higher amplitude pulses generally cause more neural recruitment and larger ECAP signals.

[0056] The processing circuitry functionality described herein may be located on one or more devices of a system, such as system 100. In one example, IMD 110 includes at least a portion of the processing circuitry. In one example, external programmer 150 includes at least a portion of the processing circuitry and a user interface configured to receive user input identifying the maximum amplitude value. In this manner, the functionality described herein may be contained within a single device or distributed over two or more devices of the system.

[0057] In one example, system 100 (which may be or may include IMD 110, external programmer 150, and / or off-site or networked computing systems) may include a stimulation generator configured to deliver a stimulation pulse to patient 105, and sensing circuitry configured to sense an ECAP signal evoked by the stimulation pulse. System 100 may also include processing circuitry configured to determine ECAP characteristic values for each of the ECAP signals, and determine at least one parameter value at least partially defining electrical stimulation therapy to be delivered or offered to the patient. The patient or clinician may further modify the stimulation therapy, for example, based on patient preference or expected battery life, for example.

[0058] In one example, IMD 110 may determine a target ECAP characteristic value based on the ECAP threshold, such as a neural response, and calculate at least one parameter value according to a difference between the current ECAP characteristic value. In this manner, IMD110 may deliver stimulation in closed-loop fashion using ECAP characteristic values as feedback. Processing circuitry of IMD 110 may thus be configured to control the stimulation generator to deliver the electrical stimulation therapy to the patient according to at least one adjusted parameter value, which may be selected based on the ECAP characteristic values and / or ECAP threshold. IMD 110 may include stimulation circuitry, sensing circuitry, and processing circuitry. In some examples, other devices, such as an external device or different implanted device, may analyze ECAP signals for characteristic values and / or adjust parameter values that define stimulation pulses based on the characteristic values.

[0059] As described herein, system 100 may include sensing circuitry (such as sensing circuitry 206 of FIG. 2) configured to generate a sensed signal and processing circuitry (such as processing circuitry 210 of FIG. 2). The processing circuitry may be configured to select one or more first polarity electrodes for sensing the sensed signal, select a plurality of second polarity electrodes for sensing the sensed signal, the first polarity being opposite of the second polarity, determine fractional contributions to the sensed signals for each electrode of the plurality of second polarity electrodes, and control the sensing circuitry to generate the sensed signal according to the one or more first polarity electrodes, the plurality of second polarity electrodes, and the fractional contributions. In this manner, the sensing electrode combination may identify each electrode of the first polarity and each electrode of the second polarity between which electrical potentials are measures. In addition, the sensing electrode combination may identify which electrodes have a fractional contribution to the signal and the percentage or fraction of the total signal to which the electrode will contribute. These fractional contributions from at least some electrodes can thus “steer” sensing between electrodes of the same polarity and move the point at which the electrical potential (e.g., voltage) is measured.

[0060] In some examples, the system may determine the fractional contributions by at least controlling the sensing circuitry to generate a plurality of sensed signals at different respective sets of fractional contributions, analyze the plurality of sensed signals for an amplitude of at least one peak within each signal of the plurality of sensed signals, and determine, based on the amplitude of the at least one peak, one set of fractional contributions as the fractional contributions of the plurality of second polarity electrodes. The amplitude of at least one peak may be one example of a characteristic that is used to determine the fractionalized contributions. Other characteristics of the signal that may be analyzed may include one or more peaks, one or more troughs, a latency, a power of a frequency contribution, or any other signal characteristic. In some examples, the system may analyze multiple characteristics to determine the fractional contributions of each electrode combination (e.g., the contribution from each electrode of the same polarity to determine the “virtual” location to sense the signal). For example, the systemmay look for largest measured potential for all of the sets of fractional contributions and select the set of fractional contributions that provided the largest signal. This may align the sensing electrode combination to the features of the signal, such as a peak and a trough of the signal. The largest signal may not always be selected. In other examples, noise may be a factor in which fractional contributions are present. For example, an electrode with very small contribution may introduce more noise and be less desirable than fractional contributions between electrodes that are more balanced. Indeed, the system can, in some examples, be configured to determine the fractional contributions to reduce a noise characteristic of sensed signals associated with a sensing electrode combination different than the fractional contributions of the plurality of second polarity electrodes. Different fractional contributions may be analyzed for variations that may provide an improved sensed signal or may better capture one or more aspects of the signal that is of interest with respect to the patient condition.

[0061] In addition to the fractional contributions, the system may be configured to determine at least one timing window for sensing the sensed signal based on the at least one peak within the sensed signal associated with the one set of fractional contributions of the plurality of second polarity electrodes. The system can this align the sensing window for the sensing electrode combination to a time from delivery of the stimulus configured to elicit the sensed signal, for example. However, the sensing window may be calculated from any event that facilitates acquisition of the sensed signal of interest.

[0062] In some example, the system can identify changes to signals propagating within the patient over time. These changes to the signal may be due to lead migration, medication, disease progression, or other factions. In one examples, the system may determine second fractional contributions for a second period of time and determine a migration of one or more electrodes based on the first fractional contributions initially determined for the system and the second fractional contributions. The system may repeat this process over time to monitor one or more changes with the patient. The system may also alert a user (e.g., patient or clinician) in response to determining that something has changed, such as the patient disease state or lead migration.

[0063] The system may determine fractional contributions for two or more electrodes of a second polarity of the sensing configuration. The other electrode of the first polarity used to sense the potential difference may be a single electrode. Alternatively, the first polarity may also include at least two first polarity electrodes that also are assigned respective fractional contributions to the sensed signal. In this manner, the system can move the sensing field to any desired location with respect to the sensed signal that occurs within the patient. In any case, the system may be configured to sense naturally occurring physiological signals or deliver an electrical stimulus that is configured to elicit a neurological response that is detectable as thesensed signal. The sensed signal may be used for a variety of purposes. The system may, in some examples, adjust, based on the sensed signal, at least one stimulation parameter that defines subsequent stimulation therapy to be delivered to the patient. The sensed signal may thus be referred to as a feedback variable.

[0064] Although in the example of FIG. 1, IMD 110 takes the form of an SCS device, in other examples, IMD 110 takes the form of any combination of deep brain stimulation (DBS) devices, peripheral nerve stimulators, implantable cardioverter defibrillators (ICDs), pacemakers, cardiac resynchronization therapy devices (CRT-Ds), left ventricular assist devices (LVADs), implantable sensors, orthopedic devices, or drug pumps, as examples. Moreover, techniques of this disclosure may be used to determine stimulation thresholds (e.g., perception thresholds and detection thresholds) associated any one of the aforementioned IMDs and then use a stimulation threshold to inform the intensity (e.g., stimulation levels) of therapy. Although ECAP signals are described as one example of a sensed signal, other signals may be sensed as appropriate for different types of sensing and therapy. For example, IMD 110 may be configured to sense other evoked signals, local field potentials (LFPs), or any other electrical signals from a patient.

[0065] FIG. 2 is a block diagram illustrating an example configuration of components of an IMD 200. IMD 200 may be an example of IMD 110 of FIG. 1. In the example shown in FIG. 2, IMD 200 includes stimulation generation circuitry 202, sensing circuitry 206, telemetry circuitry 208, processing circuitry 210, storage device 212, sensor(s) 222, and power source 224.

[0066] In the example shown in FIG. 2, storage device 212 stores patient data 240, stimulation parameter settings 242, and ECAP detection instructions 244 in separate memories within storage device 212 or separate areas within storage device 212. Patient data 240 may include parameter values, target characteristic values, or other information specific to the patient. In some examples, stimulation parameter settings 242 may include stimulation parameter values for respective different stimulation programs selectable by the clinician or patient for therapy. In this manner, each stored therapy stimulation program, or set of stimulation parameter values, of stimulation parameter settings 242 defines values for a set of electrical stimulation parameters (e.g., a stimulation parameter set), such as a stimulation electrode combination, electrode polarity, current or voltage amplitude, pulse width, pulse rate, pulse shape, and / or duty cycle. Storage device 212 may also store ECAP detection instructions 244 that define values for a set of electrical stimulation parameters configured to elicit a detectable ECAP signal, such as a stimulation electrode combination, stimulus electrode polarity, current or voltage amplitude, pulse width, pulse rate, and / or pulse shape. ECAP detection instructions 244 may also have additional information such as instructions regarding when to deliver control pulses based on the pulse width and / or frequency of the pulses defined in stimulation parameter settings 242,detection windows for detecting ECAP signals, one or more sensing electrode combinations and respective fractional contributions of each electrode, instructions for determining characteristic values from ECAP signals, etc. For example, ECAP detection instructions 244 may define how characteristic values of ECAP signals are to be determined. ECAP detection instructions 244 may also, in some examples, include instructions for performing trials of different sensing electrode combinations and different fractional contributions of each electrode to the sensing of a signal in order to identify a sensing electrode combination and fractional contributions of at least some of the selected electrodes. It should be noted that the system may select to not use any fractional contributions if the sensed signal is not improved. In addition, in some examples, the fractional contribution of some electrode(s) may be very small, or even set to 0%, as such small change to the sensing circuitry may still reduce certain noise or otherwise improve the sensed signal.

[0067] Accordingly, in some examples, stimulation generation circuitry 202 generates electrical stimulation signals in accordance with the electrical stimulation parameters noted above. Other ranges of stimulation parameter values may also be useful and may depend on the target stimulation site within patient 105. While stimulation “pulses” are primarily described herein, stimulation signals may be of any form, such as continuous-time signals (e.g., sine waves) or the like. Stimulation generation circuitry 204 may include independently controllable current sinks and sources for respective electrodes 232, 234. For example, stimulation generation circuitry 204 comprises a plurality of pairs of voltage sources, current sources, voltage sinks, or current sinks connected to each of electrodes 232, 234 such that each pair of electrodes has a unique signal circuit. In other words, in these examples, each of electrodes 232, 234 is independently controlled via its own signal circuit (e.g., via a combination of a regulated voltage source and sink or regulated current source and sink), as opposed to switching signals between electrodes 232, 234. In this manner, processing circuitry 208 may control switches or transistors to selective couple the sources and / or sinks to the conductor of electrodes of an electrode combination.

[0068] One or more switches (not shown) may selectively couple sensing circuitry 206 to respective electrodes in order to sense signals via two or more electrodes 232, 234. In other examples, switch circuitry may include one or more switch arrays, one or more multiplexers, one or more switches (e.g., a switch matrix or other collection of switches), or other electrical circuitry configured to direct stimulation signals from stimulation generation circuitry 204 to one or more of electrodes 232, 234, or directed sensed signals from one or more of electrodes 232, 234 to sensing circuitry 206. In other examples, stimulation generation circuitry 204 and / orsensing circuitry 206 may include sensing circuitry to direct signals to and / or from one or more of electrodes 232, 234, which may or may not also include switch circuitry.

[0069] Sensing circuitry 206 is configured to monitor signals from any combination of electrodes 232, 234. In some examples, sensing circuitry 206 includes one or more amplifiers, filters, and / or analog-to-digital converters. Sensing circuitry 206 may be used to sense physiological signals, such as ECAP signals. In some examples, sensing circuitry 206 detects ECAPs from a particular combination of electrodes 232, 234. In some cases, the particular combination of electrodes for sensing ECAPs includes different electrodes than a set of electrodes 232, 234 used to deliver stimulation pulses. Alternatively, in other cases, the particular combination of electrodes used for sensing ECAPs includes at least one of the same electrodes as a set of electrodes used to deliver stimulation pulses to patient 105. Sensing circuitry 206 may provide signals to an analog-to-digital converter for conversion into a digital signal for processing, analysis, storage, and / or output by processing circuitry 210.

[0070] As described herein, in some examples, the sensing circuitry 206 can generate signals from two (or more) electrode combinations and then apply (or processing circuitry 210 can apply) the fractional contributions for each electrode combinations to the generated sensed signals to produce a physiological signal reflective of the combined signals according to the fractionalized contributions. In this case, sensing circuitry 206 may generate each signal from each electrode combination in response to respective stimuli being delivered. In other examples, sensing circuitry 206 may sense the patient signal from a single delivered stimuli by using a resistor divider network for the multiple electrode combinations that splits the patient signal into each electrode combination. The resistor divider network may be configured to represent the desired fractional contributions for each electrode combination. Alternatively, sensing circuitry 206 may divide the patient signal into the different electrode combinations by dividing the electrical current. Sensing signals is generally described using bipolar electrode combinations where electrodes of the electrode combinations are provided on one or more leads. In some examples, one electrode (e.g., one electrode of one polarity assigned) can be located far from the desired target tissue in order to provide monopolar recording (e.g., with an electrode on the housing of IMD 200, using some or all of the housing itself as an electrode, or using sensing electrodes far away from each other on the lead). For monopolar recording, processing circuitry 210 or sensing circuitry 206 can weight each electrode, optimize the sensing based on pulse shape of the stimulus, or otherwise fractionalize the electrodes to sense using a “virtual” electrode that is a composite of multiple electrodes of one polarity (from multiple electrode combinations that include those multiple electrodes of that one polarity). Using monopolar sensing may help to avoid signal saturation during recording.

[0071] In some examples, sensing circuitry 206 may have separate amplifiers for each electrode combination to be used to sense signals, and the resulting signals may be weighted according to their fractional contributions either using analog circuitry or by processing circuitry 210 when analyzing the sensed signals to generate the physiological signal representative of the fractionalized contributions for each electrode combination (e.g., the signal from a “virtual” electrode). These separate amplifiers may enable simultaneous recording from these multiple electrode combinations to detect the patient signal occurring at the same time. In other examples, sensing circuitry 206 may use the amplifiers to sense signals at different times (e.g., different signals from respective delivered stimuli) and combine those signals. For sensing different signals, sensing circuitry 206 may use a single amplifier and connect the appropriate electrodes of the desired electrode combinations at that time. Processing circuitry 210 can then digitally combine the generated sensed signals from each electrode combination and weight them according to the fractionalized contributions of each electrode combination.

[0072] Telemetry circuitry 208 supports wireless communication between IMD 200 and an external programmer (not shown in FIG. 2) or another computing device under the control of processing circuitry 210. Processing circuitry 210 of IMD 200 may receive, as updates to programs, values for various stimulation parameters (e.g., amplitude and electrode combination) from the external programmer via telemetry circuitry 208. Processing circuitry 210 may store updates to the stimulation parameter settings 242 or any other data in storage device 212. Telemetry circuitry 208 in IMD 200, as well as telemetry circuits in other devices and systems described herein, such as the external programmer, may accomplish communication by radiofrequency (RF) communication techniques. In addition, telemetry circuitry 208 may communicate with an external medical device programmer (not shown in FIG. 2) via proximal inductive interaction of IMD 200 with the external programmer. The external programmer may be one example of external programmer 150 of FIG. 1. Accordingly, telemetry circuitry 208 may send information to the external programmer on a continuous basis, at periodic intervals, or upon request from IMD 110 or the external programmer.

[0073] Processing circuitry 210 may include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), discrete logic circuitry, or any other processing circuitry configured to provide the functions attributed to processing circuitry 210 herein may be embodied as firmware, hardware, software or any combination thereof. Processing circuitry 210 controls stimulation generation circuitry 202 to generate stimulation signals according to stimulation parameter settings 242 and any other instructions stored in storage device 212 toapply stimulation parameter values specified by one or more of programs, such as amplitude, pulse width, pulse rate, and pulse shape of each of the stimulation signals.

[0074] In the example shown in FIG. 2, the set of electrodes 232 includes electrodes 232A, 232B, 232C, and 232D, and the set of electrodes 234 includes electrodes 234A, 234B, 234C, and 234D. In other examples, a single lead may include all eight electrodes 232 and 234 along a single axial length of the lead. Processing circuitry 210 also controls stimulation generation circuitry 202 to generate and apply the stimulation signals to selected combinations of electrodes 232, 234. In some examples, stimulation generation circuitry 202 includes a switch circuit that may couple stimulation signals to selected conductors within leads 230, which, in turn, deliver the stimulation signals across selected electrodes 232, 234. Such a switch circuit may be a switch array, switch matrix, multiplexer, or any other type of switching circuit configured to selectively couple stimulation energy to selected electrodes 232, 234 and to selectively sense bioelectrical neural signals of a spinal cord of the patient (not shown in FIG. 2) with selected electrodes 232, 234.

[0075] In other examples, however, stimulation generation circuitry 202 does not include a switch circuit and switch circuitry 204 does not interface between stimulation generation circuitry 202 and electrodes 232, 234. In these examples, stimulation generation circuitry 202 includes a plurality of pairs of voltage sources, current sources, voltage sinks, or current sinks connected to each of electrodes 232, 234 such that each pair of electrodes has a unique signal circuit. In other words, in these examples, each of electrodes 232, 234 is independently controlled via its own signal circuit (e.g., via a combination of a regulated voltage source and sink or regulated current source and sink), as opposed to switching signals between electrodes 232, 234.

[0076] Electrodes 232, 234 on respective leads 230 may be constructed of a variety of different designs. For example, one or both of leads 230 may include one or more electrodes at each longitudinal location along the length of the lead, such as one electrode at different perimeter locations around the perimeter of the lead at each of the locations A, B, C, and D. In one example, the electrodes may be electrically coupled to stimulation generation circuitry 202, e.g., switching circuitry of the stimulation generation circuitry 202, via respective wires that are straight or coiled within the housing of the lead and run to a connector at the proximal end of the lead. In another example, each of the electrodes of the lead may be electrodes deposited on a thin film. The thin film may include an electrically conductive trace for each electrode that runs the length of the thin film to a proximal end connector. The thin film may then be wrapped (e.g., a helical wrap) around an internal member to form the lead 230. These and other constructions may be used to create a lead with a complex electrode geometry.

[0077] Although sensing circuitry 206 is incorporated into a common housing with stimulation generation circuitry 202 and processing circuitry 210 in FIG. 2, in other examples, sensing circuitry 206 may be in a separate housing from IMD 200 and may communicate with processing circuitry 210 via wired or wireless communication techniques. In some examples, one or more of electrodes 232 and 234 are suitable for sensing the ECAPs. For instance, electrodes 232 and 234 may sense the voltage amplitude of a portion of the ECAP signals, where the sensed voltage amplitude, such as the voltage difference between features within the signal, is a characteristic the ECAP signal. As described herein, two or more of the sensing electrodes may be assigned a fractional contribution in order to adjust the spatial positioning of the sensing electrode combination.

[0078] Storage device 212 may be configured to store information within IMD 200 during operation. Storage device 212 may include a computer-readable storage medium or computer- readable storage device. In some examples, storage device 212 includes one or more of a shortterm memory or a long-term memory. Storage device 212 may include, for example, random access memories (RAM), dynamic random access memories (DRAM), static random access memories (SRAM), magnetic discs, optical discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable memories (EEPROM). In some examples, storage device 212 is used to store data indicative of instructions for execution by processing circuitry 210. As discussed above, storage device 212 is configured to store patient data 240, stimulation parameter settings 242, and ECAP detection instructions 244.

[0079] In some examples, storage device 212 may store instructions on how processing circuitry 210 can adjust stimulation pulses in response to the determined characteristic values of ECAP signals. For example, processing circuitry 210 may monitor ECAP characteristic values obtained from ECAP signals (or a signal derived from the ECAP signal) to modulate stimulation parameter values (e.g., increase or decrease stimulation intensity to maintain a target therapeutic effect). In some examples, a target ECAP characteristic value may vary for different situations for a patient, such as different posture states, times of day, activities, etc.

[0080] Sensor(s) 222 may include one or more sensing elements that sense values of a respective patient parameter, such as posture state. As described, electrodes 232 and 234 may be the electrodes that sense the characteristic value of the ECAP signal. Sensor(s) 222 may include one or more accelerometers, optical sensors, chemical sensors, temperature sensors, pressure sensors, or any other types of sensors. Sensor(s) 222 may output patient parameter values that may be used as feedback to control delivery of therapy. For example, sensor(s) 222 may indicate patient activity, and processing circuitry 210 may increase the frequency of control pulses andECAP sensing in response to detecting increased patient activity. In one example, processing circuitry 210 may initiate control pulses and corresponding ECAP sensing in response to a signal from sensor(s) 222 indicating that patient activity has exceeded an activity threshold. Conversely, processing circuitry 210 may decrease the frequency of control pulses and ECAP sensing in response to detecting decreased patient activity. For example, in response to sensor(s) 222 no longer indicating that the sensed patient activity exceeds a threshold, processing circuitry 210 may suspend or stop delivery of control pulses and ECAP sensing. In this manner, processing circuitry 210 may dynamically deliver control pulses and sense ECAP signals based on patient activity to reduce power consumption of the system when the electrode-to-neuron distance is not likely to change, and may increase a system response to ECAP changes when electrode-to-neuron distance is likely to change. IMD 200 may include additional sensors within the housing of IMD 200 and / or coupled via one of leads 130 or other leads. In addition, IMD 200 may receive sensor signals wirelessly from remote sensors via telemetry circuitry 208, for example. In some examples, one or more of these remote sensors may be external to patient (e.g., carried on the external surface of the skin, attached to clothing, or otherwise positioned external to patient 105). In some examples, signals from sensor(s) 222 indicate a position or body state (e.g., sleeping, awake, sitting, standing, or the like), and processing circuitry 210 may select target ECAP characteristic values according to the indicated position or body state.

[0081] Power source 224 is configured to deliver operating power to the components of IMD 200. Power source 224 may include a battery and a power generation circuit to produce the operating power. In some examples, the battery is rechargeable to allow extended operation. In some examples, recharging is accomplished through proximal inductive interaction between an external charger and an inductive charging coil within IMD 200. Power source 224 may include any one or more of a plurality of different battery types, such as nickel cadmium batteries and lithium ion batteries.

[0082] FIG. 3 is a block diagram illustrating an example configuration of components of an example external programmer 300. External programmer 300 may be an example of external programmer 150 of FIG. 1. Although external programmer 300 may generally be described as a handheld device, external programmer 300 may be a larger portable device or a more stationary device. In other examples, external programmer 300 may be included as part of an external charging device or may include the functionality of an external charging device. As illustrated in FIG. 3, external programmer 300 may include processing circuitry 352, storage device 354, user interface 356, telemetry circuitry 358, and power source 360.

[0083] Storage device 354 may store instructions that, when executed by processing circuitry 352, cause processing circuitry 352 and external programmer 300 to provide the functionalityascribed to external programmers 150, 300 throughout this disclosure. Each of these components, circuitry, or modules may include electrical circuitry that is configured to perform some, or all of the functionality described herein. For example, processing circuitry 352 may include processing circuitry configured to perform the processes discussed with respect to processing circuitry 352.

[0084] In general, external programmer 300 includes any suitable arrangement of hardware, alone or in combination with software and / or firmware, to perform the techniques attributed to external programmer 300, and processing circuitry 352, user interface 356, and telemetry circuitry 358 of external programmer 300. In various examples, external programmer 300 may include one or more processors, such as one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. External programmer 300 also, in various examples, may include a storage device 354, such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, a hard disk, a CD-ROM, including executable instructions for causing the one or more processors to perform the actions attributed to them. Moreover, although processing circuitry 352 and telemetry circuitry 358 are described as separate modules, in some examples, processing circuitry 352 and telemetry circuitry 358 are functionally integrated. In some examples, processing circuitry 352 and telemetry circuitry 358 correspond to individual hardware units, such as ASICs, DSPs, FPGAs, or other hardware units.

[0085] Storage device 354 (e.g., a memory or other device configured to store data) may store instructions that, when executed by processing circuitry 352, cause processing circuitry 352 and external programmer 300 to provide the functionality ascribed to external programmers 150, 300 throughout this disclosure. For example, storage device 354 may include instructions that cause processing circuitry 352 to obtain a parameter set from memory, select a spatial electrode pattern, receive a user input and send a corresponding command to IMD 200, or any other functionality. Indeed, external programmer 300 may be configured to determine the sensing electrode combination and fractional contributions for each electrode. Storage device 354 may include a plurality of programs, where each program includes a parameter set that defines therapy stimulation or control stimulation. Storage device 354 may also store data received from a medical device (e.g., IMD 110). For example, storage device 354 may store ECAP -related data recorded at a sensing module of the medical device, and storage device 354 may also store data from one or more sensors of the medical device.

[0086] User interface 356 may include a button or keypad, lights, a speaker for voice commands, a display, such as a liquid crystal display (LCD), light-emitting diode (LED), or organic light-emitting diode (OLED). In some examples the display includes a touchscreen.User interface 356 may be configured to display any information related to the delivery of electrical stimulation, identified posture states, sensed patient parameter values, or any other such information. User interface 356 may also receive user input (e.g., indication of when the patient perceives a stimulation pulse) via user interface 356. The input may be, for example, in the form of pressing a button on a keypad or selecting an icon from a touchscreen. The input may request starting or stopping electrical stimulation, a new spatial electrode pattern or a change to an existing spatial electrode pattern, or some other change to the delivery of electrical stimulation.

[0087] Telemetry circuitry 358 may support wireless communication between the medical device and external programmer 300 under the control of processing circuitry 352. Telemetry circuitry 358 may also be configured to communicate with another computing device via wireless communication techniques, or direct communication through a wired connection. In some examples, telemetry circuitry 358 provides wireless communication via an RF or proximal inductive medium. In some examples, telemetry circuitry 358 includes an antenna, which may take on a variety of forms, such as an internal or external antenna.

[0088] Examples of local wireless communication techniques that may be employed to facilitate communication between external programmer 300 and IMD 110 include RF communication according to the 802.11 or Bluetooth® specification sets or other standard or proprietary telemetry protocols. In this manner, other external devices may be capable of communicating with external programmer 300 without needing to establish a secure wireless connection. As described herein, telemetry circuitry 358 may be configured to transmit a spatial electrode movement pattern or other stimulation parameter values to IMD 110 for delivery of electrical stimulation therapy. Although IMD 110 may determine characteristic values for ECAP signals and control the adjustment of stimulation parameter values in some examples, programmer 300 may perform these tasks alone or together with IMD 110 in a distributed function.

[0089] In some examples, selection of stimulation parameters or therapy stimulation programs are transmitted to the medical device for delivery to a patient (e.g., patient 105 of FIG. 1). In other examples, the therapy may include medication, activities, or other instructions that patient 105 must perform themself or a caregiver perform for patient 105. In some examples, external programmer 300 provides visual, audible, and / or tactile notifications that indicate there are new instructions. External programmer 300 requires receiving user input acknowledging that the instructions have been completed in some examples.

[0090] User interface 356 of external programmer 300 may also be configured to receive an indication from a clinician instructing a processor of the medical device to update one or more therapy stimulation programs or to update the target characteristic values for ECAP signals.Updating therapy stimulation programs and target characteristic values may include changing one or more parameters of the stimulation pulses delivered by the medical device according to the programs, such as amplitude, pulse width, frequency, and / or pulse shape of the therapy pulses and / or control pulses. User interface 356 may also receive instructions from the clinician commanding any electrical stimulation, including therapy stimulation and control stimulation, to commence or to cease. User interface 356 may also receive user input and / or display information as described herein.

[0091] Power source 360 is configured to deliver operating power to the components of external programmer 300. Power source 360 may include a battery and a power generation circuit to produce the operating power. In some examples, the battery is rechargeable to allow extended operation. Recharging may be accomplished by electrically coupling power source 360 to a cradle or plug that is connected to an alternating current (AC) outlet. In addition, recharging may be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within external programmer 300. In other examples, traditional batteries (e.g., nickel cadmium or lithium ion batteries) may be used. In addition, external programmer 300 may be directly coupled to an alternating current outlet to operate.

[0092] The architecture of external programmer 300 illustrated in FIG. 3 is shown as an example. The techniques as set forth in this disclosure may be implemented in the example external programmer 300 of FIG. 3, as well as other types of systems not described specifically herein. Nothing in this disclosure should be construed so as to limit the techniques of this disclosure to the example architecture illustrated by FIG. 3.

[0093] FIG. 4 is a graph 402 of example evoked compound action potentials (ECAPs) sensed for respective stimulation pulses, in accordance with one or more techniques of this disclosure. As shown in FIG. 4, graph 402 shows example ECAP signal 404 (dotted line) and ECAP signal 406 (solid line). In some examples, each of ECAP signals 404 and 406 are sensed from stimulation pulses that were delivered from a guarded cathode, where the control pulses are biphasic pulses including an interphase interval between each positive and negative phase of the pulse. In some such examples, the guarded cathode includes stimulation electrodes located at the end of an 8-electrode lead (e.g., leads 130 of FIG. 1) while two sensing electrodes are provided at the other end of the 8-electrode lead. ECAP signal 404 illustrates the voltage amplitude sensed as a result from a sub-detection threshold stimulation pulse. In other words, the stimulation pulse did not elicit a detectable ECAP signal in ECAP signal 404. Peaks 408 of ECAP signal 404 are detected and represent the artifact of the delivered stimulation pulse (e.g., a control pulse that may or may not contribute to a therapeutic effect for the patient). However, no propagating signal is detected after the artifact in ECAP signal 404 because the stimulation pulse was sub-detection threshold (e.g., the intensity of the stimulation pulse was insufficient to cause nerve fibers to depolarize and generate a detectable ECAP signal).

[0094] In contrast to ECAP signal 404, ECAP signal 406 represents the voltage amplitude detected from a supra-detection threshold stimulation pulse. Peaks 408 of ECAP signal 406 are detected and represent the artifact of the delivered stimulation pulse. After peaks 408, ECAP signal 406 also includes peaks Pl, Nl, and P2, which are three typical peaks representative of propagating action potentials from an ECAP. The example duration of the artifact and peaks Pl, Nl, and P2 is approximately 1 millisecond (ms). The time between two points in the ECAP signal may be referred to as a “latency” of the ECAP and may indicate the types of fibers being captured by the control pulse. ECAP signals with lower latency (i.e., smaller latency values) indicate a higher percentage of nerve fibers that have faster propagation of signals, whereas ECAP signals with higher latency (i.e., larger latency values) indicate a higher percentage of nerve fibers that have slower propagation of signals. Other characteristics of the ECAP signal may be used in other examples. Although stimulation amplitudes and ECAP amplitudes are generally described for the growth curves described here, the system may determine growth curves of latencies from the ECAP signals for different amplitudes or other different parameter values of the respective pulses from which the ECAP signals were sensed. In this manner, the system may analyze the growth curves of latencies with respect to parameter values changes to identify one or more parameter values to define subsequent stimulation pulses and / or a target latency to achieve during stimulation therapy.

[0095] The amplitude of the ECAP signal (e.g., of peaks within the ECAP signal) generally increases with increased amplitude of the stimulation pulse, as long as the pulse amplitude is greater than the threshold such that nerves depolarize and propagate the signal. The target ECAP characteristic (e.g., the target ECAP amplitude) may be determined from an ECAP signal associated with a neural response detected from pulses delivering therapy to patient 105 (FIG. 1). The ECAP signal thus is representative of the distance between the stimulation electrodes and the nerves appropriate for the stimulation parameter values of the pulses delivered at that time.

[0096] In some examples, processing circuitry 210 (FIG. 2) or other devices may be configured to determine a characteristic value for an ECAP signal, for example, from multiple different features of one or more signals associated with the ECAP signal. The characteristic value of the ECAP signal may be determined by removing an artifact from the ECAP signal using the processing circuitry. These different features may be incorporated into an average, weighted average, or other combination that represents the relative action potentials of the ECAP signal. Processing circuitry 210 may determine the characteristic value from different features of the same signal, such as the amplitude difference between two peaks in the ECAP signal and theamplitude difference between two different peaks in the ECAP signal. As another example of features from the same signal, processing circuitry 210 may determine the characteristic value based on an average of two different peaks in the second derivative signal. Alternatively, processing circuitry 210 may determine the characteristic value of the ECAP signal from features obtained from different signals. For example, processing circuitry 210 may determine the difference between the minimum and maximum values of the first derivative of the ECAP signal on either side of the P2 peak, determine the maximum value of the second derivative of the ECAP signal, and combine each of these factors into a single characteristic value of the ECAP signal. This single characteristic value of the ECAP signal may be referred to as a “composite” characteristic value because it is a composite of several different factors derived from the ECAP signal in order to obtain a more complete representation of the ECAP signal.

[0097] In one or more examples, the ECAP characteristic values may be determined after subtracting the artifact, to the extent an artifact may be present during some portion of the sensed ECAP signal. In some examples, that artifact may be modeled as a sum of exponential and a linear component. In another example, the artifact may be modeled sufficiently by either an exponential or a linear component alone. In order to fit the artifact to the response for the growth curve, several methods may be used. In one or more examples, the method may include estimating a minimum in the error function between the artifact model and the measured response. For example, if parameters of the function are P (e.g., time constant of the exponential, gain and linear slope and offset), the error function may be:Err(P) = E[E(t) - A(P, t)]

[0098] The optimal fit is to find Popt where the error Err(P) is minimized. The ECAP characteristic value may be determined the recording E(t) as:ECAP(t) = E(t) - A(Popf, t)

[0099] A common error function Err is something like a norm-2, which is defined as E = sqrt[sum_t( (E(t) - A(P,t))2]

[0100] An example model A(P, t) with four parameters is as follows: A(P, t) = exp(-t / P(l))*P(2) + 1 * P(3) + P(4)

[0101] In one or more examples, the error function may be modified by a weight function W(t), where W(t) is high for instances where the neural response is low, for example, in the first region. For example, the W function may be high for t early in the measured waveform E(t) (e.g., prior to neural response developing), and low where the neural response can be high. In some examples, W(t) can be higher after the response.E[P] = sqrt(

[0102] In this way, the model can be fit more specifically to the artifact, and not to the neural response, for example, for the first region. The weight can thus be adjusted by the system to reduce the effect of any stimulation artifact while maintaining the desired ECAP components of the signal. Note that, for this analysis, a uniform weight W may be used, so this feature may be optional.

[0103] It is also understood that, once the time constant P(l) is estimated, the rest of the parameters may be solved. For instance, in some examples, if M is defined as a matrix with rows [exp(-t / P(l)) t 1] and Wm is a matrix with diagonal equal to W, then parameters P(2) to P(4) may be:Pend = (A'*diag(W’)*diag(W)*A)\(A'* diag(W’)*diag(W)*data)

[0104] In the above table, the “\” operator is a matrix inversion operator and diag(W) transforms the weight vector of length n to a matrix of weight n with contents of W. Features of interest in W may include high starting level (where most of the artifact is contained but ECAP response is low), and low weight for features which may contain the main ECAP energy (e.g. around samples 20 and 40). In addition, weight W might contain peaks corresponding to typical transition regions (e.g. peak around sample 11 or sample 30).

[0105] For real-time systems, the matrix multiplication operation may be fairly efficient. Thus, there may be an adaptive procedure to solve for P(l) (for example by back-propagation of error method) and then an analytic method to solve for P(2) to P(4). In one or more examples, if the artifact can change fairly rapidly, the speed of the back-propagation type of algorithm may be adjusted depending on the error term (e.g., large errors can lead to faster adaptation of P(l)). In some examples, either P(l) or range of P(l) can be estimated using equipment external to the implant, such as a clinician programmer or a patient programmer.

[0106] For certain weight functions, the equation for Pend can be a sparse equation and can be reduced to a non-FIR filter model. In addition, several P( 1 ) candidates may be evaluated and the smallest one can be selected for the algorithm. Another alternative may be to determine evaluate several P( 1 ) candidates and to pick the minimum one, but to utilize the adjacent near-by measurements to fit a curve, e.g. a parabola, to more precisely determine the location of the minimum. In this way, accuracy of the estimated neural response may be improved with fewer evaluations.

[0107] In one or more examples, the artifact may be removed from the ECAP using various methods, including, but not limited to, a standard method, artifact model method, high-pass filter method, or a correlation method, where each method uses the processing circuitry to determine the ECAP characteristic value.

[0108] In using the standard method (SM) to determine an ECAP characteristic value, waveforms Vi(t) may be low-pass filtered (Kaiser filter, 11 tap, 4.5 kHz) to further band-limit and reduce asynchronous noise. In one or more examples, ECAP amplitude may be subsequently estimated (e.g., calculated) as a difference (e.g., in amplitude, such as in pV) between the P2 and N1 features of the ECAP. In one or more examples, N1 may be defined as the minimum amplitude of the filtered waveform in the temporal window from 0.3 to 0.6 milliseconds (ms), while P2 may be defined as the maximum amplitude in the temporal window from 0.7 to 1.1 ms. These windows of time may be set given the anticipated latencies and morphological characteristics of the ECAP. The latencies may be a function of the spacing between the stimulating and recording electrodes, along with the expected conduction velocity of ECAPs in the spinal cord. In case of a large artifact that starts positive and decays over time, it is possible that the N1 is greater than P2, where the N1-P2 may be computed to be negative.

[0109] The processing circuitry 210 may also, or alternatively, use an artifact model (AM) to determine a ECAP characteristic value. In one or more examples, the stimulation artifact may be composed of two decaying exponentials with different time constants. In one or more examples, over a relatively short post-stimulation window for estimating spinal ECAPs, for example, 1.5 ms, an artifact may be suitably modeled as the sum of a single exponential plus a linear component, which may more accurately estimate the ECAP amplitude. If Vi(t) is the recorded voltage waveform after averaging, the estimate of artifact A(t) may be obtained by optimally fitting the following equation to data Vi(t): i4(t) = c exp(—t / T) + c2t + c3

[0110] The fit may be performed by determining the minimum in the following error function over parameters cl, c2, c3, and T:[OHl] To solve this optimization problem, T may be varied from 50 to 800 ps in 100 logarithmic steps. For each T, E(T) may BE determined by solving the following closed-form matrix equation:C = (M’M)\(M’V)E(T) = Norm(V-M C)

[0112] In the above equation, to may be the sampling period, C is a 3x1 vector of optimal c coefficients, V may be a vector composed of measured samples V(t), and Norm may represent a norm-2 operation. Optimal T may be determined to be one that produced the smallest E(T) . The equation above was utilized to compute the C coefficients. After the artifact model is determined, the N1-P2 amplitude may be calculated or estimated from the denoised waveform V(t)-A(t) using the same N1 and P2 windows as in the standard method.

[0113] In one or more examples, the processing circuitry 210 may also, or alternatively, use a high-pass filter (HP) method. For example, the stimulation artifact may contain lower-frequency content relative to the ECAP in the later portion of the biopotential recording (e.g., greater than 0.6 ms after the end of the stimulation pulse). As such, another approach for mitigating the stimulation artifact overlapping the ECAP may be application of a high pass or differentiator filter. Such a filter may have the following benefits. The first peak response of the differentiator occurs at the high-slope transition of the ECAP from N1 to P2. This response may be delayed relative to Nl, the first feature of the ECAP used by the SM to calculate the ECAP, and advantageously results in extra temporal isolation between the signal and the artifact with the differentiator. In addition, a simple differentiator may be implemented in a very computationally efficient manner, an important consideration for battery powered implantable medical devices.

[0114] A comb filter with response 1 - z'2may be utilized as a differentiator for the acquired biopotentials. After application of the differentiator filter, the waveform may be smoothed (Kaiser, FIR 11 tap filter; cutoff 4.5 kHz). The ECAP response may be computed as the difference between the maximum output in the temporal window from approximately 0.6 to 0.85 ms to the minimum output in the window from approximately 0.9 to 1.125 ms. The temporal windows may be set using similar considerations to those employed with the standard method.

[0115] The processing circuitry 210 may also, or alternatively, use a correlation method (CM) which estimates spinal cord activation by correlating the acquired biopotential with a synthesized filter template, T(t). Specifically, the neural response may be computed as:

[0116] The template used here may have a mathematical expression of T(t) = B(t) sin(47tt / 1.3) / N, where t is time in ms, B(t) is the Bartlett window, and Ais the normalization factor, N = sum( B(t)2sin(47rt / 1.3)2 ) over a 1.3-ms window, for example. The template may approximate the morphology of a typical ECAP signal. A duration of 1.3 ms may be used to optimize the match of the template with the observed response. The template may be orthogonal to the first three components of a Taylor expansion of the artifact waveform, namely the constant term, the linear term and the quadratic term. Thus, when the template is applied to a waveformcontaining both neural response and artifact, the artifact component may be reduced. However, variable latencies in neural responses routinely occur due to the differences in conduction velocities across subjects and delay in action potential initiation across stimulation levels or pulse width. The template may be matched to the neural recording and Fourier techniques may be utilized accordingly to compute the optimal delay, A.

[0117] In some examples, to account for variability in neural response latencies, while avoiding non-physiological shifts in the response, the system may prevent A from decreasing below 0 or increasing above 0.18 ms.

[0118] FIG. 5 is a conceptual diagram of an example ECAP signal 530 superimposed to an example lead 500 carrying a plurality of electrodes 504 carried on housing 502. Lead 500 may be an example of any of leads described herein, such as leads 130 or 230. As described in FIG. 4, peaks (and troughs) of ECAP signal 530 can be used to detect nerve fiber activation. However, the peaks and troughs (or other desired feature) of ECAP signal 530 may not line up with the electrodes 504 of lead 500. Although the example of FIG. 5 is described with respect to an elicited signal such as ECAP, inherent electrical signals in the body may also be sensed in a similar fashion.

[0119] In the example of FIG. 5, electrodes 504A and 504B may be used to deliver a suprathreshold stimulus that elicits ECAP signal 530. ECAP signal 530 may include different peaks, such as peaks Pl, Nl, and P2. In some examples, Nl may be referred to as a trough. The maximum potential difference within ECAP signal 530 is generally between Nl and P2. This amplitude difference may be calculated by the system am used as the characteristic of the ECAP signal 530. Generally, the largest potential within the signal may be used because it is easier to identify consistently. However, such as shown in FIG. 5, peaks Nl and P2 do not line up spatially with any two electrodes. P2 lines up with the most distal electrode 504H (line 532C), but Nl falls between electrodes 504F (line 532A) and 504G (line 532B). If the system were to use electrode 504G as the first polarity electrode and electrode 504H as the second polarity electrode in a two electrode sensing electrode combination, the electrodes may not be able tocapture the actual amplitude difference between N1 and P2. This is because the electrodes are not spatially aligned to the propagating signal.

[0120] However, the system could use fractional contributions of electrode 504F and electrode 504G together as the first polarity of the sensing combination, with electrode 504H as the second polarity. Since N1 appears to fall in the middle between electrodes 504F and 504G, each electrode 504F and 504G may be assigned a contribution of 50% or one half. In this manner, half of the potential sensed by each electrode can be summed and used together with electrode 504H to capture full amplitude differential between N1 and P2. If peak N1 falls closer to a specific electrode, that electrode can have a higher fractional contribution than the other electrode in the same polarity, such as a ratio of 80% to 20%, for example. The system may be configured to assign any fractional contribution between 0% and 100% for any electrode. In some examples, the system may be limited to some set integers or fractional options. This limitations may be hardware and / or software imposed as determined for performance and / or other design considerations. In some examples, each polarity of the sensing electrode combination may include two or more electrodes that each have a respective fractional contribution. The system may also identify the sensing window for ECAP signal 530. For example, the system may calculate the time needed to ensure that the system senses peaks N 1 and P2 (without other peaks) if those peaks are the features of interest.

[0121] The system may implement the concept of fractional contributions of different electrodes various ways. For example, the system may employ two amplifiers that are configured to record respective signals (e.g., respective ECAP signals). These two amplifiers can operate to sense simultaneously or in close succession (e.g., across the different electrode combinations in response to respective adjacent stimuli pulses). After two signals (e.g., waveforms) are acquired from the respective electrode combinations, the system can digitally combine the signals according to the fractional contributions. For example, referring to FIG. 5, if one amplifier is configured to sense between electrodes 504F and 504G (Wl(t)), and another amplifier is configured to record between electrodes 504G and 504H (W2(t)), then recording between two virtual points at spacing equal to that between 504F and 505G between 504F and 504H could be estimated as (1 -alpha)* Wl(t)+alpha*W(2), with alpha being the fractional weighting. Put another way, larger fractional contributions, or weights, can effectively “shift” the sensing location towards the more heavily weighted electrodes. This technique can provide an estimate of a physiological signal (e.g., an ECAP) in intermediate locations if the spacing between the electrodes (distance 504F to 504G and 504H to 504H) is relatively small compared to the spatial wavelength of the underlying action potential (equal to spike duration multiplied by spike propagation velocity). For human action potentials, the spike duration may be about 0.5microseconds (ms), and the space constant for a spike may be about 0.5 msec * 50 m / sec = 25 mm. In other examples, the system may sense from different electrode combinations at the same time, or in very close succession, in order to sense the same passing signal using the different electrode combinations. Again, these generated sensed signals from the different electrode combinations may be weighted according to their fractionalized contributions in order to improve the spatial alignment of the sensing to the passing wave.

[0122] FIG. 6 is an example user interface 600 configured to display sense electrode configurations and fractional contributions from each sense electrode to a sensed signal. User interface 600 may be an example of user interface 356 of external programmer 150 and be presented on a presence sensitive display. As shown in the example of FIG. 6, user interface 600 includes various display and input fields. For example, a representation of electrodes (and leads in some examples) implanted within the patient may be provided. Both of leads 602A and 602B are shown with respect to vertebral levels T8 and T9 of the patent. On this representation of the electrodes, user interface 600 may indicate the electrode combination 604 that is selected to deliver stimulation pulses and the sensing electrodes 608A, 608B, and 608C (collectively “sensing electrode combination 608) selected to sense ECAP signals elicited by the pulses generated by electrode combination 604. Sensing electrode combination 608 may be referred as such because it generates virtual electrode combination with the virtual electrode between electrodes 608 A and 608B. In some examples, where each electrode is part of a respective electrode combination to produce respective signals that are later combined, user interface 600 may illustrate these electrode combinations differently. For example, each electrode combination (e.g., first combination with electrodes 608C and 608B and second combination with electrodes 608C and 608A) may be shown separately with the fractional contributions presented for each electrode combination instead of for each electrode of the same polarity as shown in FIG. 6. Although the fractionalized contributions are described with respect to the electrodes of the same polarity in some examples, the fractionalized contributions may be associated with entire electrode combinations in other examples.

[0123] The screen in user interface 600 can display the result of the sensing electrode combination selection process that can utilize fractional contributions for two or more electrodes of any polarity for sensing. As shown in the example of FIG. 6, sensing electrodes 608 have been selected at the opposite end of lead 602 from electrodes 604. Electrode 608C may have a first electrode polarity for sensing an identified as electrode “0” in the screen. Electrodes 608A and 608B may collectively form the second electrode polarity 610 and collectively be used to sense the electrical potential with electrode 608C. Electrode 608B is identified as electrode “1” and electrode 608A is identified as electrode “2”. The physical size of each electrode mayvisually represent the contribution to sensing. Electrode 608C uses 100% and is the largest. Electrode 608B is assigned only 30% fractional contribution and is the smallest while electrode 608 A is assigned 70% fractional contribution and is larger than electrode 608B. Numerical indications 612A and 612B also provide the numerical fractional contribution for each electrode. If the user, or system, makes any changes to these fractional contributions, user interface 600 can update these visual indications of the fractional contributions of each electrode.

[0124] User interface 600 can also provide interactive fields associated with the sensing electrode combination. Percentage field 620 may be configured to show the respective fractional contribution for each electrode and, in some examples, accept user input changing any of the fractional contributions. Polarity field 622 may be used to show the polarity each electrode is associated with for sensing and, in some examples, also accept user input changing any of the polarities. Although sensing electrodes may not be described has having a polarity, the polarity as described herein for sensing may refer to how the electrodes are connected to the sensing circuitry for detecting the electrical potential within tissue. Switching the polarity of the electrodes in an sensing electrode combination may merely flip the amplitudes from positive to negative. When comparing signals over time, the system may attempt to maintain one polarity at the end of the lead or the polarities to be the same with respect to lead orientation or signal source in order to maintain sensed signal orientation.

[0125] If the user desires to accept the shown sensing configuration in user interface 600, the user can select accept sense configuration button 624, and the system can move to a different programming screen or therapy delivery screen. If the user desires that the system re-run the selection process for the sensing electrode combination and / or fractional contributions, the user can select re-run sense button 626. In response to receiving selection of button 626, the system may again sense signals with different electrodes and / or fractional contributions in order to identify a different sensing electrode combination and / or fractional contributions.

[0126] FIG. 7 is a flow diagram illustrating an example technique for determining a fractional contributions for each electrode of a sense electrode combination. IMD 200 and processing circuitry 210 will be described in the example of FIG. 7, but other IMDs, such as IMD 110, or other devices (e.g., external programmer 150) or systems may perform, or partially perform, the technique of FIG. 7.

[0127] As shown in the example of FIG. 7, processing circuitry 210 can select one or more first polarity electrodes for sensing a signal, such as an ECAP signal (700). Processing circuitry 210 can then select second polarity electrodes for sensing the signal (702). As described herein, electric potential from the tissue may be sensed between the first polarity electrode(s) and the second polarity electrodes. Therefore different electrode combinations may be created forsensing respective signals using the one or more first polarity electrode(s) and the respective second polarity electrodes. Processing circuitry 210 may select electrodes at known locations to start with or evaluate multiple electrodes as options.

[0128] Processing circuitry 210 may then determine fractional contributions to the sensed signal for each electrode of the second polarity electrodes (704). For example, processing circuitry 210 may iteratively sense different signals (e.g., ECAP signals) elicited by the same stimulus electrodes using different fractional contributions for the electrodes. Processing circuitry 210 may then select the fractional contributions for the electrodes that results in the sensed signal that has the largest amplitude, largest signal to noise ratio, or reduces total noise or a specific noise source from the signal. Processing circuitry 210 can then control sensing circuitry 206 to sense the signal according to the selected sensing electrode combination(s) and fractional contributions for at least some electrodes (706). In some examples, processing circuitry 210 may control sensing circuitry 206 to generate sensed signals for each electrode combination, receive information representative of the sensed signals from each electrode combination, and then generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination. In this manner, processing circuitry 210 may digitally weight each sensed signal according to the fractionalized contributions.

[0129] Processing circuitry 210 may repeat this process of FIG. 7 in response to identified issues with sensing and / or at the request of a user. For example, processing circuitry 210 may monitor noise characteristics of sensed signals using the fractional contributions for the electrodes for changes over time. Noise from different electrode combinations may change due to lead migration, lead fractures, electrode-tissue interface changes, or other factors. In some examples, processing circuitry 210 may determine a noise characteristic of one or more sensed signals sensed over time and using a first fractional contributions of the electrode combination(s). Processing circuitry 210 can compare the noise characteristic to a noise threshold. The noise threshold may be a preset value or a percentage or scale based on the initial noise characteristic of the sensed signals using the first fractional contributions. Processing circuitry 210 can determine that the noise characteristic exceeds the noise threshold, and, responsive to determining that the noise characteristic exceeds the noise threshold, determine a second fractional contributions for each electrode combination resulting in a noise characteristic below the noise threshold. Processing circuitry 210 may sense signals using different fractional contributions and / or other electrode combinations in order to identify a second fractional contributions from the same or different electrode combinations. Processing circuitry 210 canthen generate subsequent physiological signals based on subsequently sensed signals and the second fractional contributions for each electrode combination.

[0130] FIG. 8 is a flow diagram illustrating an example testing different sense electrodes and fractional contributions from each electrode for determining a sense electrode combination for sensing subsequent signals from a patient. IMD 200 and processing circuitry 210 will be described in the example of FIG. 8, but other IMDs, such as IMD 110, or other devices (e.g., external programmer 150) or systems may perform, or partially perform, the technique of FIG. 8.

[0131] In one or more examples, processing circuitry 210 receives a request to determine a sensing electrode combination, which may include fractional contributions from two or more electrodes if appropriate (800). For example, processing circuitry 210 may receive this request from the system or according to instructions upon initial system setup for a user. In other examples, processing circuitry 210 may receive the request from a user (e.g., clinician or patient) in response to possible issues with therapy. Processing circuitry 210 then controls IMD 200 to deliver a stimulus (802). In some examples, the stimulus may be delivered from a stimulation electrode combination according to a set of stimulation parameters that define the stimulus. The set of stimulation parameters may be selected to deliver a stimulus that is supra-threshold and elicits a detectable ECAP signal (or other signal to be sensed). In an initial setup phase, the system may be configured to determine these stimulation parameters may delivering a sweep of pulses at different amplitudes, pulse widths, frequences, etc. Generally, the delivered stimulus may be selected to elicit a detectable ECAP signal without being perceptible or uncomfortable by for the patient.

[0132] The processing circuitry 210 may also control IMD 200 to sense the respective ECAP signal using the selected sense electrodes and fractional contributions for that particular sensing electrode combination (804). As described herein, the selected sense electrodes may be part of one or more electrode combinations, wherein the fractional contributions are applied via hardware to the signals being sensed and / or digitally weighted by processing circuitry 210 after multiple signals are sensed from respective electrode combinations and according to the fractional contributions from each electrode combination. The fractional contributions may be for only one of the sensing polarities or for both sensing polarities. Processing circuitry 210 can then determine an ECAP characteristic value from the sensed signal (806). This ECAP characteristic value may be the value that processing circuitry 210 would be able to obtain during sensing. The value may be representative of the amplitude between two peaks, or at least the largest amplitude that can be detected using the selected electrodes and selected fractional contributions. In some examples, the ECAP characteristic values may comprise the ECAP signal information with an artifact removed therefrom. In one or more examples, removing the artifactmay include modeling, for example by the processing circuitry, the artifact as a sum of a single exponential component plus a linear component, and removing the sum from each ECAP signal. In yet another example, the artifact may be sufficiently modeled solely as a linear component or exponential. In some examples, modeling the artifact by the processing circuitry includes estimating a minimum of an error function by weighting the error function higher in a first region than in a second region, where the first region is prior to a patient neural response and the second region is after the patient neural response. In one or more examples, removing the artifact includes passing the ECAP signal through a high-pass filter.

[0133] Processing circuitry 210 can then determine if another fractional contribution and / or electrode combination should be tested (808). If processing circuitry 210 determines that another test should be run (“YES” branch of block 808), processing circuitry 210 selects the next fractional contributions, such as from memory or according to a procedure, (810), processing circuitry again delivers a stimulus (802) and senses the resulting ECAP signal using the new fractional contributions (804). If processing circuitry 210 determines that no more tests need to be run (“NO” branch of block 808), processing circuitry 210 can select the sense electrodes and fractional contributions that resulted in the best or desired ECAP characteristic value for subsequent sensing (812). Processing circuitry 210 may follow a decision criteria or certain logic process for this determination. Processing circuitry 210 can also determine the sensing window(s) for sensing the subsequent ECAP signals using the sense electrodes based on the timing of one or more aspects of the ECAP signal (814). For example, processing circuitry 210 may identify the window to align with a majority of each desired peak (e.g., peaks N1 and P2) or some other criteria. Processing circuitry 210 can then proceed to monitor subsequent ECAP signals using the selected electrodes (and fractional contributions) and sensing window(s) (816).

[0134] FIG. 9 is a flow diagram illustrating an example technique for determining an ECAP threshold and controlling electrical stimulation using an ECAP characteristic of the ECAP signal. For convenience, FIG. 9 is described with respect to IMD 200 of FIG. 2. However, the technique of FIG. 9 may be performed by different components of IMD 200 or by additional or alternative devices. The technique of FIG. 9 is an example feedback mechanism for controlling stimulation therapy using sensed ECAP signals.

[0135] As illustrated in FIG. 9, processing circuitry 210 of IMD 200 delivers a stimulation pulse and senses the resulting ECAP elicited by the stimulation pulse (902). For example, processing circuitry 210 may control sensing circuitry 206 to use fractional contributions from electrodes of at least one sensing polarity. Processing circuitry 210 receives and analyzes the ECAP to determine an ECAP characteristic value (904). The processing circuitry 210 evaluates whether the ECAP characteristic value has exceeded the target ECAP value (906). The targetECAP value may be based on the ECAP threshold determined prior. In some examples, the processing circuitry 210 may target a lesser percentage than the ECAP characteristic value associated with the ECAP threshold, for example to extend battery life of IMD 200. For example, processing circuitry 210 may target 70% of the ECAP threshold. In some examples, the ECAP threshold target may include a range of values. In one or more examples, the ECAP threshold target may include a range of 30% of the ECAP threshold to an upper limit of below a discomfort threshold for a patient.

[0136] If processing circuitry 210 determines that the representative amplitude of the one or more ECAP signals is greater than the target ECAP value (“YES” branch of block 906), processing circuitry 210 decreases the amplitude of the next stimulation pulses (908). For example, the amplitudes of the stimulation pulses may be decreased by predetermined steps. As another example, the respective amplitudes of the stimulation pulses may be decreased by an amount proportional to the difference between the representative amplitude and the ECAP characteristic value associated with the neural response. If processing circuitry 210 determines that the representative characteristic value is less than the ECAP characteristic value for the target ECAP value, (“NO” branch of block 906), processing circuitry 210 moves to block 910.

[0137] At block 910, processing circuitry 210 increases the amplitude of the stimulation pulses by an amount proportional to the difference between the representative amplitude and the target ECAP characteristic value. Processing circuitry 210 then continues to deliver a stimulation pulse according to the increased or decreased amplitudes. In some examples, the decrease or increase applied to the stimulation pulses in steps 908 or 910, respectively, may apply to the amplitude or another parameter of the next-scheduled stimulation pulse. In this manner, even if a decrease is applied to the next stimulation pulse, the overall new amplitude of the next stimulation pulses may still be greater than the previous stimulation pulse if the scheduled amplitude of the next stimulation pulse minus the decrease is still greater than the amplitude of the previous stimulation pulse.

[0138] Although the process of FIG. 9 is described for adjusting the amplitude of the stimulation pulses (e.g., control pulses and / or stimulation pulses), other parameter values may be changed in other examples. For example, sensed ECAP signals may be used to increase or decrease the pulse width of the stimulation pulse to adjust the amount of charge delivered to the tissue to maintain consistent volume of neural activation. In other examples, electrode combinations may be adjusted in order to deliver different amounts of charge and modify the number of neurons being recruited by each stimulation pulse. In other examples, processing circuitry 210 may be configured to adjust the pulse rate or duty cycle of the stimulation pulses.

[0139] In some examples, therapy, such as for SCS stimulation, may be programmed. For example, setting parameter values for therapy may be based on a patient sensory threshold. In some examples, the programming and / or closed-loop control of SCS stimulation may be based on the ECAP threshold. In some examples, if stimulation therapy becomes uncomfortable, the patient may terminate the stimulation. As described herein, a configuration for measurement can be selected to facilitate a larger response, which may be different than one used for ECAP therapy.

[0140] Once the ECAP threshold is determined for each component of the program, stimulation parameters of a SCS stimulation program may be determined based on the ECAP threshold. For example, amplitude level for stimulation pulses of each program can be set as a percentage of the estimated neural threshold (e.g., 65%). Alternatively, both neural thresholds and sigma can be utilized to estimate the stimulation levels. For example, stimulation can be set to neural threshold plus 1 / sigma to get a nearly constant response.

[0141] In some instances, one can record changes in threshold in the presence of other stimulation (e.g., high-rate stimulation) and compare to lower-rate stimulation to determine proper dosing of higher-rate stimulation. In some examples, real-time measurements of ECAP signals may be used to determine ECAP characteristic values for the ECAP signals, and ECAP thresholds may be determined. The real-time determination of ECAP thresholds may be utilized to set stimulation levels. For example, occasional measurements near a sensation threshold can be utilized to measure threshold and establish a “dose” (e.g., intensity, duration, etc.) for other components of stimulation. Alternatively, when a position of the person is changed, one can adjust the stimulation automatically based on best neural threshold.

[0142] FIG. 10 is a flow diagram illustrating an example technique for tracking any changes to patient sensing over time. IMD 200 and processing circuitry 210 will be described in the example of FIG. 10, but other IMDs, such as IMD 110, or other devices (e.g., external programmer 150) or systems may perform, or partially perform, the technique of FIG. 10.

[0143] In one or more examples, processing circuitry 210 receives a request to check for sensing changes (1000). These sensing changes could be lead migration, disease progression, medication dosage or usage, or other events that could affect signal detection, such as ECAP detection. For example, processing circuitry 210 may receive this request from the system or according to instructions during therapy. In other examples, processing circuitry 210 may receive the request from a user (e.g., clinician or patient) in response to possible issues with therapy. Processing circuitry 210 then controls IMD 200 to deliver a stimulus (1002). In some examples, the stimulus may be delivered from a stimulation electrode combination according to a set of stimulation parameters that define the stimulus. The set of stimulation parameters may beselected to deliver a stimulus that is supra-threshold and elicits a detectable ECAP signal (or other signal to be sensed). This stimulus may be the same stimulus that the system has been using to detect ECAP signals during therapy delivery or otherwise used in treating or monitoring the patient. Generally, the delivered stimulus may be selected to elicit a detectable ECAP signal without being perceptible or uncomfortable by for the patient. The stimulus may or may not contribute to a therapeutic response for the patient.

[0144] The processing circuitry 210 may also control IMD 200 to sense the respective ECAP signal using the selected sense electrodes and fractional contributions for that particular sensing electrode combination (1004). As described herein, the selected sense electrodes may be part of one or more electrode combinations, wherein the fractional contributions are applied via hardware to the signals being sensed and / or digitally weighted by processing circuitry 210 after multiple signals are sensed from respective electrode combinations and according to the fractional contributions from each electrode combination. The fractional contributions may be for only one of the sensing polarities or for both sensing polarities. Processing circuitry 210 can then determine an ECAP characteristic value from the sensed signal (1006). This ECAP characteristic value may be the value that processing circuitry 210 would be able to obtain during sensing. The value may be representative of the amplitude between two peaks, or at least the largest amplitude that can be detected using the selected electrodes and selected fractional contributions. In some examples, the ECAP characteristic values may comprise the ECAP signal information with an artifact removed therefrom.

[0145] Processing circuitry 210 can then determine if another fractional contribution and / or electrode combination should be tested (1008). If processing circuitry 210 determines that another test should be run (“YES” branch of block 1008), processing circuitry 210 selects the next fractional contributions, such as from memory or according to a procedure (1010), and processing circuitry again delivers the stimulus (1002) and senses the resulting ECAP signal using the new fractional contributions (1004). In cases where processing circuitry 210 is attempting to identify minor changes to ECAP signal propagation, the same electrodes may be used but at different fractional contributions to slightly adjust sensing and look for slight adjustments. For example, processing circuitry 210 may start at the known fractional contributions and adjust the fractional contributions up or down in small increments for each iteration. In some examples, processing circuitry 210 may continue testing different fractional contributions as long as the ECAP characteristic value is increasing in amplitude which indicates a change has occurred. Processing circuitry 210 may adjust the fractional contributions in the other direction if no increases to the ECAP characteristic value occurs.

[0146] If processing circuitry 210 determines that no more tests need to be run (“NO” branch of block 1008), processing circuitry 210 can determine the sense electrodes and fractional contributions that resulted in the best or desired ECAP characteristic value for subsequent sensing (1012). Processing circuitry 210 may follow a decision criteria or certain logic process for this determination. Processing circuitry 210 can then compare the determined sense electrodes and fractional contributions to the prior used electrode configuration and fractional contributions (1014) and then output the result of the comparison (1016). For example, processing circuitry 210 may control a user interface to present the difference, or lack of difference, in the fractional contributions and / or identify the change to the patient (e.g., migration of a lead and to which direction or some other change). In some examples, processing circuitry 210 may proceed to use the new sensing electrode combination and fractional contributions to sense subsequent ECAP signals and adjust stimulation therapy. In other examples, processing circuitry 210 may recommend changes to medication or recommend a course of action to a user in response to the detected change indicated by the change in the fractional contributions determined to sense the ECAP signal.

[0147] The following examples are described herein.

[0148] Example 1. A system comprising: sensing circuitry configured to generate one or more sensed signals; and processing circuitry configured to: select a plurality of electrode combinations for sensing the one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determine fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receive information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

[0149] Example 2. The system of example 1, wherein the sensed signal is one or an evoked compound action potential (ECAP) signal or a local field potential (LFP) signal.

[0150] Example 3. The system of any of examples 1 and 2, wherein the processing circuitry is configured to determine the fractional contributions for each electrode of the plurality of second polarity electrodes by at least: controlling the sensing circuitry to generate a plurality of sensed signals at different respective electrode combinations of the plurality of electrode combinations; analyze the plurality of sensed signals for a characteristic within each signal of the plurality of sensed signals; and determine, based on the characteristic, one set of fractionalcontributions as the fractional contributions of the plurality of electrode combinations according to the respective electrodes assigned to the second polarity.

[0151] Example 4. The system of example 3, wherein the processing circuitry is configured to determine at least one timing window for detecting the sensed signal based on the characteristic of the sensed signal associated with the one set of fractional contributions of the plurality of second polarity electrodes.

[0152] Example 5. The system of any of examples 3 and 4, wherein the fractional contributions for each electrode combination are first fractional contributions for a first period of time, and wherein the processing circuitry is configured to: determine second fractional contributions for each electrode combination for a second period of time; and determine a migration of one or more electrodes of a plurality of electrodes of the plurality of electrode combinations based on the first fractional contributions and the second fractional contributions.

[0153] Example 6. The system of any of examples 1 through 5, wherein the processing circuitry is configured to determine the fractional contributions to reduce a noise characteristic of sensed signals associated with a sensing electrode combination different than the fractional contributions of the plurality of second polarity electrodes.

[0154] Example 7. The system of any of examples 1 through 6, wherein the one or more electrodes assigned the first polarity comprises at least two electrodes assigned the first polarity, and wherein the at least two electrodes assigned the first polarity have respective fractionalized contributions to the sensed signal.

[0155] Example 8. The system of any of examples 1 through 7, wherein the processing circuitry is configured to control stimulation circuitry to deliver an electrical signal that elicits a neurological response detected as the sensed signal.

[0156] Example 9. The system of any of claims 1 through 8, wherein the one or more sensed signals are sensed during a first period of time, wherein the fractional contributions for each electrode combination are a first fractional contributions, and wherein the processing circuitry is configured to: receive one or more sensed signals according to the first fractional contributions during a second period of time subsequent to the first period of time, determine a noise characteristic of the one or more sensed signals during the second period of time; determine that the noise characteristic exceeds a noise threshold; responsive to determining that the noise characteristic exceeds the noise threshold, determine a second fractional contributions for each electrode combination resulting in a noise characteristic below the noise threshold; and generate a subsequent physiological signal based on subsequently sensed signals and the second fractional contributions for each electrode combination.

[0157] Example 10. The system of any of examples 1 through 9, wherein the processing circuitry is configured to adjust, based on the sensed signal, at least one stimulation parameter that defines stimulation therapy.

[0158] Example 11. The system of any of examples 1 through 10, further comprising an implantable medical device that comprises the sensing circuitry and the processing circuitry.

[0159] Example 12. A method comprising: selecting, by processing circuitry, a plurality of electrode combinations for sensing, by sensing circuitry one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determining, by the processing circuitry, fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receiving, by the processing circuitry, information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generating, by the processing circuitry, a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

[0160] Example 13. The method of example 12, wherein the sensed signal is one or an evoked compound action potential (ECAP) signal or a local field potential (LFP) signal .

[0161] Example 14. The method of any of examples 12 and 13, wherein determining the fractional contributions for each electrode of the plurality of second polarity electrodes comprises: controlling the sensing circuitry to generate a plurality of sensed signals at different respective electrode combinations of the plurality of electrode combinations; analyze the plurality of sensed signals for a characteristic within each signal of the plurality of sensed signals; and determine, based on the characteristic, one set of fractional contributions as the fractional contributions of the plurality of electrode combinations according to the respective electrodes assigned to the second polarity.

[0162] Example 15. The method of example 14, further comprising determining at least one timing window for detecting the sensed signal based on the characteristic of the sensed signal associated with the one set of fractional contributions of the plurality of second polarity electrodes.

[0163] Example 16. The method of any of examples 14 and 15, wherein the fractional contributions for each electrode combination are first fractional contributions for a first period of time, and wherein the method further comprises: determining second fractional contributions for each electrode combination for a second period of time; and determining a migration of one or more electrodes of a plurality of electrodes of the plurality of electrode combinations based on the first fractional contributions and the second fractional contributions.

[0164] Example 17. The method of any of examples 12 through 16, wherein determining the fractional contributions comprises determining the fractional contributions to reduce a noise characteristic of sensed signals associated with a sensing electrode combination different than the fractional contributions of the plurality of second polarity electrodes.

[0165] Example 18. The method of any of examples 12 through 17, wherein the one or more electrodes assigned the first polarity comprises at least two electrodes assigned the first polarity, and wherein the at least two electrodes assigned the first polarity have respective fractionalized contributions to the sensed signal.

[0166] Example 19. The method of any of examples 12 through 18, further comprising controlling stimulation circuitry to deliver an electrical signal that elicits a neurological response detected as the sensed signal.

[0167] Example 20. The method of any of examples 12 through 19, further comprising adjusting, based on the sensed signal, at least one stimulation parameter that defines stimulation therapy.

[0168] Example 21. The method of any of claims 12 through 20, wherein the one or more sensed signals are sensed during a first period of time, wherein the fractional contributions for each electrode combination are a first fractional contributions, and wherein the method further comprises: receiving one or more sensed signals according to the first fractional contributions during a second period of time subsequent to the first period of time, determining a noise characteristic of the one or more sensed signals during the second period of time; determining that the noise characteristic exceeds a noise threshold; responsive to determining that the noise characteristic exceeds the noise threshold, determining a second fractional contributions for each electrode combination resulting in a noise characteristic below the noise threshold; and generating a subsequent physiological signal based on subsequently sensed signals and the second fractional contributions for each electrode combination.

[0169] Example 22. A non-transitory computer-readable medium comprising instructions that, when executed, control processing circuitry to: select a plurality of electrode combinations for sensing, by sensing circuitry, one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determine fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receive information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

[0170] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware or any combination thereof. For example, various aspects of the described techniques may be implemented within one or more processors or processing circuitry, including one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A control unit including hardware may also perform one or more of the techniques of this disclosure.

[0171] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various operations and functions described in this disclosure. For example, processing circuitry may conduct processing off-line and conduct automatic checks of patient ECAP signals and update programming from a remote location. In addition, any of the described units, circuits or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as circuits or units is intended to highlight different functional aspects and does not necessarily imply that such circuits or units must be realized by separate hardware or software components. Rather, functionality associated with one or more circuits or units may be performed by separate hardware or software components or integrated within common or separate hardware or software components.

[0172] The techniques described in this disclosure may also be embodied or encoded in a computer-readable medium, such as a computer-readable storage medium, containing instructions that may be described as non-transitory media. Instructions embedded or encoded in a computer-readable storage medium may cause a programmable processor, or other processor, to perform the method, e.g., when the instructions are executed. Computer readable storage media may include random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electronically erasable programmable read only memory (EEPROM), flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media.

Claims

WHAT IS CLAIMED IS:

1. A system comprising: sensing circuitry configured to generate one or more sensed signals; and processing circuitry configured to: select a plurality of electrode combinations for sensing the one or more sensed signals, wherein the plurality of electrode combinations comprise one or more electrodes assigned a first polarity and two or more electrodes assigned a second polarity opposite the first polarity; determine fractional contributions for each electrode combination of the plurality of electrode combinations for sensing the one or more sensed signals; receive information representative of the one or more sensed signals generated by the sensing circuitry using the plurality of electrode combinations; and generate a physiological signal based on the one or more sensed signals and the fractional contributions for each electrode combination.

2. The system of claim 1, wherein the sensed signal is one or an evoked compound action potential (ECAP) signal or a local field potential (LFP) signal.

3. The system of any of claims 1 and 2, wherein the processing circuitry is configured to determine the fractional contributions for each electrode of the plurality of second polarity electrodes by at least: controlling the sensing circuitry to generate a plurality of sensed signals at different respective electrode combinations of the plurality of electrode combinations; analyze the plurality of sensed signals for a characteristic within each signal of the plurality of sensed signals; and determine, based on the characteristic, one set of fractional contributions as the fractional contributions of the plurality of electrode combinations according to the respective electrodes assigned to the second polarity.

4. The system of claim 3, wherein the processing circuitry is configured to determine at least one timing window for detecting the sensed signal based on the characteristic of the sensed signal associated with the one set of fractional contributions of the plurality of second polarity electrodes.

5. The system of any of claims 3 and 4, wherein the fractional contributions for each electrode combination are first fractional contributions for a first period of time, and wherein the processing circuitry is configured to: determine second fractional contributions for each electrode combination for a second period of time; and determine a migration of one or more electrodes of a plurality of electrodes of the plurality of electrode combinations based on the first fractional contributions and the second fractional contributions.

6. The system of any of claims 1 through 5, wherein the processing circuitry is configured to determine the fractional contributions to reduce a noise characteristic of sensed signals associated with a sensing electrode combination different than the fractional contributions of the plurality of second polarity electrodes.

7. The system of any of claims 1 through 6, wherein the one or more electrodes assigned the first polarity comprises at least two electrodes assigned the first polarity, and wherein the at least two electrodes assigned the first polarity have respective fractionalized contributions to the sensed signal.

8. The system of any of claims 1 through 7, wherein the processing circuitry is configured to control stimulation circuitry to deliver an electrical signal that elicits a neurological response detected as the sensed signal.

9. The system of claim 8, further comprising the stimulation circuitry.

10. The system of claim 9, further comprising an implantable medical device comprising the sensing circuitry and the stimulation circuitry.

11. The system of any of claims 1 through 10, wherein the processing circuitry is configured to adjust, based on the sensed signal, at least one stimulation parameter that defines stimulation therapy.

12. The system of any of claims 1 through 11, wherein the one or more sensed signals are sensed during a first period of time, wherein the fractional contributions for each electrodecombination are a first fractional contributions, and wherein the processing circuitry is configured to: receive one or more sensed signals according to the first fractional contributions during a second period of time subsequent to the first period of time, determine a noise characteristic of the one or more sensed signals during the second period of time; determine that the noise characteristic exceeds a noise threshold; responsive to determining that the noise characteristic exceeds the noise threshold, determine a second fractional contributions for each electrode combination resulting in a noise characteristic below the noise threshold; and generate a subsequent physiological signal based on subsequently sensed signals and the second fractional contributions for each electrode combination.

13. The system of any of claims 1 through 12, further comprising an implantable medical device that comprises the sensing circuitry.

14. The system of any of claims 1 through 13, wherein the implantable medical device comprises the processing circuitry.

15. A non-transitory computer-readable medium comprising instructions that, when executed, control the processing circuitry to perform functions of any of claims 1 through 13.

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