Determination of electrode or lead positions

Abstract

An example system includes processing circuitry configured to determine a plurality of impedance values for a plurality of electrodes implanted, within a patient. The processing circuitry is configured to apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes. The processing circuitry is configured to determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes. The processing circuitry is configured to output information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

Description

Docket No.: A0010253WO01 / 1123-791WO01 DETERMINATION OF ELECTRODE OR LEAD POSITIONS

[0001] This application claims priority to, and the benefit of, U.S. Provisional Application No.63 / 520,019, filed August 16, 2024, and entitled, “DETERMINATION OF ELECTRODE OR LEAD POSITIONS,” the entire contents of which is incorporated herein by reference. TECHNICAL FIELD

[0002] This disclosure generally relates to electrical stimulation therapy, and in particular, determining relative positions of electrodes, leads, and / or anatomical features. BACKGROUND

[0003] 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.

[0004] 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

[0005] In general, systems, devices, and techniques are described for determining relative or absolute positions for leads and electrodes for delivering electrical stimulation and / or sensing physiological signals from a patient. Relative and absolute positions for lead and / orDocket No.: A0010253WO01 / 1123-791WO01 electrodes may be useful for a clinician or other user, particularly for selecting one or more stimulation parameters (e.g., electrode combination) for electrical stimulation. SCS systems may stimulate a spinal cord of a patient to mitigate or completely eliminate pain experienced by the patient. It may be beneficial to identify positions of leads relative to other leads or an absolute positions of leads in relation to anatomical features in order to configure delivery of electrical stimulation to with parameters that can account for the relative positions of the electrodes. In some examples, this electrical stimulation can be configured to mitigate or completely eliminate the pain experienced by the patient.

[0006] In some examples, a system may determine relative and / or absolute lead positions based on cross-impedance values for stimulation and sensing electrode pairs. Additionally, in some examples, the system may determine relative and / or absolute lead positions based on bioelectrical signals. Bioelectric signals may, in some cases, include local field potentials (LFPs), evoked compound action potentials (ECAPs), and electrocardiogram (ECG) signals. The system may apply cross-impedance values and / or bioelectric signal values to a model defining a relationship between the values and one or more distances between electrodes, leads, and / or anatomical features. The system may output information (e.g., via a display or user interface) indicative of and / or based on a distance between one or more electrodes carried by one or more leads or between electrodes, relative positions of leads to each other, and / or distances or orientations of the electrodes or leads to one or more anatomical features. This information may enable a clinician to implant the medical lead and / or choose one or more stimulation parameter values (e.g., electrode combinations, amplitudes, etc.) more effectively as compared with systems that do not output information indicating relative and / or absolute positions of leads.

[0007] In one example, a system includes processing circuitry configured to determine a plurality of impedance values for a plurality of electrodes implanted within a patient; apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and output information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0008] In another example, a method includes determining, by processing circuitry, a plurality of impedance values for a plurality of electrodes implanted within a patient; applying, by the processing circuitry, the plurality of impedance values to a model, the modelDocket No.: A0010253WO01 / 1123-791WO01 defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determining, by the processing circuitry and based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and outputting, by the processing circuitry, information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0009] In another example, a computer-readable medium comprising instructions that, when executed, control processing circuitry to determine a plurality of impedance values for a plurality of electrodes implanted within a patient; apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and output information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0010] 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

[0011] FIG.1 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.

[0012] FIG.2 is a block diagram illustrating an example configuration of components of the IMD of FIG.1.

[0013] FIG.3 is a block diagram illustrating an example configuration of components of an example external programmer.

[0014] FIG.4 is a graph of example evoked compound action potentials (ECAPs) sensed for respective stimulation pulses.

[0015] FIG.5 illustrates leads of an implantable medical device (IMD) implanted adjacent to a spinal cord, in accordance with one or more techniques of this disclosure.Docket No.: A0010253WO01 / 1123-791WO01

[0016] FIG.6 illustrates leads of an implantable medical device (IMD) that are offset relative to each other.

[0017] FIG.7 illustrates diverging leads of an implantable medical device (IMD).

[0018] FIG.8 illustrates converging leads of an implantable medical device (IMD).

[0019] FIG.9 illustrates diverging leads of an implantable medical device (IMD).

[0020] FIG.10 illustrates crossed leads of an implantable medical device (IMD).

[0021] FIG.11 is an example user interface configured to present information related to electrode or lead positions.

[0022] FIG.12 is a flow diagram illustrating an example technique for determining relative lead or electrode positions.

[0023] FIG.13 is a block diagram illustrating an example system that includes an external device, such as a server, and one or more computing devices that are coupled to an implantable medical device and external programmer shown in FIG.1 via a network. DETAILED DESCRIPTION

[0024] This disclosure describes examples of medical devices, systems, and techniques for determining relative and absolute positions of leads and electrodes used in electrical stimulation therapy. 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. Even though a clinician can attempt to implant leads, or electrodes carried thereon, to desired positions within a patient, the final implant position can deviate from the desired position. This deviation can occur from the flexible leads being pushed to different paths in tissue, movement of the patient, or other inaccuracies inherent in lead implantation. Further, leads may migrate (e.g., move) from an initial implant location. With implantation in certain anatomical locations, such as the epidural space adjacent the spinal cord, the distal ends of leads that carry the electrodes are typically not fixed to tissue. Therefore, electrode selection and other stimulation parameter selection may require a trial- and-error approach without precise information on the position of electrodes to each other and / or anatomical structures.

[0025] As described herein, the devices, systems, and techniques of this disclosure enable determination of relative and / or absolute positions of medical leads and / or electrodes to otherDocket No.: A0010253WO01 / 1123-791WO01 leads, electrodes, and / or anatomical features of a patient. For example, the system may determine impedance values for the implanted electrodes (e.g., impedances between different pairs or sets of electrodes) and apply these impedances to a model that defines the relationship between impedances and distances between electrodes. The system can then determine the actual distances between electrodes, orientations of one lead to another, orientations of electrodes to other electrodes, curving of leads, or any combination thereof. Additionally, the techniques of this disclosure enable ongoing determination of relative and / or absolute positions of leads and / or electrodes in order to provide real-time feedback. These relative and / or absolute positions may enable selection or adjustment of stimulation parameters (e.g., electrode combination) and / or monitoring of one or more patient conditions over time (e.g., posture or disease state).

[0026] Relative positions may refer to positions of electrodes and / or leads in relation to each other. As described herein, absolute positions may refer to positions of electrodes and / or leads in relation to the body of a patient, or more particularly, certain anatomical features of a patient. Relative and absolute positions of leads and electrodes may be determined and used to select, adjust, and / or recommend parameters of the stimulation therapy.

[0027] In some examples, effective stimulation therapy requires selection, and possibly adjustment, of stimulation parameters. Identifying therapeutically effective stimulation parameters (including electrode combination) may be difficult and time consuming, particularly without knowing the position of electrodes to each other, such as along a curved lead or between different leads. A system or clinician may select or adjust stimulation parameter values based on relative or absolute positions of electrodes and leads. In some instances, techniques for determining relative and / or absolute lead and electrode positions relying on minimum of excitation do not provide sufficient accuracy needed for selection of effective stimulation parameters. Additionally, in some cases, medical imaging techniques provide data as to the relative and absolute positions of electrodes and leads, but selectively provide positions of leads and / or electrodes at a given point or period of time (e.g., during an / or shortly after implantation). Where stimulation parameters are initially selected, patients may thus need to return to the clinic in order to update the thresholds and / or parameter values defining stimulation therapy. These issues may increase the time and resources needed achieve therapy efficacy possible with the therapy system or reduce the likelihood that the patient receives efficacious therapy.

[0028] 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)Docket No.: A0010253WO01 / 1123-791WO01 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.

[0029] As shown in the example of FIG.1, system 100 includes an IMD 110, lead 130A, lead 130B, one or more electrodes 132, one or more electrodes 134, 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 132 (collectively referred to as electrodes 132) and / or one or more electrodes 134 (collectively referred to as electrodes 134) of lead 130A and / or lead 130B (collectively, “leads 130”), e.g., for relief of chronic pain or other symptoms. In some examples, electrodes 132 are carried by or disposed on lead 130A and electrodes 134 are carried by or disposed on lead 130B. In other examples, IMD 110 may be coupled to a single lead carrying multiple electrodes or more than two leads each carrying multiple electrodes. IMD 110 may be a chronic electrical stimulator that remains implanted within patient 105 for weeks, months, years, or longer. 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 to percutaneously implanted leads. In some examples, IMD 110 uses one or more leads, while in other examples, IMD 110 is leadless.

[0030] 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 circuitry and a rechargeable or non-rechargeable power source. In addition, in some examples, the outer housing of IMD 110Docket No.: A0010253WO01 / 1123-791WO01 is selected from a material that facilitates receiving energy to charge the rechargeable power source.

[0031] 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 132 and / or one or more electrodes 134 of implantable leads 130. In the example of FIG.1, leads 130 carry electrodes 132 and electrodes 134 that are placed adjacent to the target tissue of spinal cord 120. In examples of this disclosure, leads 130 may be placed in the epidural space of the spine of patient 105, such as near one or more of a dorsal root ganglion (DRG), dorsal roots / rootlets, dorsal root entry zone, and / or ventral roots / rootlets in order to sense LFPs and / or ECAPs. In general, leads 130 may be positioned in a lateral placement from the midline. One or more of the electrodes 132 and / or electrodes 134 may be disposed at a distal portion 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. Electrodes 132 and / or electrodes 134 may transfer electrical stimulation generated by an electrical stimulation generator in 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 addition, 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.

[0032] The epidural space of patient 105 may represent a space between a posterior portion of a vertebra of the patient 105 and the spinal cord 120 of the patient. The epidural space may include fat. The epidural space may extend along at least a portion of the spinal cord 120 of the patient 105 such that leads 130 may be placed in the epidural space along the spinal cord 120. Since the epidural space is proximate to the spinal cord 120, leads placed within the epidural space may stimulate the spinal cord 120 and / or other nerve tissue proximate to the spinal cord 120. The epidural space of the patient may include a central region and one or more lateral regions. The central region of the epidural space may include a center point of a cross-section of the epidural space. The lateral regions of the epidural space may be laterally displaced from the center point of the cross-section of the epidural space. Typically, leads 130 are not fixed within the epidural space, so electrodes 132 and electrodes 134 may move relative to each other during implantation and potentially over time with patient movement.Docket No.: A0010253WO01 / 1123-791WO01

[0033] The spinal cord 120 may include a collection of neurons referred to herein as the “dorsal horn.” Dorsal horn neurons may carry signals along the spinal cord 120 to and from a brain of patient 105. Dorsal roots may enter the spinal cord 120 of the patient 105 at one or more locations along a length of the spinal cord 120. Dorsal roots may serve as a bridge between the dorsal horn and one or more peripheral nerves of the patient. In some examples, patient 105 may experience pain when the dorsal horn carries pain signals to the patient’s brain. In some cases, these pain signals may enter the dorsal horn via one or dorsal roots. In some examples, a lateral region of the epidural space may be proximate to a point at which a dorsal root enters the spinal cord 120 and connects with the dorsal horn. In some examples, one or more of leads 130 may be placed in a lateral region of the epidural space of the patient 105 so that one or more of leads 130 is proximate to one or more locations in which dorsal roots enter the spinal cord 120.

[0034] In some examples, spinal cord 120 may include one or more interneurons that relay signals between sensory neurons and motor neurons. A wind-up of one or more interneurons in the spinal cord 120 may cause patient 105 to experience pain. Wind-up may represent a phenomenon that represents a frequency-dependent response of a neuron evoked by electrical stimulation. Wind-up in one or more interneurons within spinal cord 120 may cause patient 105 to experience pain in addition to or alternatively to pain signals that enter the dorsal horn via the one or more dorsal roots. During acute pain, there may be C- and A- delta fibers transmitting pain signals from a periphery and through the lateral epidural space.

[0035] In some examples, one or more of leads 130 may be located in a central region of the epidural space (e.g., proximate to the longitudinal axis of the epidural space). The central region of the epidural space is proximate to the spinal cord 120, but a lateral region of the epidural space may be closer to a location in which a dorsal root connects with the spinal cord 120 than the central region of the epidural space. As described herein, determining the relative location of electrodes and / or leads to each other and / or anatomical locations may enable the system to target stimulation to particular portions of the spinal cord, particular nerve fibers, the dorsal horn, or any other desired anatomical structure.

[0036] While the example of FIG.1 depicts electrodes 132 and electrodes 134 as ring (circular) electrodes surrounding the body of leads 130, the electrodes of leads 130 may be electrode pads on a paddle 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 orDocket No.: A0010253WO01 / 1123-791WO01 multipolar electrode combinations for therapy. For purposes of illustration, electrodes 132 and electrodes 134 arranged at different axial positions at the distal ends of leads 130 are described herein.

[0037] The deployment of electrodes 132 and electrodes 134 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.

[0038] The stimulation parameter set of a therapy stimulation program that defines the stimulation pulses of electrical stimulation therapy delivered by IMD 110 through the electrodes 132 and electrodes 134 of leads 130 may include information identifying which electrodes have been selected for delivery of stimulation according to a stimulation program (e.g., the subset of electrodes selected for delivery of therapy), the polarities of the selected electrodes, i.e., the electrode combination for the program, voltage or current amplitude, pulse frequency, pulse width, pulse shape of stimulation delivered by the electrodes. These stimulation parameters values that make up the stimulation parameter set that defines pulses 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.

[0039] In some examples, IMD 110 may deliver stimulation pulses that contribute to therapy perceived by patient 105. IMD 110 may detect ECAP signals elicited by these stimulation pulses. In other examples, stimulation pulses configured to provide therapy may prevent IMD 110 from detecting ECAP signals (e.g., because the pulse width of the stimulation pulses are long enough to interfere with propagating ECAP signals). Therefore, if control pulses (e.g., pulses that may or may not contribute to therapy) separate from informed pulses configured to provide therapy are needed to elicit a detectable ECAP signal, system 100 may employ an ECAP test stimulation program that defines stimulation parameter valuesDocket No.: A0010253WO01 / 1123-791WO01 that define control pulses delivered by IMD 110 through at least some of electrodes 132 and / or electrodes 134 of leads 130.

[0040] These stimulation parameter values may include information identifying which electrodes (e.g., from electrodes 132 and electrodes 134) have been selected for delivery of control pulses, the polarities of the selected electrodes, i.e., the electrode combination for the program, and voltage or current amplitude, pulse frequency, pulse width, and pulse shape of stimulation delivered by the electrodes. The stimulation signals (e.g., one or more stimulation pulses or a continuous stimulation waveform) defined by the parameters of each ECAP test stimulation program are configured to evoke a compound action potential from nerves. In some examples, the ECAP test stimulation program defines when the control pulses are to be delivered to the patient based on the frequency and / or pulse width of the informed pulses. The stimulation defined by each ECAP test stimulation program may not be intended to provide or contribute to therapy for the patient, but the patient may perceive the control pulses in some examples. In addition, the ECAP test stimulation program may define the control pulses used for each sweep of pulses that are used to detect a change in an ECAP signal. As described below, ECAP signals and changes in ECAP signals may be used to determine relative and absolute locations of electrodes and / or leads.

[0041] Although FIG.1 is directed to SCS therapy, e.g., therapy 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. Additionally, system 100 may be configured to provide therapy for stroke recovery, spinal cord injury (SCI), and / or autonomic control (e.g., blood pressure, sugar levels, etc.). Further, system 100 may be configured for different lead placements (e.g., lateral or midline placements).

[0042] In some examples, lead 130 includes one or more sensors, wherein IMD 110 is configured to monitor one or more parameters of patient 105 via the one or more sensors. The one or more patient parameters may include one or more of patient activity, position,Docket No.: A0010253WO01 / 1123-791WO01 pressure, temperature, or other characteristics. The one or more sensors may be provided in addition to, or in place of, electrodes 132 and / or electrodes of leads 130. In some examples, one or more of electrodes 132 and / or electrodes 134 are configured for sensing. In some examples, IMD 110 is configured to detect and record ECAP signals via electrodes 132 and electrodes 134.

[0043] IMD 110 is configured to deliver electrical stimulation therapy to patient 105 via selected combinations of electrodes (e.g., from electrodes 132 and electrodes 134) 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 some examples, the target tissue is peripheral tissue. 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 adjacent to 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 causes a tingling sensation that may reduce the perception of pain by patient 105, and thus, provide efficacious therapy results. In some examples, stimulation of spinal cord 120 may be configured to reduce or eliminate pain without paresthesia. IMD 110 may, in some examples, stimulate target tissue in order to decrease acute pain.

[0044] IMD 110 is configured to generate and deliver electrical stimulation therapy to a target stimulation site within patient 105 via electrodes 132 and electrodes 134 of leads 130 to patient 105 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 according to that program. 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, pulse shape, etc. for stimulation pulses delivered by IMD 110 according to that program. As described herein, IMD 110 may leverage distances orDocket No.: A0010253WO01 / 1123-791WO01 orientations determined for the electrodes for the purpose of determining values of one or more stimulation parameters that define stimulation.

[0045] Furthermore, IMD 110 may be configured to deliver control stimulation to patient 105 via a combination of electrodes (e.g., a subset) carried by 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 (e.g., control pulses and / or informed pulses). 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. Since control stimulation pulses can be delivered in an interleaved manner with informed pulses (e.g., when the pulses configured to contribute to therapy interfere with the detection of ECAP signals or pulse sweeps intended to detect migration of leads 130 via ECAP signals do not correspond to pulses intended for therapy purposes), a clinician and / or user may select any desired electrode combination for informed pulses. Like the electrical stimulation therapy, the control stimulation may be in the form of electrical stimulation pulses or continuous waveforms. In one example, each control stimulation pulse may include a balanced, bi-phasic square pulse that employs an active recharge phase. However, in other examples, the control stimulation pulses may include a monophasic pulse followed by a passive recharge phase. In other examples, a control pulse may include an imbalanced bi-phasic portion and a passive recharge portion. Although not necessary, a bi-phasic control pulse may include an interphase interval between the positive and negative phase to promote propagation of the nerve impulse in response to the first phase of the bi-phasic pulse. The control stimulation may be delivered without interrupting the delivery of the electrical stimulation informed pulses, such as during the window between consecutive informed pulses. The control pulses may elicit an ECAP signal from the tissue, and IMD 110 may sense the ECAP signal via two or more electrodes on leads 130. In cases where the control stimulation pulses are applied to spinal cord 120, the signal may be sensed by IMD 110 from spinal cord 120.

[0046] IMD 110 can deliver control stimulation to a target stimulation site within patient 105 via electrodes 132 and electrodes 134 of leads 130 according to one or more ECAP test stimulation programs. The one or more ECAP test stimulation programs may be stored in a storage device of IMD 110. Each ECAP test program of the one or more ECAP test stimulation programs includes values for one or more parameters that define an aspect of the control stimulation delivered by IMD 110 according to that program, such as current orDocket No.: A0010253WO01 / 1123-791WO01 voltage amplitude, pulse width, pulse frequency, electrode combination, and, in some examples timing based on informed pulses to be delivered to patient 105.

[0047] 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 (e.g., informed pulses) and / or control stimulation (e.g., control pulses). For example, external programmer 150 may transmit therapy stimulation programs, ECAP test stimulation programs, stimulation parameter adjustments, therapy stimulation program selections, ECAP test program selections, user input, or other information to control the operation of IMD 110, e.g., by wireless telemetry or wired connection. Programmer 150 may provide relative distances between electrodes or to anatomical structures, for example, in order to enable the clinician to select appropriate stimulation parameter values.

[0048] In some cases, external programmer 150 may be characterized as a physician or 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 may accompany 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, or when a patient perceives stimulation being delivered. 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.

[0049] In some examples, external programmer 150 may receive sensed signals or representative information and perform the same techniques and functions attributed to IMD 110 herein. In other examples, a remote server (e.g., a standalone server or part of a cloud service as shown in FIG.13) may perform the functions attributed to IMD 110, external programmer 150, or any other devices described herein.Docket No.: A0010253WO01 / 1123-791WO01

[0050] As described herein, information may be transmitted between external programmer 150 and IMD 110. Therefore, 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 IMD 110 implant site to improve the quality 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.

[0051] 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 informed 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 informed pulses may be automatically updated.

[0052] While the ECAPs-related techniques described above may be used for sensing the effects of electrical stimulation therapy and updating parameters, this disclosure further describes techniques for using measured signals, including bioelectric signals (e.g., ECAPs, ECGs, etc.), to determine relative orientations of electrodes to each other and / or to another lead and / or one or more anatomical structures. For example, the techniques described herein may be used to determine a relative orientation of leads. Relative orientations for leads may indicate how the leads are positioned to each other, such as orientations including parallel or substantially parallel, converging (e.g., where respective distal portion of leads are spaced apart closer than respective proximal portions of leads), or diverging (e.g., where respective distal portion of leads are spaced apart further than respective proximal portions of leads). In some examples, the techniques of this disclosure may be used to determine relative twist or curving of the one or more leads. Twist may include an increase of divergence or convergence over the length of respective leads. These lead orientations may be determined from the relative position information between electrodes on the one or more leads and / or with respect to one or more anatomical structures.Docket No.: A0010253WO01 / 1123-791WO01

[0053] One or more techniques described herein may include a system for informing a clinician or other user as to the proximity and orientation of one or more electrodes or one or more leads to other electrodes, to other leads, or to particular anatomical features. The feedback regarding proximity or orientation may be used to select or adjust one or more parameters for sensing and / or stimulation. In some examples, the system may automatically select electrode combinations and / or other stimulation parameter values (e.g., amplitudes, pulse shape, etc.) based on the relative electrode positions and target stimulation locations.

[0054] The techniques described herein may provide clinicians with ways to select stimulation parameters for delivering effective stimulation therapy throughout the lifetime of the implanted system. As lead orientations may change over time (e.g., between one or more time points) due to lead migration, injury, or change in a patient position (e.g., supine, prone, sitting, standing, etc.), the relative positions of leads and electrodes with respect to each other and other anatomical features may provide feedback for selecting or adjusting one or more parameters for sensing and / or stimulation. In some examples, the feedback of relative lead and / or electrode positions may be provided to a user for manually select or update one or more parameters for sensing and / or stimulation. However, the feedback may be used for automatic selection or adjustment of one or more parameters for sensing and / or stimulation.

[0055] FIG.2 is a block diagram of IMD 200, in accordance with one or more techniques of this disclosure. IMD 200 may be an example of IMD 110 of FIG.1. In the example shown in FIG.2, IMD 200 includes processing circuitry 214, memory 215, stimulation generation circuitry 211, sensing circuitry 212, telemetry circuitry 213, sensor 216, and power source 219. Each of these circuits may be or include programmable or fixed function circuitry configured to perform the functions attributed to respective circuitry. For example, processing circuitry 214 may include fixed-function or programmable circuitry, stimulation generation circuitry 211 may include circuitry configured to generate stimulation signals such as pulses or continuous waveforms on one or more channels, sensing circuitry 212 may include sensing circuitry for sensing signals, and telemetry circuitry 213 may include telemetry circuitry for transmission and reception of signals. Memory 215 may store computer-readable instructions that, when executed by processing circuitry 214, cause IMD 200 to perform various functions. Memory 215 may be a storage device or other non- transitory medium.

[0056] In the example shown in FIG.2, memory 215 stores therapy stimulation programs 217 and ECAP test stimulation programs 218 in separate memories within memory 215 or separate areas within memory 215. Memory 215 also stores bioelectric signal analysis unitDocket No.: A0010253WO01 / 1123-791WO01 221 and electrode proximity unit 222. Each stored therapy stimulation program 217 defines values for a set of electrical stimulation parameters (e.g., a parameter set or set of parameter values), such as a stimulation electrode combination, electrode polarity, current or voltage amplitude, pulse width, pulse rate, and pulse shape. Each stored ECAP test stimulation programs 218 defines values for a set of electrical stimulation parameters (e.g., a control stimulation parameter set), such as a stimulation electrode combination, electrode polarity, current or voltage amplitude, pulse width, pulse rate, and pulse shape. ECAP test stimulation programs 218 may also have additional information such as instructions regarding when to deliver control pulses based on the pulse width and / or frequency of the informed pulses defined in therapy stimulation programs 217.

[0057] Accordingly, in some examples, stimulation generation circuitry 211 generates electrical stimulation signals in accordance with the electrical stimulation parameters noted above. Other ranges of parameter values may also be useful and may depend on the target stimulation site within patient 105. While stimulation pulses are described, stimulation signals may be of any form, such as continuous-time signals (e.g., sine waves) or the like.

[0058] Processing circuitry 214 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 214 herein may be embodied as firmware, hardware, software or any combination thereof. Processing circuitry 214 controls stimulation generation circuitry 211 to generate stimulation signals according to therapy stimulation programs 217 and ECAP test stimulation programs 218 stored in memory 215 to apply 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.

[0059] In the example shown in FIG.2, the set of electrodes 232 includes electrode 232A, electrode 232B, electrode 232C, and electrode 232D, and the set of electrodes 234 includes electrode 234A, electrode 234B, electrode 234C, and electrode 234D. Electrodes 232 and electrodes 234 may be disposed on a first lead 230A and / or a second lead 230B (collectively leads 230). Electrodes 232 may be disposed on a first lead 230A. Electrodes 234 may be disposed on a second lead 230B. In other examples, a single lead may include all eight electrodes of electrodes 232 and electrodes 234 along a single axial length of the lead. Lead 230A, lead 230B, electrodes 232 and electrodes 234 may be examples of lead 130A, lead 130B, electrodes 132 and electrodes 134 of FIG.1.Docket No.: A0010253WO01 / 1123-791WO01

[0060] In some examples, processing circuitry 214 also controls stimulation generation circuitry 211 to generate and apply the stimulation signals to selected combinations of electrodes of electrodes 232 and / or electrodes 234 (e.g., for therapy, or for ECAP recording). In some examples, stimulation generation circuitry 211 includes a switch circuit that may couple stimulation signals to selected conductors within leads 230, which, in turn, deliver the stimulation signals across selected of electrodes 232 and / or electrodes 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 of electrodes 232 and / or electrodes 234 and to selectively sense bioelectrical neural signals of a spinal cord of the patient (not shown in FIG.2) with selected electrodes of electrodes 232 and / or electrodes 234.

[0061] In other examples, however, stimulation generation circuitry 211 does not include a switch circuit. In these examples, stimulation generation circuitry 211 comprises a plurality of pairs of voltage sources, current sources, voltage sinks, or current sinks connected to each of electrodes 232 and electrodes 234 such that each pair of electrodes has a unique signal circuit. In other words, in these examples, each of electrodes 232 and electrodes 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.

[0062] Electrodes 232 and electrodes 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. In one example, the electrodes may be electrically coupled to stimulation generation circuitry 211, 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.

[0063] Although sensing circuitry 212 is incorporated into a common housing with stimulation generation circuitry 211 and processing circuitry 214 in FIG.2, in other examples, sensing circuitry 212 may be in a separate housing from IMD 200 and may communicate with processing circuitry 214 via wired or wireless communication techniques.Docket No.: A0010253WO01 / 1123-791WO01

[0064] In some examples, one or more of electrodes 232 and electrodes 234 may be configured for sensing the ECAPs. For instance, electrodes 232 and electrodes 234 may sense the voltage amplitude of a portion of the ECAP signals, where the sensed voltage amplitude is a characteristic the ECAP signal.

[0065] Sensor 216 may include one or more sensing elements that sense values of a respective patient parameter. As described previously, electrodes 232 and electrodes 234 may be the electrodes that sense the parameter value of the ECAP. Sensor 216 may include one or more accelerometers, optical sensors, chemical sensors, temperature sensors, pressure sensors, or any other types of sensors. Sensor 216 may output patient parameter values that may be used as feedback to control delivery of therapy. For example, sensor 216 may indicate patient activity, and processing circuitry 214 may increase the frequency of control pulses and ECAP sensing in response to detecting increased patient activity. In one example, processing circuitry 214 may initiate control pulses and corresponding ECAP sensing in response to a signal from sensor 216 indicating that patient activity has exceeded an activity threshold. Conversely, processing circuitry 214 may decrease the frequency of control pulses and ECAP sensing in response to detecting decreased patient activity. For example, in response to sensor 216 no longer indicating that the sensed patient activity exceeds a threshold, processing circuitry 214 may suspend or stop delivery of control pulses and ECAP sensing. In this manner, processing circuitry 214 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 increase 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 213, 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 the patient). In some examples, signals from sensor 216 may indicate a position or body state (e.g., sleeping, awake, sitting, standing, or the like), and processing circuitry 214 may select target ECAP characteristic values according to the indicated position or body state.

[0066] In some examples, telemetry circuitry 213 is configured to provide wireless communication between IMD 200 and an external programmer (not shown in FIG.2) or another computing device under the control of processing circuitry 214. Processing circuitry 214 of IMD 200 may receive, as updates to programs, values for various stimulationDocket No.: A0010253WO01 / 1123-791WO01 parameters such as amplitude and electrode combination, from the external programmer via telemetry circuitry 213. Updates to the therapy stimulation programs 217 and ECAP test stimulation programs 218 may be stored within memory 215. Telemetry circuitry 213 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 213 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 213 may send information to the external programmer on a continuous basis, at periodic intervals, or upon request from IMD 110 or the external programmer.

[0067] In some examples, power source 219 delivers operating power to various components of IMD 200. Power source 219 may include a rechargeable or non-rechargeable battery and a power generation circuit to produce the operating power. Recharging may be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within IMD 200. In other examples, traditional primary cell batteries may be used.

[0068] In some examples, stimulation generation circuitry 211 of IMD 200 receives, via telemetry circuitry 213, instructions to deliver electrical stimulation therapy according to therapy stimulation programs 217 to a target tissue site of the spinal cord of the patient via a plurality of electrode combinations of electrodes 232 and / or electrodes 234 of leads 230 and / or a housing of IMD 200. Stimulation generation circuitry 211 may receive, via telemetry circuitry 213, user instructions to deliver control stimulation to the patient according to ECAP test stimulation programs 218. Each pulse of a plurality of control pulses may elicit an ECAP that is sensed by sensing circuitry 212 via some of electrodes 232 and 234. ECAP test stimulation programs 218 may instruct stimulation generation circuitry 211 to deliver a plurality of control pulses interleaved with at least some of the plurality of informed pulses. Processing circuitry 214 may receive, via an electrical signal sensed by sensing circuitry 212, information indicative of an ECAP signal (e.g., a numerical value indicating a characteristic of the ECAP in electrical units such as voltage or power) produced in response to the control stimulation. Therapy stimulation programs 217 may be updated according to the ECAPs recorded at sensing circuitry 212 according to the following techniques.

[0069] In one example, the plurality of informed pulses each have a pulse width of greater than approximately 100 microseconds and less than approximately 2000Docket No.: A0010253WO01 / 1123-791WO01 microseconds (i.e., 2 milliseconds). In some examples, the informed pulse width is greater than approximately 200 microseconds and less than approximately 800 microseconds. In another example, the informed pulse width is greater than approximately 300 microseconds and less than approximately 500 microseconds. In one example, informed pulses have a pulse width of approximately 450 microseconds and a pulse frequency of approximately 60 Hertz. Amplitude (current and / or voltage) for the informed pulses may be between approximately 0.5 mA (or volts) and approximately 10 mA (or volts), although amplitude may be lower or greater in other examples. In some examples, the system may deliver informed pulses from two or more stimulation programs such that the informed pulses from one stimulation program have at least one different parameter value than the informed pulses from another stimulation program.

[0070] Each control pulse of the plurality of control pulses may have a pulse width of less than approximately 300 microseconds. In one example, each control pulse of the plurality of control pulses may be a bi-phasic pulse with a positive phase having a width of approximately 100 microseconds, a negative phase having a width of approximately 100 microseconds, and an interphase interval having a width of approximately 30 microseconds. In some examples, the positive phase and negative phase may each be 90 microseconds or 120 microseconds in other examples. In other examples, the control pulses may each have a pulse width of approximately 60 microseconds or smaller. Due to the relatively long pulse widths of the plurality of informed pulses, sensing circuitry 212 may be incapable of adequately recording an ECAP signals elicited from an informed pulse because the informed pulse itself will occur during the ECAP signal and obscure the ECAP signal. However, stimulation pulses with pulse widths less than approximately 300 microseconds, such as the plurality of control pulses, may be suited to elicit an ECAP which can be sensed after the control pulse is completed at sensing circuitry 212 via two or more of electrodes 232 and 234. In some examples, the control pulses may be non-therapeutic pulses in that the control pulses do not contribute to therapy for the patient. In other examples, the control pulses may fully provide or partially contribute to the therapy received by the patient by reducing or eliminating symptoms and / or a condition of the patient.

[0071] Control pulses delivered for the purpose of eliciting detectable ECAP signals may have a current amplitude between approximately 3 mA and 12 mA in some examples, but higher or lower amplitudes may be used in other examples. The frequency of the control pulses may be between approximately 10 Hertz and 400 Hertz in some examples, which may match the predetermined pulse frequency of the informed pulses when one control pulse isDocket No.: A0010253WO01 / 1123-791WO01 delivered for each therapeutic pulse. The predetermined pulse frequency may be a single frequency or a varied frequency over time (e.g., the interpulse interval may change over time according to predetermined pattern, formula, or schedule). In some examples, the system may change the predetermined pulse frequency based on patient input or a sensed parameter such as patient posture or activity. Such a relationship may be present when the control pulses are fully interleaved (e.g., alternating) with the informed pulses. However, the frequency of the control pulses may be delivered at a higher frequency than then informed pulses when two or more control pulses are delivered between consecutive informed pulses. In other examples, the frequency of the control pulses may be delivered at a lower frequency than the informed pulses when at least some informed pulses are delivered without a control pulse delivered between them. The frequency of the control pulses may be delivered at a frequency that varies over time if the system is configured to adjust control pulse delivery, and the resulting ECAP sensing, based on other factors such as patient activity.

[0072] In one example, the predetermined pulse frequency of the plurality of informed pulses may be less than approximately 400 Hertz. In some examples, the predetermined pulse frequency of the plurality of informed pulses may be between approximately 50 Hertz and 70 Hertz. In one example, the predetermined pulse frequency of the plurality of informed pulses may be approximately 60 Hertz. However, the informed pulses may have frequencies greater than 400 Hertz or less than 50 Hertz in other examples. In some examples, the predetermined pulse frequency of the informed pulses may be a single frequency or a frequency that varies over time. In addition, the informed pulses may be delivered in bursts of pulses, with interburst frequencies of the pulses being low enough such that a control pulse and sensed ECAP can still fit within the window between consecutive informed pulses delivered within the burst of informed pulses.

[0073] Since each informed pulse of the plurality of informed pulses may be sensed as an artifact that covers, or obscures, the sensing of at least one ECAP, the plurality of control pulses may be delivered to the patient during a plurality of time events. For example, a time event (e.g., a window) of the plurality of time events may be a time (e.g., a window) between consecutive informed pulses of the plurality of informed pulses at the predetermined pulse frequency. One or more control pulses of the plurality of control pulses may be delivered to the patient during each time event. Consequently, the control pulses may be interleaved with at least some of the informed pulses such that the plurality of control pulses are delivered to the patient while informed pulses are not delivered. In one example, an ECAP elicited from to a control pulse delivered during a time event may be recorded by sensing circuitry 212Docket No.: A0010253WO01 / 1123-791WO01 during the same time event. In another example, two or more ECAPs responsive to two or more respective control pulses delivered during a time event may be recorded by sensing circuitry 212 during the same time event.

[0074] In some examples, therapy stimulation programs 217 may be updated according to a plurality of ECAPs received in response to the plurality of control pulses delivered to the patient according to ECAP test stimulation programs 218. For instance, processing circuitry 214 may update therapy stimulation programs 217 in real time by comparing one or more characteristics of ECAPs sensed by sensing circuitry 212 with target ECAP characteristics stored in memory 215. For example, processing circuitry 214 is configured to determine the amplitude of each ECAP signal received at sensing circuitry 212, and processing circuitry 214 is further configured to determine the representative amplitude of at least one respective ECAP signal and compare the representative amplitude of a series of ECAP signals to a target ECAP adjustment window. Target ECAP adjustment window may thus be a range of amplitudes deviating from target ECAP amplitude. For instance, the target ECAP adjustment window may span from a lower-bound amplitude value (e.g., the target ECAP amplitude minus the variance) to an upper-bound amplitude value (e.g., the target ECAP amplitude plus the variance). Generally, the lower-bound amplitude value is less than the target ECAP amplitude, and the upper-bound amplitude value is greater than target ECAP amplitude.

[0075] If the representative amplitude of the at least one respective ECAP signal (e.g., an amplitude of a single ECAP signal or an average of two or more ECAP amplitudes) is greater than the upper-bound amplitude value, processing circuitry 214 may adjust one or more of therapy stimulation programs 217 and ECAP test stimulation programs 218 to decrease the amplitude of informed pulses and control pulses following the at least one respective ECAP. The amplitude of informed pulses and control pulses may be decreased by different predetermined steps or different predetermined percentages. Additionally, if the representative amplitude of the at least one respective ECAP is less than the lower-bound amplitude value, processing circuitry 214 may adjust therapy stimulation programs 217 and ECAP test stimulation programs 218, and the programs 217 and 218 may instruct stimulation generation circuitry 211 to increase the amplitude of informed pulses and control pulses following the at least one respective ECAP. Moreover, if the representative amplitude of the at least one respective ECAP is greater than the lower-bound amplitude value and less than the upper-bound amplitude value, processing circuitry 214 may not change programs 217 and 218, and stimulation generation circuitry 211 may maintain the amplitude of the informed pulses following the at least one respective ECAP. In one example, adjusting the programsDocket No.: A0010253WO01 / 1123-791WO01 217 and 218 may include changing one or more parameters of the plurality of informed pulses and the plurality of control pulses. In one example, the at least one respective ECAP may include a series of four consecutive ECAPs. As described herein, ECAP signals may be employed as part of the technique to determine relative distances and / or orientations between electrodes and / or as feedback for adjusting stimulation therapy.

[0076] In some examples, leads 230 may be linear 8-electrode leads (not pictured); sensing and stimulation delivery may each be performed using a different set of electrodes. In a linear 8-electrode lead, each electrode may be numbered consecutively from 0 through 7. For instance, a control pulse may be generated using electrode 1 as a cathode and electrodes 0 and 2 as anodes (e.g., a guarded cathode), and a respective ECAP signal may be sensed using electrodes 6 and 7, which are located on the opposite end of the electrode array. This strategy may minimize the interference of the stimulation pulse with the sensing of the respective ECAP. Other electrode combinations may be implemented, and the electrode combinations may be changed using the patient programmer via telemetry circuitry 213. For example, stimulation electrodes and sensing electrodes may be positioned closer together. Shorter pulse widths for the control pulses may allow the sensing electrodes to be closer to the stimulation electrodes.

[0077] In some examples, processing circuitry 214 is configured to determine a plurality of impedance values for electrodes 232 and electrodes 234 implanted within a patient. For example, processing circuitry 214 may be configured to determine a cross-impedance value between pairs (or sets of more than 2) of stimulating electrodes and / or respective pairs (or sets of more than 2) of recording electrodes. Processing circuitry 214, alone or in combination with stimulation generation circuitry 211, may be configured to provide, via one or more pairs of electrodes, which may be referred to as a stimulation pair of electrodes, (e.g., a first subset of electrodes 232 and / or 234), a pre-defined current for determination of cross- impedance values. Additionally, processing circuitry 214 may be configured to record (or sense), via one or more pairs of electrodes, which may be referred to as a recording or sensing pair of electrodes (e.g., a second subset of electrodes 232 and / or 234), the resulting voltage from pre-defined current for determination of cross-impedance values. The resulting voltage may be recorded over a period of time (e.g., a sense window), which may be less than 3.5 milliseconds in some examples, but shorter or longer periods of time may be used in other examples. In some examples, the sense window may include a period of time for each recording pair of electrodes to record a resulting voltage from a given pulse of pre-defined current provided by the stimulation pair of electrodes.Docket No.: A0010253WO01 / 1123-791WO01

[0078] Processing circuitry 214 may determine the cross-impedance across all pairs of electrodes of electrodes 232 and electrodes 234 based on the pre-defined current provided by the first subset of electrodes and the resulting voltage recorded across the second pair of electrodes. As an illustrative example, a stimulating pair of electrodes (e.g., which may be a first subset of electrodes from electrodes 232A and / or electrodes 232B) may provide a pre- defined current, and the resulting voltage may be measured across a recording pair of electrodes (e.g., which may be a second subset of electrodes from electrode 234A and / or electrode 234B). In some examples, the cross-impedance across the stimulating pair of electrodes and the recording pair of electrodes is the resulting voltage as recorded by the recording pair divided by the pre-defined current provided by the stimulating pair. In some examples, the stimulation pairs of electrodes and the recording pairs of electrodes are carried by different leads (e.g., a stimulation pair of electrodes is carried by lead 230A and a recording pair of electrodes is carried by lead 230B). In some examples, the stimulation pairs of electrodes and the recording pairs of electrodes are carried by the same lead (e.g., a stimulation pair of electrodes and a recording pair of electrodes are carried by lead 230A). In some examples, one or more of the stimulation electrodes or recording electrodes are carried by a housing of a medical device (e.g., the housing of IMD 110).

[0079] In some examples, processing circuitry 214 may update the pre-defined current provided via the stimulating pair of electrodes (e.g., the first subset of electrodes from electrodes 232A and / or electrodes 232B) at least in part based on the resulting voltage of one or more recording pairs of electrodes (e.g., the second subset of electrodes from electrode 234A and / or electrode 234B). For example, where the resulting voltage (e.g., a first resulting voltage) measured by one or more recording electrodes is below or above a pre-determined voltage threshold, processing circuitry 214 may adjust the pre-defined current to elicit a different voltage (e.g., a second resulting voltage) in the one or more recording pairs of electrodes. In some examples, processing circuitry 214 may be configured to change or update (e.g., automatically, without user input) the pre-defined current provided by the stimulating electrodes (e.g., from a first pre-defined current to a second pre-defined current). Processing circuitry 214 may be configured to update a first pre-defined current value to a second pre-defined current value, where the second pre-defined current value is different than the second pre-defined current value. In some examples, where a measured voltage across a recording pair of electrodes is below a predetermined minimum threshold, processing circuitry 214, with or without input from a user, may increase the pre-defined current to elicit a higher voltage recorded across the recording pair of electrodes. Similarly, in someDocket No.: A0010253WO01 / 1123-791WO01 examples, where a measured voltage across a recording pair of electrodes is above a predetermined maximum threshold, processing circuitry 214, with or without input from a user, may decrease the pre-defined current to elicit a lower voltage recorded across the recording pair of electrodes. In this way, the pre-defined current provided may be adaptive and / or dynamic based on measured voltages across the recording electrodes.

[0080] The determination of cross-impedance values may be repeated across all pairs or nearly all pairs of electrodes of electrodes 232 and electrodes 234 to determine a set (e.g., a matrix) of cross-impedance values for electrodes 232 and electrodes 234. In some examples, a characterization of field spread (e.g., field spread between lead 230A and lead 230B) is based on the determined cross-impedance values. While the determination of cross- impedance values may be repeated for all pairs of stimulation and recording electrodes of electrodes 232 and 234, a plurality of impedance values may be determined for a selected set of stimulation and recording pairs (e.g., less than all pairs of electrodes 232 and electrodes 234). For example, depending on a level of accuracy needed for determining the relative positions of leads 230 and / or electrodes 232 and electrodes 234, a plurality of impedance values may be determined for a subset (e.g., less than all) of electrodes 232 and / or electrodes 234. Further, cross-impedance values may be determined for one lead (e.g., lead 230A) or the electrodes of the one lead (e.g., electrodes 232 of lead 230), even in cases where more than one lead is use (e.g., where lead 230B is used). For example, where a position of a single lead (e.g., lead 230A) or the electrodes of the single lead (e.g., electrodes 232 of lead 230A) is determined with respect to an anatomical feature, the plurality of impedance values may be determined for electrodes 232 (e.g., an not determined for electrodes 234 of lead 230B).

[0081] Additionally, processing circuitry 214 may determine the plurality of impedance values using one or more stimulation pulses with different stimulation pulse widths. For example, stimulation generation circuitry 211 may be configured to generate, via one or more electrodes of electrodes 232 and / or electrodes 234, one or more stimulation pulses having a first pulse width. The resulting voltage may be recorded across one or more recording pairs of electrodes of electrodes 232 and / or electrodes 234 to determine a first set of cross-impedance values. Further, stimulation generation circuitry 211 may be configured to generate, via one or more electrodes of electrodes 232 and / or electrodes 234, one or more stimulation pulses having a second pulse width. The resulting voltage may be recorded across one or more recording pairs of electrodes of electrodes 232 and / or electrodes 234 to determine a second set of cross-impedance values. This may be repeated with any suitable number of pulses having any number of pulse widths (e.g., one, two, three, four, five, ten, twenty, fifty, etc.) toDocket No.: A0010253WO01 / 1123-791WO01 determine multiple sets of cross-impedance values. In some examples, stimulation generation circuitry 211 generates two or more stimulation pulses with the same pulse width. Depending on the number of pulse widths used, using multiple pulse width to determine multiple sets of cross-impedance values may enhance or confirm an estimate of one or more distances between two or more electrodes of electrodes 232 and / or electrodes 234.

[0082] In some examples, processing circuitry 214 is configured to apply the plurality of impedance values determined for electrodes 232 and 234 to a model (e.g., an analytical model or machine learning model), where the model defines a relationship between impedance values for and one or more distances between two or more electrodes of electrodes 232 and electrodes 234. For example, the model may include a model of field spread, e.g., between leads 230 and / or between electrodes of electrodes 232 and / or electrodes 234. The model may include a simulation to determine an estimated distance (e.g., displacement) between leads 230 and / or between two or more electrodes of electrodes 232 and electrodes 234 based on the different impedance values (from the respective electrodes or sets of electrodes) applied to the model. In some examples, the distance determined by the model may include one or more vertical or longitudinal (e.g., parallel to the median anatomical plane) distances between two or more electrodes of electrodes 232 and electrodes 234. In some examples, the distance determined by the model may include one or more horizontal or lateral (e.g., parallel to the horizontal or transverse anatomical plane) distances between two or more electrodes of electrodes 232 and electrodes 234. In some examples, the model is configured to determine twist of curve of lead 230A and / or lead 230B. In some examples, the model may additionally or alternatively define a relationship between the plurality of impedance values and a proximity (e.g., distance) of the one or more electrodes of electrodes 232 and / or electrodes 234 to the anatomical feature of the patient.

[0083] In some examples, processing circuitry 214 is configured to exclude from applying to the model one or more impedance values. Some impedance values may be invalid (or otherwise not representative of actual impedances) due to various measurement issues such as lead integrity issues or tissue encapsulation, and these invalid values may prevent accurate determination of the relative distances between electrodes. For example, processing circuitry 214 may be configured to exclude from applying to the model one or more impedance values above or below an impedance threshold. In some examples, processing circuitry 214 may be configured to determine one or more electrodes of electrodes 232 and / or electrodes 234 associated with one or more impedance values above a maximum impedance threshold and exclude, from applying to the model, the one or more impedance values aboveDocket No.: A0010253WO01 / 1123-791WO01 the maximum impedance threshold for any of these electrodes. As another example, processing circuitry 214 may be configured to determine one or more electrodes of electrodes 232 and / or electrodes 234 associated with one or more impedance values below a minimum impedance threshold and exclude, from applying to the model, the one or more impedance values below the minimum impedance threshold. In this manner, after excluding or removing these above or below threshold impedance values, processing circuitry 214 may apply the impedance values below (or above) the threshold to the model (e.g., and not apply the excluded impedance values to the model). By excluding certain impedance values from application to the model, the model may more accurately predict or estimate one or more relative positions of leads 230 and / or electrodes 232 and electrodes 234 to each other or an anatomical feature of patient 105.

[0084] In addition to determining an estimated distance between leads 230 and / or between two or more electrodes of electrodes 232 and electrodes 234, processing circuitry 214 may be configured to determine a relative orientation of two or more leads (e.g., an orientation of a first lead 230A with respect to a second lead 230B). An orientation of a first lead with respect to a second lead may include parallel or substantially parallel (to account for minor variations), disposed at an angle, crossed, or other relative orientations. When a first lead is disposed at an angle with respect a second lead, the leads may be converging (e.g., where respective distal portion of leads are spaced apart closer than respective portions of leads), or diverging (e.g., where respective distal portion of leads are spaced apart further than respective proximal portions of leads). In some examples, an orientation of a first lead with respect to a second lead may include multiple orientations. For example, an orientation of a first lead with respect to a second lead may include portions where the leads are converging, and other portions where the leads are diverging. In some examples, the relative orientation of two or more leads includes relative twist of the one or more leads. As described with respect to FIG.9, twist may include an increase of divergence or convergence over the length of respective leads (e.g., where one or more leads is curved in a direction away from or towards a second lead). A lead may include one, two, or more areas of curvature which may be in the same or different directions.

[0085] In some examples, the model (e.g., the model of field spread) is based on (e.g., generated from) experimental values of cross-impedance values and experimental distance values between leads. For example, to build the model, leads (e.g., leads 230) and / or electrodes on respective leads (e.g., electrodes 232 and electrodes 234) may be positioned at a fixed (e.g., predetermined) distance, and a human user or a machine program may recordDocket No.: A0010253WO01 / 1123-791WO01 resulting impedance values for stimulation pairs and sensing pairs of electrodes. Each stimulating pair of electrodes may generate a fixed (e.g., predetermined) current to determine the experimental values of cross-impedance values at the fixed distance. The experimental fixed distance values may be varied to further define the model. To determine the experimental values for the model, leads (e.g., leads 230) may be placed in saline, a living subject (e.g., an animal or a human subject), or another suitable location. In some examples, the experimental distance values between leads and / or electrodes is based on medical imaging data. Medical imaging data may be generated from fluoroscopy, radiography, magnetic resonance imaging (MRI), computed tomography (CT) scan, or another suitable imaging method.

[0086] In some examples, the model includes at least one of a neural network or an iterative maximum likelihood estimator for determining relative positions of leads (e.g., lead 230) or one or more distances between two or more electrodes (e.g., of electrodes 232 and electrodes 234). More generally, the model may include an artificial intelligence (AI) engine or a machine learning (ML) engine. The neural network, iterative maximum likelihood estimator, AI engine, or ML engine may aid in determining a best (or most probable) relative position of leads or one or more distances between two or more electrodes given the input impedance values into the model. In some examples, the neural network includes an activation function and depth customized to the complexity of the neural network.

[0087] The model, neural network, and / or iterative maximum likelihood estimator may utilize one or more inputs to determine relative and absolute positions of leads 230, electrodes 232 and / or electrodes 234. In some examples, an input into the neural network or the iterative maximum likelihood estimator includes the plurality of impedance values. For example, processing circuitry 214 may be configured to apply the plurality of impedance values for stimulation and recording pairs of electrodes of electrodes 232 and electrodes 234 to the neural network or the iterative maximum likelihood estimator. In some examples, processing circuitry 214 is configured to apply cross-impedance values for all stimulation and recording pairs of electrodes 232 and / or electrodes 234. In some examples, processing circuitry 214 is configured to apply cross-impedance values for less than all stimulation and recording pairs of electrodes 232 and / or electrodes 234 (e.g., in the case of missing cross- impedance values, or where some cross-impedance values are purposely excluded). In some examples, processing circuitry 214 may be configured to apply other values as inputs to the neural network or the iterative maximum likelihood estimator includes the plurality of impedance values. For example, other inputs for the neural network or the iterative maximumDocket No.: A0010253WO01 / 1123-791WO01 likelihood estimator may include, but are not limited to, one or more of device information (e.g., a size, configuration, model of device, device-specific offsets, etc.), patient information (e.g., patient gender, height, weight, body mass index (BMI), spinal disease state, implant location, patient position information, etc.), sensed physiological signal information (e.g., local field potentials, ECAPs, ECG, etc.) or other relevant information. In some examples, the spinal disease state includes one or more of scoliosis, kyphosis, compression fractures, lordosis, or other relevant conditions. Patient position information may include a patient’s current position including supine, prone, sitting, standing, etc., as well as changes in position over time. In some examples, an input includes medical imaging data, such as medical imaging data obtained from initial lead placement into a patient. The neural network or the iterative maximum likelihood estimator, and the model more generally, may use inputs in determining or estimating one or more outputs (e.g., distances) between the two or more electrodes of the electrodes 232 and electrodes 234.

[0088] In some examples, an output of the neural network or the iterative maximum likelihood estimator includes the one or more distances between the two or more electrodes of the electrodes 232 and electrodes 234. For example, the neural network or the iterative maximum likelihood estimator may be configured to output a value (or a range of values) of one or more distances between the two or more electrodes of the electrodes 232 and electrodes 234. In some examples, the output includes an average, mean, or other representative value of a set one or more distances between the two or more electrodes of the electrodes 232 and electrodes 234. Additionally or alternatively, an output of the neural network or the iterative maximum likelihood estimator may include one or more distances or positions of leads 230, electrodes 232, and / or electrodes 234 relative to one or more anatomical features. In some examples, the anatomical feature includes one or more of portions of the spine, spinal cord, dorsal root ganglion (DRG), dorsal roots / rootlets, dorsal root entry zone, and / or ventral roots / rootlets. Processing circuitry 214 may be configured to determine, based on an output of the neural network or the iterative maximum likelihood estimator, whether one or more electrodes (e.g., of electrodes 232 and / or electrodes 234) is within an inter-vertebral space or under a vertebra.

[0089] In some examples, the neural network or the iterative maximum likelihood estimator is trained with at least one of medical imaging data or data indicative of positional measurements between leads. As described above with respect to the model more generally, the neural network or the iterative maximum likelihood estimator experimental may be trained with medical imaging data. The medical imaging data may include one or moreDocket No.: A0010253WO01 / 1123-791WO01 images of medical leads including electrodes. In some examples, imaging data include data gathered during placements, reposition, extraction of leads (e.g., leads 230), and / or other annotations indicating locations of one or more electrodes within the imaging data. Medical imaging data may be generated from fluoroscopy, radiography, magnetic resonance imaging (MRI), computed tomography (CT) scan, or another suitable imaging method. In some examples, training data may include experimental values taken from animal or bench models. In some examples, training data may also include data from human subject. In some examples, an ML engine is utilized in interpreting images to serve as input to the model.

[0090] In some examples, processing circuitry 214 is configured to determine, based on an output of the model, one or more distances between the two or more electrodes of electrodes 232 and / or electrodes 234. In some examples, processing circuitry 214, with or without the neural network or the iterative maximum likelihood estimator discussed above, is configured to output at least one distance between the two or more electrodes of electrodes 232 and / or electrodes 234. However, in some examples, processing circuitry 214 is configured to output all distances between the two or more electrodes of electrodes 232 and / or electrodes 234. In some examples, processing circuitry 214 is configured to output a summary or representative values (e.g., an average or mean) of the distances between the two or more electrodes of electrodes 232 and / or electrodes 234.

[0091] In some examples, processing circuitry 214 is configured to determine a quality metric based on a fit of the plurality of impedance values to the model. Because the data (e.g., the impedance values) are fit to the model, the quality metric may indicate how the data fits the model. In some examples, the fit to the model may include a measure of how the model is able to generalize new data similar to the data with which the model was trained. For example, processing circuitry 214 may be configured to determine a numerical value (e.g., a confidence score, a p-value, a percentage, correlation coefficient, or another value) indicating the closeness of fit of the data (e.g., the plurality of impedance values) to the model. In some examples, the quality metric as a percentage is expressed as a whole number (e.g., 98 percent), as a decimal (e.g., 0.98), or as another suitable parameter or indication. In some examples, the quality metric includes a confidence score of zero to one. Processing circuitry 214 may determine the confidence score using at least one of bootstrapping or “leave one out” techniques. In examples where the model includes at least one of a neural network, iterative maximum likelihood estimator, or other ML modality, the quality metric may indicate a likelihood that the output of the at least one of a neural network, iterative maximum likelihood estimator, or other ML modality, is correct. The quality metric mayDocket No.: A0010253WO01 / 1123-791WO01 provide a clinician or other user confidence about a determination of one or more distances between leads 230 and / or electrodes of electrodes 232 and / or 234, or other outputs of the model.

[0092] In some examples, processing circuitry 214 may compare the quality metric with another value (e.g., a threshold) to provide an output (e.g., a warning, an indication of acceptable or poor fit, etc.). In some examples, processing circuitry 214 may be configured to determine whether more data is needed (e.g., in order to accurately provide an output).

[0093] In some examples, processing circuitry 214 is configured to determine whether the quality metric meets a pre-defined quality metric threshold. For example, processing circuitry 214 may be configured to compare the quality metric to the pre-defined quality metric threshold. Processing circuitry 214 may be configured to determine whether the quality metric exceeds the pre-determined quality metric threshold. In some examples, the pre- defined quality metric threshold is 80 percent (e.g., 0.80 expressed as a decimal), 90 percent (e.g., 0.90 expressed as a decimal), 95 percent (e.g., 0.95 expressed as a decimal), 98 percent (e.g., 0.98 expressed as a decimal), 99 percent (e.g., 0.99 expressed as a decimal), 99.5 percent (e.g., 0.995 expressed as a decimal), 99.9 percent (e.g., 0.999 expressed as a decimal), or another suitable threshold. In some examples, such as when using anatomically based models, a higher quality metric threshold (e.g., 0.95) is used. In some examples, such as when using simplified models (e.g., in saline), a lower quality metric threshold (e.g., 0.80) is used. A quality metric threshold may be determined based on, at least in part, prior applications of the model. In some examples, the quality metric threshold may be used to select a particular model (e.g., from a plurality of different possible models).

[0094] In some examples, processing circuitry 214 is configured to compare the quality metric to the pre-defined quality metric threshold over a period of time (e.g., at one or more timepoints). In some examples, processing circuitry 214 is configured to compare the quality metric to the pre-defined quality metric threshold continuously (or near continuously). In some examples, processing circuitry 214 is configured to compare the quality metric to the pre-defined quality metric threshold in real-time (or near real-time to account for variations in processing time). In some examples, processing circuitry 214 is configured to compare the quality metric to multiple (e.g., two or more) quality metric thresholds. For example, a first quality metric threshold may be a warning threshold, and a second quality metric threshold may be a less acceptable (e.g., danger) threshold.

[0095] In some examples, processing circuitry 214 generates an output based on the comparison of the quality metric to the pre-defined quality metric threshold. For example,Docket No.: A0010253WO01 / 1123-791WO01 processing circuitry 214, alone or in combination with telemetry circuitry 213, may be configured to output information indicating the quality metric is equal to and / or above (or otherwise acceptable compared to) the pre-defined quality metric threshold. As another example, processing circuitry 214, alone or in combination with telemetry circuitry 213, may be configured to output information indicating the quality metric is below (or otherwise not acceptable compared to) the pre-defined quality metric threshold. In some examples, processing circuitry 214 is configured to output a warning or prompt, via a user device or display, to indicate the quality metric is below a pre-defined threshold. For example, processing circuitry 214 may be configured to prompt a user to reposition lead 230A, lead 230B, electrodes 232 and / or electrodes 234, or take another action in response to the quality metric being below the pre-defined quality metric threshold. In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, may prompt a user to initiate redetermination of the plurality of impedance values for one or more electrodes of electrodes 232 and / or electrodes 234 in response to the quality metric not meeting (e.g., not acceptable according to) the pre-defined quality metric.

[0096] In some examples, processing circuitry 214 is configured to determine impedance values for applying to the model in response to one or more trigger events. For example, processing circuitry 214 may be configured to detect a trigger event, and in response to detecting a trigger event, determine a plurality of updated impedance values. After determining the updated impedance values, processing circuitry 214 may be configured to apply the updated impedance values to the model. Based on an updated output of the model, processing circuitry 214 may be configured to determine a change (e.g., a change over time) between a first set of one or more distances between leads and / or electrodes and a second set of one or more distances between leads and / or electrodes, where the second set of one or more distances between leads and / or electrodes is associated with the updated impedance values. In this way, processing circuitry may determine changes to of one or more distances between leads and / or electrodes over time, or in response to certain trigger events. In some examples, such changes of one or more distances between leads and / or electrodes over time can indicate movement (e.g., including permanent displacement) of one or more of leads and / or electrodes.

[0097] Example trigger events (e.g., for determining updated impedance values, which can be used by processing circuitry 214 to determine changes in distances between leads and / or electrodes) may include, but are not limited to, a change in posture of patient 105 (e.g., as shown in FIG.1), the passing of a predetermined amount of time, a prompt from a userDocket No.: A0010253WO01 / 1123-791WO01 (e.g., via a user interface), a change in a recorded / sensed signal (e.g., ECAP, electrode impedance, and which can include a change above a predetermined threshold, etc.), or another suitable event. Processing circuitry 214 may receive signals from one or more sensors, monitor one or more clocks, and / or monitor received user input, to identify a trigger event. For example, where patient 105 changes position from sitting to standing, processing circuitry 214 may detect the change in position from an accelerometer signal or other signal indicative of the change in position and then responsively determine one more updated impedance values and one or more one or more distances between leads and / or electrodes. As another example, processing circuitry 214 may determine one more updated impedance values and one or more one or more distances between leads and / or electrodes after a predetermined (e.g., programmed) amount of time, such as after 1 hour, 1 day, 1 week, or another suitable amount of time. As another example, processing circuitry 214 may determine one or more updated impedance values in response to a change in an ECAP signal (in examples where ECAP is monitored). In some examples, processing circuitry 214 may determine the one or more updated impedance values in response to (e.g., as a condition of) the change in the ECAP signal is above a minimum ECAP signal change threshold, such that minor changes in the ECAP signal do not trigger processing circuitry 214 to determined updated impedance values. In other words, processing circuity 214 may be configured to not update the impedance values unless the change in the ECAP signal is above the minimum ECAP signal change threshold.

[0098] As another example, processing circuitry 214 may determine one or more updated impedance values in response to a change in an electrode impedance (in examples where an impedance of one or more electrodes, such as a subset of electrodes or less than all electrodes, is monitored). In some examples, processing circuitry 214 determines the one or more updated impedance values if the change in electrode impedance is above a minimum electrode impedance change threshold. For example, in some examples, processing circuitry 214 determines the one or more updated impedance values in response to determining that the change in electrode impedance for one or more electrodes is above the minimum electrode impedance change threshold. In some examples, processing circuitry 214 does not determine the one or more updated impedance values if the change in electrode impedance is not above the minimum electrode impedance change threshold (e.g., such that minor changes in electrode impedance do not trigger processing circuitry 214 to determined updated impedance values).Docket No.: A0010253WO01 / 1123-791WO01

[0099] In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213 (e.g., of IMD 200) and / or processing circuitry 353, alone or in combination with telemetry circuitry 352 of programmer 300 (as discussed in connection with FIG.3) is configured to generate, for output to a suitable device, information related to and / or based on the position and / or movement of leads and / or electrodes. In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, is configured to generate one or more of a prompt (e.g., for a user and / or a clinician to review information), a warning, and / or an alert based on positions and / or movement of leads and / or electrodes. In any of the examples discussed herein, information (e.g., including patient-specific information) can be transmitted between IMD 200, patient devices and / or clinician devices (e.g., including computing devices), including remote devices connected via a network (e.g., as discussed in connection with FIG.13).

[0100] In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, may be configured to output (e.g., for display), information of the changes to one or more distances between leads and / or electrodes over time (e.g., over a pre- defined time period), such as the difference between the determined distances and the one or more updated distances. In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, may be configured to output an indication (e.g., an alert, warning, such as by text message, push notification, email, or the like) if movement of the leads and / or electrodes is above a pre-defined threshold (e.g., a pre-defined movement threshold of leads and / or electrodes relative to each other and / or another reference). In some examples, if processing circuitry 214 determines movement of the leads and / or electrodes is above a pre-defined threshold, processing circuitry 214, alone or in combination with telemetry circuitry 213, can be configured to output a prompt to a clinician to intervene and / or review information related to leads and / or electrodes. In some examples, based on determining movement of the leads and / or electrodes is above a pre-defined threshold, processing circuitry 214, alone or in combination with telemetry circuitry 213 is configured to generate a notification and / or prompt for output on a patient and / or clinician device to review information related to the leads and / or electrodes.

[0101] In some examples, processing circuitry 214 is configured to determine different levels of movement (e.g., migration) of leads 230, electrodes 232, and / or electrodes 234, and output information depending on the level of movement. In some examples, processing circuitry 214 is configured to compare estimated relative positions of leads 230, electrodes 232, and / or electrodes 234 at one or more time points (e.g., to determine a relativeDocket No.: A0010253WO01 / 1123-791WO01 displacement of leads 230, electrodes 232, and / or electrodes 234 between the one or more time points). For example, a relatively large change in cross-impedance values between different time points may indicate a fall of the patient, a loss of therapy, or another event. In response to the relatively large change in cross in cross-impedance values (e.g., a change in cross-impedance values greater than a pre-defined threshold), which may be indicative of movement of leads 230 and / or electrodes 232 above a pre-defined movement threshold over a pre-defined time period, processing circuitry 214 may be configured generate one or more of a prompt and / or an alert via a user interface or display (e.g., for a user, such as a patient and / or clinician), initiate other measurements (e.g., electrophysiological recordings), alter stimulation therapy (e.g., including turning off stimulation or adjusting a stimulation parameter), or a combination thereof.

[0102] In some examples, processing circuitry 214 is configured to differentiate between and / or classify different types of movement of leads 230, electrodes 232, and / or electrodes 234, and output information accordingly. For example, in some examples, processing circuitry 214 is configured to determine and / or classify that movement of leads 230, electrodes 232, and / or electrodes 234 is a permanent movement (e.g., migration) of one leads 230, electrodes 232, and / or electrodes 234, and output information based on the determination of the movement being a permanent movement. In some examples, a permanent movement can include a movement of one or more of leads 230, electrodes 232, and / or electrodes 234 that results in a displacement of one or more leads 230, electrodes 232, and / or electrodes 234 to a new location (e.g., within patient 105). In some examples, processing circuitry 214 determines that a movement of one of leads 230, electrodes 232, and / or electrodes 234 is a permanent movement based on determining that the movement is above a pre-defined threshold (e.g., a pre-defined movement threshold and / or a change in cross-impedance values being greater than a pre-defined threshold) and / or that the change in position of one of leads 230, electrodes 232, and / or electrodes 234 is sustained for at least a pre-defined time period (e.g., wherein the pre-defined time period is more than 24 hours, such as more than 48 hours). In some examples, based determining and / or classifying the type of movement, processing circuitry 214 is configured generate one or more of a prompt and / or an alert (e.g., via a user interface or display, such as for a user including a patient and / or clinician), initiate other measurements (e.g., electrophysiological recordings), alter stimulation therapy (e.g., including turning off stimulation), or a combination thereof. Processing circuitry 214 may not generate a prompt and / or an alert in cases where processing circuitry 214 does not classify a movement of leads 230, electrodes 232, and / or electrodesDocket No.: A0010253WO01 / 1123-791WO01 234 as a permanent movement (e.g., in cases of slight movements and / or movements that are not sustained for a particular pre-defined time period).

[0103] In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, is configured to output (e.g., for display), information of the migration of leads 230 over time (e.g., a visualization of leads 230 at different time points). In some examples, data indicative of lead migration may enable a clinician to determine (e.g., program, reprogram, transfer, etc.) system settings for therapy. In some examples, as discussed in connection with FIG.13, processing circuitry 214, alone or in combination with telemetry circuitry 213 is configured to output information to a clinician (e.g., to a clinician programmer and / or a remote computing device) via a network.

[0104] In some examples, processing circuitry 214 is configured to generate information related to the distances between and / or movement of leads 230, electrodes 232, and / or electrodes 234 based on a status (e.g., activity status) of leads 230, electrodes 232, and / or electrodes 234. For example, in some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, are configured to generate and output information related to the distances between and / or movement of leads 230, electrodes 232, and / or electrodes 234 in the case that such leads and / or electrodes that are “active” (e.g., programmed to deliver electrical stimulation therapy and / or configured to sense patient parameters according to a therapy program). In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, does not generate and output information related to the distances between and / or movement of leads 230, electrodes 232, and / or electrodes 234 for leads and / or electrodes that are not “active” (e.g., not programmed to deliver electrical stimulation therapy and / or not configured to sense patient parameters according to a therapy program). In some examples, processing circuitry 214 is configured to determine an activity status of one or more of lead 230A, lead 230B, electrodes 232, and / or electrodes 234 and generate information related to and / or based on the distances between and / or movement of leads 230, electrodes 232, and / or electrodes 234 based on the activity status. In some examples, processing circuitry 214 determines which of leads 230, electrodes 232, and / or electrodes 234 are active (e.g., according to a current therapy stimulation program), and outputs information related to the distances between and / or movement for those active leads 230, electrodes 232, and / or electrodes 234. In some examples, processing circuitry 214, alone or in combination with telemetry circuitry 213, is configured to output a prompt to a clinician to intervene and / or review information related to leads and / or electrodes based on determining distances between and / or movement of active ones of leads 230,Docket No.: A0010253WO01 / 1123-791WO01 electrodes 232, and / or electrodes 234. In examples where at least some of electrodes 232 and / or electrodes 234 are not active (e.g., according to a current therapy stimulation program), processing circuitry 214 does not generate information related to the distances and / or movement of such inactive ones of lead 230A, lead 230B, electrodes 232, and / or electrodes 234.

[0105] In some examples, electrode proximity unit 222, or another suitable component of memory 215, is configured to store information corresponding to the model (e.g., inputs, outputs, algorithms, activation functions, quality metrics, trigger events, etc.). Processing circuitry 214 may be configured to access, from memory 215, information corresponding to the model. For example, electrode proximity unit 222 may be configured to store impedance values and / or cross-impedance values for electrodes 232 and / or electrodes 234, and processing circuitry 214 may be configured to access cross-impedance values for determining one or more distances between two more electrodes of electrodes 232 and / or electrodes 234.

[0106] In addition to the aforementioned techniques, one or techniques of this disclosure may be used to monitor one or more patient conditions. For example, processing circuitry 214 may be configured to determine the progression of a disease state based on relative or absolute positions of leads 230, electrodes 232, and / or electrodes 234. For example, a disease state, such as disc degeneration, compression fracture, or another disease state, may cause movement of leads 230, electrodes 232, and / or electrodes 234. In some examples, a disease state may cause motion of anatomical structures (such as disks) relative to leads 230, electrodes 232, and / or electrodes 234. For example, an intra-disk vertebral space may decrease, at least in part, in response to a disk fracture. In some examples, processing circuitry 214 is configured to determined relative or absolute positions of leads 230A at one or more predetermined time points (e.g., to monitor progression of the disease state). As another example, processing circuitry 214 may be configured to monitor water retention (e.g., in the case of diabetes) as impedance and / or cross impedance may be affected by hydration state. As another example, processing circuitry 214 may be configured to monitor patient ergonomics (e.g., time spent sitting, standing, slouching, or lying down) based on relative or absolute positions of leads 230, electrodes 232, and / or electrodes 234.

[0107] In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured output information indicative of the one or more distances between the two or more electrodes of electrodes 232 and / or electrodes 234. For example, telemetry circuitry 213 may be configured to output (e.g., present) information indicative of the one or more distances between the two or more electrodes of electrodes 232Docket No.: A0010253WO01 / 1123-791WO01 and / or electrodes 234 on a display or user interface. In some examples, a user interface displays the information indicative of the one or more distances between the two or more electrodes of electrodes 232 and / or electrodes 234. In some examples, a user interface may display information indicative of the one or more distances between the two or more electrodes of electrodes 232 and / or electrodes 234 in real time or near real-time so that a clinician can select or adjust one or more stimulation parameters for stimulation therapy. In some examples, the information indicative of the one or more distances between the two or more electrodes may enable the clinician to select which electrodes of electrodes 232 from lead 230A and / or electrodes 234 from lead 230B are to be included in the electrode combination used for stimulation therapy. In some examples, one or more stimulation parameters includes selective activation of a subset of electrodes 232 and / or electrodes 234 for therapy delivery. In some examples, the information indicative of the one or more distances between the two or more electrodes may enable a clinician to reposition lead 230A and / or 230B to improve efficacy of stimulation therapy. As compared to other methods of determining relative or absolute positions of lead and / or electrodes, the techniques of this disclosure may provide greater accuracy (e.g., sub-electrode accuracy). In some examples, processing circuitry 214 may provide relative or absolute positions of lead and / or electrodes within one-fourth or about one-fourth of an electrode.

[0108] In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured to output information indicative of relative positions of leads 230. In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured to display estimated relative positions of leads 230 along with medical imaging data (e.g., such as an overlay). In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured to display past or expected future movement and / or migration based on comparing estimated relative positions of leads and medical imaging data (e.g., previously acquired medical imaging data). In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured to display an overlay of estimated relative positions of leads 230 onto previously or concurrently acquired medical images. In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured to display a probability map of estimated relative positions of leads 230 (e.g., multiple possible positions of leads 230 and associated probabilities thereof).

[0109] In some examples, processing circuitry 214 is configured to select one or more stimulation parameters based one or more distances between the two or more electrodes ofDocket No.: A0010253WO01 / 1123-791WO01 electrodes 232 and / or electrodes 234 and control delivery of electrical stimulation to the patient according to the one or more stimulation parameters. Adjustment of stimulation parameters including electrode combination for therapy may enhance the therapeutic effect of stimulation therapy to patient 105. For example, processing circuitry 214 may automatically (e.g., without user or clinician input), select or adjust which electrodes of electrodes 232 from lead 230A and / or electrodes 234 from lead 230B are to be included in the electrode combination used for stimulation therapy. In this way, processing circuitry 214 may automatically activate, via stimulation generation circuitry 211, a subset of electrodes 232 and / or electrodes 234 for therapy delivery.

[0110] In some examples, processing circuitry 214 is configured to determine or select electrode combinations for eliciting and recording ECAP signals at least partially based on relative positions of leads. In some examples, processing circuitry 214 is configured to select or adjust electrode combination at least in part based on a desired conduction velocity and / or latency. For example, processing circuitry 214 may be configured to select or adjust the electrode combination to achieve longer conduction velocity therapy targeting lower back and leg targets and shorter conduction velocity for lateral targets. In some examples, processing circuitry 214 may be configured to determine or select (e.g., without user input) electrodes for ECAP recording based on distances between leads (e.g., where recording electrodes are greater than a minimum threshold distance away from stimulation pairs of electrodes). Distances between leads may be distances between physical locations on leads, or distances between leads may be determined or estimated through cross-impedance measurements. Processing circuitry 214 may be configured to automatically select electrodes for ECAP recording at least in part based on minimization of noise (artifact). Additionally or alternatively, processing circuitry 214 may be configured to determine, select, or adjust the sense window for ECAP peak detection. In some examples, where processing circuitry 214 detects a twist in one or more leads 230, and one or more electrodes of electrodes 232 and / or electrodes 234 are not aligned with other electrodes on the respective lead, processing circuitry 214 may be configured to exclude one or more electrodes of electrodes 232 and / or electrodes 234 for ECAP signal detection. Electrodes that are not aligned may not be optimal for detecting ECAP signals.

[0111] While the aforementioned description pertains primarily to determining relative positions of electrodes and / or leads to each other, processing circuitry 214 may also be configured to determine, based on a bioelectric signal (e.g., an ECAP signal, ECG signal) (instead of or in addition to impedance values), a proximity of one or more electrodes (e.g., ofDocket No.: A0010253WO01 / 1123-791WO01 electrodes 232 and / or electrodes 234) to an anatomical feature of patient 105. In some examples, the anatomical feature includes one or more of portions of the spine, spinal cord 120, dorsal root ganglion (DRG), dorsal roots / rootlets, dorsal root entry zone, and / or ventral roots / rootlets. For example, stimulation generation circuitry 211 may be configured to deliver electrical stimulation to the patient in a plurality of pulses to elicit a plurality of ECAP signals. In some examples, one or more pulses of the plurality of pulses is configured to elicit a respective ECAP signal of the one or more ECAP signals. In some examples, the processing circuitry 214 is configured to determine, based on a latency of the one or more ECAP signals, a proximity of the one or more electrodes (e.g., of electrodes 232 and / or electrodes 234) to an anatomic features of patient 105. For example, processing circuitry 214 may be configured to determine, based on a latency (or other change, such as amplitude) of one or more ECAP signals, a proximity of one or more electrodes (e.g., of electrodes 232 and / or electrodes 234) to a midline of the epidural space of the patient. In some examples, processing circuitry 214 may be configured to determine, such as based on the one or more ECAP signals or a change in the one or more ECAP signals, whether one or more electrodes (e.g., of electrodes 232 and / or electrodes 234) is within an inter-vertebral space or under a vertebra.

[0112] In some examples, processing circuitry 214 is configured to determine relative or absolute positions of electrodes and / or leads in relation anatomical features based on one or more ECG signals and / or ECG values derived from ECG signals. For example, recording an ECG signal across various pairs of electrodes of electrodes 232 and / or electrodes 234 may indicate the absolute positions of leads 230 and / or electrodes 232 and / or electrodes 234 relative to the heart or particular vertebrae. Because an ECG signal may be strongest near the heart (e.g., the origin of the signal), ECG values may be useful for determining the relative positions of leads 230 and / or electrodes 232 and / or electrodes 234 near the thoracic level. In some examples, sensing circuitry 212 is configured to detect and record one or more ECG signal values via electrodes 232 and / or electrodes 234 and / or sensor 216. Processing circuitry 214 may be configured to apply the one or more ECG signal values to a model defining a relationship between the one or more ECG values and distances between an anatomical feature (e.g., the heart) and one or more electrodes of electrodes 232 and / or electrodes 234. Information indicative of a patient’s posture (e.g., obtained via sensor 216, which may include an accelerometer), may be used with one or more ECG signal values to determine relative and / or absolute positions of leads 230 and / or electrodes 232 and / or electrodes 234. As heart positions relative to vertebrae may change with a patient’s posture (e.g., standing,Docket No.: A0010253WO01 / 1123-791WO01 lying, sitting, etc.), information indicative of a patient’s posture may be used in determining absolute positions of leads 230 and / or electrodes 232 and / or electrodes 234 to a patient’s heart or vertebrae. In some examples, processing circuitry 214 is configured to determined migration of leads and / or electrodes (e.g., in relation to each other or anatomical features) at least in part based on one or more ECG signal values. In some examples, processing circuitry 214 is configured to determine heart rate and / or heart rate variability based on the ECG signal.

[0113] In some examples, processing circuitry 214 may additionally be configured to determine relative or absolute positions of leads 230 and / or electrodes 232 and / or electrodes 234 at least partially based on absolute impedance measurements. In some examples, absolute impedance measurements include impedance measurements from an electrode or pair of electrodes (e.g., of leads 230 and / or electrodes 232 and / or electrodes 234) that is used for both stimulation and recording. Absolute impedance measurements may be larger than relative impedance measurements, where relative impedance measurements use different electrodes for stimulation and recording. In some examples, absolute impedance measurements include multiple impedance components based on different pulse widths. For example, absolute impedance measurements may include a first impedance component in response to a first pulse width (e.g., which may be an access impedance component of the absolute impedance measurements). Absolute impedance measurements may include a second impedance component in response to a second pulse width (e.g., which may be a polarization impedance component of the absolute impedance measurements). In some examples, the first pulse width associated with the first impedance component is narrower than the second pulse width associated with the second impedance component, and the second pulse width is wider than the first pulse width. In some examples, the access impedance component is different than the polarization impedance component. In some examples, at least the access impedance component is indicative of a relative or absolute positions a lead or an electrode (e.g., of leads 230 and / or electrodes 232 and / or electrodes 234) to one or more anatomical features of patient a patient. In some examples, the polarization impedance component may be indicative of a level of hydration of tissue of a patient.

[0114] In some examples, processing circuitry 214, and / or processing circuitry 353 of programmer 300 (as discussed in connection with FIG.3) may be configured to generate and / or use a template for permanent lead (e.g., leads 230) placement. For example, processing circuitry 214 may be configured to generate an implantation template (e.g., anDocket No.: A0010253WO01 / 1123-791WO01 implantation model) based on information from an implantation trial period. The implantation template may include suggested lead locations for lead implantation. An implantation trial period may include a period of time shorter than a chronic (e.g., permanent) period. Information from the implantation trial period may include one or more of data indicative of lead migration during the implantation trial period, patient feedback during the implantation trial period, data indicative of patient habitus, data indicative of patient posture (e.g., during implantation, or at one or more points during the trial period), and / or data indicative of implantation / fixation technique. For example, data indicative of lead migration (e.g., of leads 230) during the trial period may include a displacement of leads over time or a relative positions of leads at one or more timepoints (e.g., to determine when lead migration occurred). Data indicative of lead migration during the implantation trial period may include information of relative and / or absolute locations of leads and / or electrodes to each other or to anatomical features according to the techniques of this disclosure (e.g., based on impedance, based on bioelectric signals such as ECAP or ECG, etc.). Information from the trial period may inform a user (e.g., a clinician) about where to place leads for chronic implantation. In some examples, lead migration during a trial implant period may affect the efficacy of therapy a patient receives.

[0115] In some examples, processing circuitry 214 may be configured to generate information for chronic placement at least in part based on the implantation template for permanent lead placement. For example, processing circuitry 214 may generate information for a user (e.g., a clinician) of where to place leads (e.g., leads 230) for permanent placement based on the implantation template. In some examples, processing circuitry 214 generates suggested lead locations based on the implantation template. In some examples, processing circuitry 214 generates suggested electrode combinations (e.g., for stimulation and / or ECAP recording) based on the implantation template. In some examples, processing circuitry 214 generates a predicted lead migration based on the implantation template.

[0116] In some examples, telemetry circuitry 213, alone or in combination with processing circuitry 214, is configured output information indicative of the proximity of the one or more electrodes (e.g., of electrodes 232 and / or electrodes 234) to the anatomical feature of the patient. For example, telemetry circuitry 213 may be configured to output (e.g., display) information indicative of the one or more distances of or more electrodes of electrodes 232 and / or electrodes 234 to the anatomical feature on a display. In some examples, a user interface displays the information indicative of the one or more distances of or more electrodes of electrodes 232 and / or electrodes 234 to the anatomical feature. In someDocket No.: A0010253WO01 / 1123-791WO01 examples, a user interface may display the information indicative of the one or more distances of or more electrodes of electrodes 232 and / or electrodes 234 to the anatomical feature in real time or near real-time so that a clinician can select or adjust one or more stimulation parameters for stimulation therapy. In some examples, the information indicative of the one or more distances of or more electrodes of electrodes 232 and / or electrodes 234 to the anatomical feature may enable the clinician to select which electrodes of electrodes 232 from lead 230A and / or electrodes 234 from lead 230B are to be included in the electrode combination used for stimulation therapy. In some examples, the information indicative of the one or more distances of or more electrodes of electrodes 232 and / or electrodes 234 to the anatomical feature may enable a clinician to reposition lead 230A and / or 230B to improve efficacy of stimulation therapy.

[0117] In some examples, memory 215 is store at least one of the plurality of impedance values for electrodes 232 and / or electrodes 234, one or more distances between the two or more electrodes of electrodes 232 and / or electrodes 234, or the information indicative of the one or more distances between the two or more electrodes of electrodes 232 and / or electrodes 234. In some examples, the one or more impedance values, the one or more distances, or information indicative of the one or more distances may be retrieved from memory 215, such as by processing circuitry 214. In some examples, a user (e.g., via a user interface), may access previously determined impedance values, distances, or information indicative of distances.

[0118] FIG.3 is a block diagram of the example external programmer 300, in accordance with one or more techniques of this disclosure. External programmer 300 may be an example of external programmer 150 of FIG.1. Although programmer 300 may generally be described as a hand-held device, programmer 300 may be a larger portable device or a more stationary device. In addition, in other examples, programmer 300 may be included as part of an external charging device or include the functionality of an external charging device. As illustrated in FIG.3, programmer 300 may include a processing circuitry 353, memory 354, user interface 351, telemetry circuitry 352, and power source 355. Memory 354 may store instructions that, when executed by processing circuitry 353, cause processing circuitry 353 and external programmer 300 to provide the functionality ascribed to external programmer 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 353 may include processing circuitry configured to perform the processes discussed with respect to processing circuitry 353.Docket No.: A0010253WO01 / 1123-791WO01

[0119] In general, programmer 300 comprises any suitable arrangement of hardware, alone or in combination with software and / or firmware, to perform the techniques attributed to programmer 300, and processing circuitry 353, user interface 351, and telemetry circuitry 352 of programmer 300. In various examples, 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. Programmer 300 also, in various examples, may include a memory 354, such as 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, comprising executable instructions for causing the one or more processors to perform the actions attributed to them. Moreover, although processing circuitry 353 and telemetry circuitry 352 are described as separate modules, in some examples, processing circuitry 353 and telemetry circuitry 352 are functionally integrated. In some examples, processing circuitry 353 and telemetry circuitry 352 correspond to individual hardware units, such as ASICs, DSPs, FPGAs, or other hardware units.

[0120] Memory 354 (e.g., a storage device) may store instructions that, when executed by processing circuitry 353, cause processing circuitry 353 and programmer 300 to provide the functionality ascribed to programmer 300 throughout this disclosure. For example, memory 354 may include instructions that cause processing circuitry 353 to obtain a parameter set from memory 354, or receive a user input and send a corresponding command to IMD 110, or instructions for any other functionality. In addition, memory 354 may include a plurality of programs, where each program includes a parameter set that defines therapy stimulation or control stimulation. Memory 354 may also store data received from a medical device (e.g., IMD 110). For example, memory 354 may store bioelectrical signal related data (e.g., ECAP signal values), cross-impedance values for electrodes, or other data. Memory 354 may also store information indicative of the one or more distances between the two or more electrodes of electrodes 132 and / or electrodes 134. Memory 354 may also store data or information corresponding to the model (e.g., inputs, outputs, algorithms, activation functions, quality metrics, trigger events, etc.).

[0121] User interface 351 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 may be a touch screen. User interface 351 may be configured to display any information related to the delivery ofDocket No.: A0010253WO01 / 1123-791WO01 electrical stimulation, sensing of one or more bioelectric signals, implant of one or more leads, identified patient behaviors, sensed patient parameter values, patient behavior criteria, or any other such information. In some examples, user interface 351 is configured to display information related to cross-impedance values of electrodes, distance between electrodes and / or leads, as well as information related to model used for determining the relationship between cross-impedance values and one or more distances, including summary information of the inputs, outputs, or other parameters of the model. User interface 351 may also receive user input via user interface 351. The user input may be, for example, in the form of pressing a button on a keypad or selecting an icon from a touch screen. The user input may request starting or stopping electrical stimulation, the user input may request a new spatial electrode movement pattern or a change to an existing spatial electrode movement pattern, of the user input may request some other change to the delivery of electrical stimulation. Other user inputs may include inputs for the model.

[0122] Telemetry circuitry 352 may support wireless communication between the medical device and programmer 300 under the control of processing circuitry 353. Telemetry circuitry 352 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 352 provides wireless communication via an RF or proximal inductive medium. In some examples, telemetry circuitry 352 includes an antenna, which may take on a variety of forms, such as an internal or external antenna.

[0123] Examples of local wireless communication techniques that may be employed to facilitate communication between 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 programmer 300 without needing to establish a secure wireless connection. As described herein, telemetry circuitry 352 may be configured to transmit a spatial electrode movement pattern or other stimulation parameter values to IMD 110 for delivery of electrical stimulation therapy.

[0124] In some examples, selection of parameters or therapy stimulation programs may be transmitted to the medical device for delivery to the patient. In other examples, the therapy may include medication, activities, or other instructions that the patient must perform themselves or a caregiver perform for the patient. In some examples, programmer 300 may provide visual, audible, and / or tactile notifications that indicate there are new instructions.Docket No.: A0010253WO01 / 1123-791WO01 Programmer 300 may require receiving user input acknowledging that the instructions have been completed in some examples.

[0125] According to the techniques of the disclosure, user interface 351 of external programmer 300 receives an indication from a clinician instructing a processor of the medical device to update one or more therapy stimulation programs or to update one or more ECAP test stimulation programs. Updating therapy stimulation programs and ECAP test stimulation programs 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 pulse shape of the informed pulses and / or control pulses. User interface 351 may also receive instructions from the clinician commanding any electrical stimulation, including therapy stimulation and control stimulation to commence or to cease.

[0126] The architecture of 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 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.

[0127] In some examples, an external device may include functionality attributed to both IMD 200 and external programmer 300. For example, during the interoperative positioning process, the external device may be coupled to the one or more leads 130 in order to deliver stimulus and sense ECAPs in response to each respective stimulus. In addition, the external device may include a user interface that provides, visual, audible, and / or tactile feedback regarding the position of the lead (or electrodes of the lead) to facilitate physician placement of the lead with respect to the anatomy of the patient. In other examples, a fully automated external device may implement the techniques described herein for implanting and positioning lead 130.

[0128] 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 signal 404 and ECAP signal 406 are sensed from control pulses that were delivered via a guarded cathode, where the control pulses are bi-phasic 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 404Docket No.: A0010253WO01 / 1123-791WO01 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 control pulse was sub-detection threshold.

[0129] In contrast to ECAP signal 404, ECAP signal 406 represents the voltage amplitude detected from a supra-detection threshold control pulse. Peaks 408 of ECAP signal 406 are detected and represent the artifact of the delivered control pulse. After peaks 408, ECAP signal 406 also includes peaks P1, N1 (sometime referred to as a valley), and P2, which are three typical peaks representative of propagating action potentials from an ECAP. In the illustrated example, duration of the artifact and peaks P1, N1, and P2 is approximately 1 millisecond (ms). When detecting the ECAP of ECAP signal 406, different characteristics may be identified. For example, the characteristic of the ECAP may be the amplitude between N1 and P2. This N1-P2 amplitude may be easily detectable even if the artifact, a relatively large signal, impinges on P1. Additionally, the N1-P2 amplitude may be minimally affected by electronic drift in the signal. In other examples, the characteristic of the ECAP used to detect the posture state of the patient and / or control informed pulses may be an amplitude of P1, N1, or P2 with respect to neutral or zero voltage. In some examples, the characteristic of the ECAP may be a sum of two or more of peaks P1, N1, or P2. In other examples, the characteristic of ECAP signal 406 may be the area under one or more of peaks P1, N1, and / or P2. In other examples, the characteristic of the ECAP may be a ratio of one of peaks P1, N1, or P2 to another one of the peaks. In some examples, the characteristic of the ECAP is a slope between two or more points in the ECAP signal, such as the slope between N1 and P2. For example, the characteristic may include the difference between two slopes (i.e., slope from N1 to P2 and the slope from P2 to end, etc.). In other examples, the characteristic of the ECAP may be the time between two points of the ECAP, such as the time between N1 and P2. 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. The amplitude of the ECAP signal generally increases with increasedDocket No.: A0010253WO01 / 1123-791WO01 amplitude of the control pulse, as long as the pulse amplitude is greater than threshold such that nerves depolarize and propagate the signal.

[0130] FIG.5 illustrates lead 230A and lead 230B (collectively “leads 230”) of an implantable medical device (e.g., IMD 110 of FIG.1 or IMD 200 of FIG.2) implanted adjacent to a spinal cord 504 in an epidural space, in accordance with one or more techniques of this disclosure. FIG.5 illustrates vertebrae 506A, vertebrae 506B, and vertebrae 506C (collectively “vertebrae 506”) with lamina and transverse processes. In the example of FIG. 5, lead 230A includes electrode 232A, electrode 232B, electrode 232C, and electrode 232D (collectively “electrodes 232”). In the example of FIG.5, lead 230B includes electrode 234A, electrode 234B, electrode 234C, and electrode 232D (collectively “electrodes 234”). FIG.5 illustrates leads 230 in the location along spinal cord 504 at which leads 230 are implanted (e.g., the “implant location”). IMD 110 is programmed with one or more sets of stimulation parameters (e.g., amplitude and pulse width, etc.) to provide effective therapy to patient 105 at the implant location. The effectiveness of the stimulation parameters may wane as leads 230 (and the associated electrodes 232 and / or electrodes 234) migrate from implant location such that the stimulation parameters may need to be adjusted to continue to provide effective therapy.

[0131] FIG.6 – FIG.10 illustrate examples various relative positions and orientations of leads 230, electrodes 232, and electrodes 234 that could occur after implantation. In accordance with the techniques described herein, information indicative of the relative positions and / or orientations may provide a clinician or other user feedback needed to adjust one or more stimulation parameters and / or to adjust the positions and orientations of leads 230, electrodes 232, and electrodes 234. Information indicative of the positions and orientations of leads 230, electrodes 232, and electrodes 234 may enable more effective therapy for patient 105. The following descriptions also reference components of system 100 of FIG.1 and IMD 200 of FIG.2, but may be used with any of the devices of this disclosure. While the examples of FIGS.6 – FIG.10 depict one or more distances and one or more angles between leads and / or electrodes, the examples described herein are for illustrative purposes only. In some examples, the number of distances and / or angles may vary depending on the model, available inputs, desired outputs, or other factors.

[0132] FIG.6 illustrates an example lead configuration wherein a first lead 230A is offset from a second lead 230B. In the example of FIG.6, lead 230A is disposed on a first side (e.g., right side, such as when viewing a patient posteriorly) of a midline 672 (e.g., a midline of spinal cord 504, as shown in connection with FIG.5), and lead 230B is disposed on aDocket No.: A0010253WO01 / 1123-791WO01 second side (e.g., left side) of midline 672. For purposes of illustration, lead 230A is shown as parallel to lead 230B in the example of FIG.6, with both lead 230A and lead 230B being parallel to midline 672. However, as will be described in connection with other examples, lead 230A and lead 230B may be disposed at other relative orientations, including, but not limited to, disposed at an angle (e.g., diverging or converging), crossed, or other relative orientations. Similarly, for purposes of illustration, while lead 230A and lead 230B are shown as straight or substantially straight, lead 230A and 230B may individually have lead shapes other than straight. For example, lead 230A and or lead 230B may be curved at any portion along a lead body of each respective lead.

[0133] In the example of FIG.6, lead 230A is horizontally offset from midline 672 by a distance A, measured as a horizontal distance between a reference point on lead 230A and a second reference point on midline 672. In the example of FIG.6, distance A is measured as a horizontal distance between a first point at the horizontal midpoint of electrodes 232 on lead 230A and a second point on midline 672. However, any suitable point may be used as the first reference point on lead 230A determine the horizontal displacement between lead 230A and midline 672. In the example of FIG.6, a horizontal distance refers to a distance measured parallel to the horizontal or transverse anatomical plane (e.g., when patient 105 is in the standing position). In some examples, processing circuitry 214 is configured to determine horizonal distance A, or another suitable measure of horizontal displacement between lead 230A and midline 672, or another suitable anatomical feature, by applying a plurality of impedance values of electrodes 232 to the model. Similarly, processing circuitry 214 may be configured to determine a horizontal distance between lead 230B and midline 672.

[0134] In the example of FIG.6, lead 230A is vertically offset from lead 230B by a vertical distance B, measured as a vertical distance between a first reference point on lead 230A and a second reference point on lead 230B. In the example of FIG.6, vertical distance B is measured as a vertical distance between a first point (e.g., a midpoint) between electrode 232C and electrode 232D on lead 230A and a second point (e.g., a midpoint) between electrode 234C and electrode 234D on lead 230B. However, any suitable point may be used as the first reference point or the second reference point to determine the vertical displacement between lead 230A and lead 230B. In the example of FIG.6, a vertical distance refers to a distance measured parallel to the median anatomical plane (e.g., when patient 105 is in the standing position). In some examples, processing circuitry 214 is configured to determine vertical distance B, or another suitable measure of vertical displacement betweenDocket No.: A0010253WO01 / 1123-791WO01 lead 230A and lead 230B, by applying a plurality of impedance values of electrodes 232 and / or electrodes 234 to the model.

[0135] In the example of FIG.6, lead 230A is also horizontally offset from lead 230B by a horizontal distance C, measured as a horizontal distance between a first reference point on lead 230A and a second reference point on lead 230B. In the example of FIG.6, horizontal distance C is measured as a horizontal distance between a first point at the horizontal midpoint of electrodes 232 on lead 230A and a second point at the horizontal midpoint of electrodes 234 on lead 230B, which may be a distance at a right angle to both leads or an average of the distances at different points long the leads. However, any suitable point may be used as the first reference point or the second reference point to determine the horizontal displacement between lead 230A and 230B. In the example of FIG.6, a horizontal distance refers to a distance measured parallel to the horizontal or transverse anatomical plane (e.g., when patient 105 is in the standing position). In some examples, processing circuitry 214 is configured to determine horizonal distance C, or another suitable measure of horizontal displacement between lead 230A and lead 230B, by applying cross-impedance values of electrodes 232 and / or electrodes 234 to the model.

[0136] FIG.7 illustrates an example lead configuration wherein first lead 230A is diverging with respect to second lead 230B (e.g., diverging moving towards a distal end of each respective lead of lead 230A and lead 230B). In the example of FIG.7, lead 230A is offset from lead 230B by a distal a horizontal distance D, wherein horizontal distance D is measured from a first location on each respective lead 230A and lead 230B. For example, the first location is a horizontal midpoint of the distalmost electrode on each respective lead, such as electrode 232D on lead 230A and electrode 234D on lead 230B. Additionally, lead 230A is offset from lead 230B by distal horizontal distance E, wherein horizontal distance E is measured from a second location on each respective lead of lead 230A and lead 230B. For example, the second location is a horizontal midpoint of the proximal-most electrode on each respective lead, such as electrode 232A on lead 230A and electrode 234A on lead 230B. In the example of FIG.7, horizontal distance D is greater than horizontal distance E, indicating that lead 230A is diverging from lead 230B moving towards the distal end of each respective lead of lead 230A and lead 230B. In the example of FIG.7, lead 230B is disposed parallel to midline 672, and lead 230A is disposed at an angle F relative to midline 672 and lead 230B, wherein angle F is an acute angle measured between midline 672 and a central midline or central axis of lead 230A.Docket No.: A0010253WO01 / 1123-791WO01

[0137] In some examples, processing circuitry 214 is configured to determine whether lead 230A diverges from lead 230B or vice versa. In some examples, processing circuitry 214 is configured to determine horizontal distance D, horizontal distance E, and / or angle F by applying cross-impedance values of electrodes 232 and / or electrodes 234 to the model. In some examples, processing circuitry 214 determines the extent to which lead 230A diverges from lead 230B or vice versa by applying cross-impedance values of electrodes 232 and / or electrodes 234 to the model. In some examples, processing circuitry 214 determines the extent to which lead 230A diverges from midline 672. For example, angle F may be a measure of the extent to which lead 230A diverges from lead 230B or midline 672, wherein a greater value of angle F indicates greater divergence. As another example, a greater difference between horizontal distance D and horizontal distance E indicates greater divergence between lead 230A and lead 230B.

[0138] FIG.8 illustrates an example lead configuration wherein first lead 230A is converging with respect to second lead 230B (e.g., converging moving towards a distal end of each respective lead of lead 230A and 230B). In the example of FIG.8, lead 230A is offset from lead 230B by a distal horizontal distance G, wherein horizontal distance G is measured from a first location on each respective lead 230A and lead 230B. For example, the first location is a horizontal midpoint of the distalmost electrode on each respective lead, such as electrode 232D on lead 230A and electrode 234D on lead 230B. Additionally lead 230A is offset from lead 230B by a distal horizontal distance H, wherein horizontal distance H is measured from a second location on each respective lead of lead 230A and lead 230B. For example, the second location is a horizontal midpoint of the proximal-most electrode on each respective lead, such as electrode 232A on lead 230A and electrode 234A on lead 230B. In the example of FIG.8, horizontal distance G is less than horizontal distance H, indicating that lead 230A is converging towards lead 230B moving towards the distal end of each respective lead of lead 230A and 230B. In the example of FIG.8, lead 230B is disposed parallel to midline 672, and lead 230A is disposed at an angle J relative to midline 672 and lead 230B, wherein angle J is an acute angle measured between midline 672 and a central midline or central axis of lead 230A.

[0139] In some examples, processing circuitry 214 is configured to determine whether lead 230A converges towards lead 230B or vice versa. In some examples, processing circuitry 214 is configured to determine horizontal distance G, horizontal distance H, and / or angle J by applying cross-impedance values of electrodes 232 and / or electrodes 234 to the model. In some examples, processing circuitry 214 determines the extent to which lead 230ADocket No.: A0010253WO01 / 1123-791WO01 converges towards lead 230B or vice versa. In some examples, processing circuitry 214 determines the extent to which lead 230A converges towards midline 672. For example, angle J may be a measure of the extent to which lead 230A converges toward lead 230B or midline 672, wherein a greater value of angle J indicates greater convergence. As another example, a greater difference between horizontal distance G and horizontal distance H indicates greater convergence between lead 230A and lead 230B.

[0140] FIG.9 illustrates an example lead configuration wherein first lead 230A is curved or twisted with respect to second lead 230B (e.g., curving or twisting away moving towards a distal end of each respective lead of lead 230A and 230B). In the example of FIG.9, lead 230A is offset from lead 230B by a distal horizontal distance K, wherein horizontal distance K is measured from a first location on each respective lead 230A and lead 230B. For example, the first location is a horizontal midpoint of the distalmost electrode on each respective lead, such as electrode 232D on lead 230A and electrode 234D on lead 230B. Additionally lead 230A is offset from lead 230B by a distal horizontal distance M, wherein horizontal distance M is measured from a second location on each respective lead of lead 230A and lead 230B. For example, the second location is a horizontal midpoint of the proximal-most electrode on each respective lead, such as electrode 232A on lead 230A and electrode 234A on lead 230B. In the example of FIG.9, horizontal distance K is greater than horizontal distance M, indicating that lead 230A is diverging from lead 230B moving towards the distal end of each respective lead of lead 230A and 230B.

[0141] In the example of FIG.9, lead 230B is disposed parallel to midline 672. As lead 230A is twisted or curved, lead 230A may be disposed at multiple angles along the lead body of lead 230A with respect to midline 672 or lead 230B. For example, lead 230A is disposed at a first angle N at a first point along lead 230A, wherein angle N is an acute measured between midline 672 and a first horizontal axis parallel to a first central axis of lead 230A (e.g., a first central axis at a proximal-most electrode lead 230A, such as electrode 232A). Lead 230A is disposed at a second angle P at a second point along lead 230A, wherein angle P is an acute measured between midline 672 and a second horizontal axis parallel to a second central axis of lead 230A (e.g., a second central axis at a distalmost electrode lead 230A, such as electrode 232D). In the example of FIG.9, angle N is less than angle P, indicating that lead 230A is twisting or curving away from midline 672 and or lead 230B.

[0142] In some examples, processing circuitry 214 is configured to determine whether lead 230A curves or twists with respect to lead 230B or vice versa . In some examples, processing circuitry 214 is configured to determine horizontal distance K, horizontal distanceDocket No.: A0010253WO01 / 1123-791WO01 M, angle N and / or angle P by applying cross-impedance values of electrodes 232 and / or electrodes 234 to the model. Further, processing circuitry 214 may determine distances between all of electrodes 232 and electrodes 234 by applying cross-impedance values to the model. In some examples, processing circuitry 214 determines the extent to which lead 230A curves or twists away (or towards) lead 230B, or vice versa. In some examples, processing circuitry 214 determines the extent to which lead 230A curves or twists away (or towards) midline 672. For example, a greater difference between angle N and angle P indicates greater curve or twist of lead 230A with respect to lead 230B.

[0143] FIG.10 illustrates an example lead configuration wherein first lead 230A is crossed or overlapping with second lead 230B. In the example of Fig.10, lead 230B is vertical or nearly vertical, and a distal portion of lead 230A is disposed on a first (e.g., left) side of lead 230B and a proximal portion of lead 230A is disposed on a second (e.g., right) side of lead 230B. In some examples, processing circuitry 214 is configured to determine whether lead 230A crosses or overlaps lead 230B or vice versa by applying cross-impedance values of electrodes 232 and / or electrodes 234 to the model. Although one or more leads may be placed in different angles or curves in the patient, processing circuitry 214 may use the actual distances between electrodes for electrode combination selection or the selection of other values of stimulation parameters, and / or recommendation of such selection. The system may generate these angles or curves for generating an image representative of the leads implanted within the patient.

[0144] While FIGS.6–10 and the corresponding descriptions describe selected relative orientations of lead 230A, lead 230B, electrodes 232, and / or electrodes 234, the relative orientations may be present in any combination. For example, portions of lead 230A and 230B may be diverging with respect to each other while other portions of lead 230A and 230B may be converging with respect to each other. Processing circuitry 214 may be configured to determine one or more areas of convergence and / or one or more areas of divergence of lead 230A with respect to lead 230B. Further, some portions of either of lead 230A and / or lead 230B may exhibit curve or twist while other portions of lead 230A and / or lead 230B are straight or substantially straight. Processing circuitry 214 may be configured to determine one or more areas of curve, twist, and / or straightness in lead 230A and lead 230B. Processing circuitry 214 may be configured to determine multiple relative orientations of lead 230A and 230B along either or both of lead 230A and 230B. Additionally, while FIGS.6-10 primarily describe relative orientations of lead 230A and lead 230B with respect to eachDocket No.: A0010253WO01 / 1123-791WO01 other, any of the aforementioned relative orientations may be with respective to an anatomical feature of patient 105.

[0145] FIG.11 illustrates an example user interface 1160 related to information of related to relative lead and / or positions according to the techniques of this disclosure. User interface 1160 may be implemented as part of external programmer 150 of FIG.1, programmer 300 of FIG.3, or another suitable device. For example, user interface 1160 may be an example of user interface 351 as shown in FIG.3. The following descriptions in the example of FIG.11 also reference components of system 100 of FIG.1, IMD 200 of FIG.2, and selected anatomical features as depicted in FIG.5, but may be used with any of the devices of this disclosure. User interface 1160 may include a screen 1162 with various boxes or areas that displays relevant information. User interface 1160 may provide a user with information about relative positions of leads 230, electrodes 232, electrodes 234, and / or anatomical features of patient 105. Although user interface 1160 may have static boxes to display information related relative positions of leads, electrodes, and anatomical features, one or more pop-up boxes, tabs, or other types of alerts are contemplated.

[0146] In the example of FIG.11, user interface 1160 provides a user (which may be a patient, clinician, or another suitable user) with information related to the relative position of leads 1130A and 1130B (collectively “leads 1130”), which may be graphical representations corresponding to leads 230 carrying respective electrodes 232, electrodes 234, and / or anatomical features of patient 105. Vertebrae 1106 may be graphical representations of vertebrae 506. For example, screen 1162 includes box 1164 showing information related to leads 1130. Box 1164 includes box 1166, where box 1166 includes a representative value of a relative position between lead 1130A and lead 1130B (shown as “7mm”) and a quality metric of the fit to the model (shown as “0.953”), each of which are described previously. Box 1164 also includes a representative image depicting the relative orientation of lead 1130A with respect to lead 1130B. The representative image depicting the relative orientation of leads may be based on estimated relative position of leads as described above (e.g., based on an output of a model), medical imaging data, or any suitable combination thereof (e.g., including overlays of the estimated relative positions of leads onto acquired medical images). Box 1164 also includes representative positions of each electrode (shown as circles) of electrodes disposed on lead 1130A and electrodes disposed on lead 1130B. Numbers of each electrode (0-15) are shown in screen 1162, which may facilitate identification of desired electrodes. A user may use information from user interface 1160 to select one or more parameters for therapy delivery, including selective activation of a subset of electrodes 232 and / or electrodesDocket No.: A0010253WO01 / 1123-791WO01 234 for therapy delivery. In some examples, each electrode on leads 1130 may be selectable by a user for stimulation or sensing. In some examples, screen 1162 may show electrodes without lines connecting each electrode. In some electrodes, screen 1162 may display an icon that looks similar to an actual lead that is implanted.

[0147] In some examples, processing circuitry (e.g., processing circuitry 353 of programmer 300) may be configured to display, via user interface 1160 or another suitable user interface, data indicative of estimated relative lead positions and / or acquired medical imaging data. For example, user interface 1160 may be configured display a location probability map (e.g., in examples where determining relative lead includes a neural network or an iterative maximum likelihood estimator). In some examples, user interface 1160 is configured to display estimated distances, angles, or other measures of estimated lead positions (e.g., relative to acquired medical images). As discussed previously, user interface 1160 may display an overlay of estimated lead positions with acquired medical images.

[0148] FIG.12 is a flow chart illustrating an example technique for determining relative lead or electrode position. The example technique of FIG.12 is discussed in relation to the components of system 100 of FIG.1 and IMD 200 of FIG.2, such as processing circuitry 214, but may be used with any of the devices, circuitry, components, or combination thereof, described in this disclosure.

[0149] Processing circuitry 214 may determine a plurality of impedance values for a plurality of electrodes (e.g., electrodes 232 and / or electrodes 234) implanted within patient 105 (1202). In some examples, processing circuitry 214 determines the plurality of impedance values using different stimulation pulses (e.g., one or more stimulation pulses) with different pulse widths. For example, stimulation generation circuitry 211 may generate, via one or more electrodes of electrodes 232 and / or electrodes 234, one or more stimulation pulses having a first pulse width. The resulting voltage may be recorded across one or more recording pairs of electrodes of electrodes 232 and / or electrodes 234 to determine a first set of cross-impedance values. Further, stimulation generation circuitry 211 may generate, via one or more electrodes of electrodes 232 and / or electrodes 234, one or more stimulation pulses having a second pulse width. The resulting voltage may be recorded across one or more recording pairs of electrodes of electrodes 232 and / or electrodes 234 to determine a second set of cross-impedance values. This may be repeated with any suitable number of pulses having any number of pulse widths (e.g., one, two, three, four, five, ten, twenty, fifty, etc.) to determine multiple sets of cross-impedance values. In some examples, stimulation generation circuitry 211 generates two or more stimulation pulses with the same pulse width.Docket No.: A0010253WO01 / 1123-791WO01 Depending on the number of pulse widths used in the model, using multiple pulse width to determine multiple sets of cross-impedance values may enhance or confirm an estimate of one or more distances between two or more electrodes of electrodes 232 and / or electrodes 234.

[0150] Processing circuitry 214 may apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for electrodes 132 and / or electrodes 134 and one or more distances between two or more electrodes of electrodes 132 and / or electrodes 134 (1204). In some examples, the model includes at least one of a neural network or an iterative maximum likelihood estimator. In some examples, an input into the at least one of the neural network or the iterative maximum likelihood estimator includes the plurality of impedance values. In some examples, an output of the at least one of the neural network or the iterative maximum likelihood estimator includes the one or more distances between the two or more electrodes of electrodes 132 and / or electrodes 134. In some examples, the neural network and / or the iterative maximum likelihood estimator is trained with at least one of medical imaging data or data indicative of positional measurements between leads 130. In some examples, as described above, processing circuitry determines a quality metric based on a fit of the plurality of impedance values for electrodes 132 and / or electrodes 134 to the model.

[0151] Processing circuitry 214 may determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes (1206). In examples where electrodes 132 and electrodes 134 are disposed leads (e.g., lead 130A and lead 130B), processing circuitry 214 may determine an orientation of a first lead (e.g., lead 130A) with respect to a second lead (e.g., lead 130B). In some examples, processing circuitry 214 determines a proximity of one or more electrodes of electrodes 132 and / or electrodes 134 to an anatomical feature of patient 105.

[0152] Processing circuitry 214 may output information indicative of the one or more distances between the two or more electrodes of electrodes 132 and / or electrodes 134 (1208). In some examples, processing circuitry 214 may output information indicative of the proximity of the one or more electrodes of electrodes 132 and / or electrodes 134 to an anatomical feature of the patient. For example, processing circuitry 214 may cause a user interface to display the distances or a representation of the distances to the user, such as via external programmer 150 using a user interface such as user interface 1160 of FIG.11. In some examples, processing circuitry 214 may generate electrode combination recommendations and / or other stimulation parameter value recommendations based on theDocket No.: A0010253WO01 / 1123-791WO01 distances between the electrodes. In response to electrode configuration selection and / or receiving other stimulation parameter selection, processing circuitry 214 may control IMD 110 to deliver electrical stimulation according to the stimulation parameter values selected (e.g., electrode combination, amplitude, frequency, pulse width, etc.).

[0153] FIG.13 is a block diagram illustrating an example system 1300 that includes an external device, such as a server 360, and one or more computing devices 362A–362N, that are coupled to IMD 110 and external programmer 150 shown in FIG.1 via a network 358. In this example, IMD 110 may use its telemetry circuit to communicate with external programmer 150 via a first wireless connection, and to communication with an access point 350 via a second wireless connection. In some examples, programmer 150 may communicate with IMD 110 via an intermediate device that can facilitate transferring between different communication protocol requirements between IMD 110 and programmer 150.

[0154] In the example of FIG.13, access point 350, external programmer 150, server 360, and computing devices 362A–362N are interconnected, and able to communicate with each other, through network 358. In some cases, one or more of access point 350, external programmer 150, server 360, and computing devices 362A–362N may be coupled to network 358 through one or more wireless connections. In some examples, computing device 362N (or any other computing devices) may be configured to communicate directly to programmer 150 over communication link 356 (e.g., via short range wireless communication such as Bluetooth) such that programmer 150 can relay commands or data between IMD 110 and computing device 362N. IMD 110, external programmer 150, server 360, and computing devices 362A–362N may each comprise one or more processors, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic circuitry, or the like, that may perform various functions and operations, such as those described in this disclosure.

[0155] Access point 350 may comprise a device, such as a home monitoring device, that connects to network 358 via any of a variety of connections, such as telephone dial-up, digital subscriber line (DSL), or cable modem connections. In other examples, access point 350 may be coupled to network 358 through different forms of connections, including wired or wireless connections.

[0156] During operation, IMD 110 may collect and store various forms of data. For example, IMD 110 may collect sensed posture state information during therapy that indicate how patient 105 moves throughout each day. IMD 110 may store usage statistics (e.g., delivery times in hours per day, percentage of on time, compliance to the dosing schedule,Docket No.: A0010253WO01 / 1123-791WO01 etc.) for later presentation to a user or otherwise evaluating therapy and / or patient compliance. In some cases, IMD 110 may directly analyze the collected data to evaluate the status of the patient and / or other aspects of the patient. In some cases, IMD 110 may directly analyze collected data to evaluate delivered therapy. In some cases, IMD 110 may directly analyze collected data to evaluate a position of one of leads 130 and / or one or more electrodes 132, and / or one or more electrodes 134. In some cases, IMD 110 may directly analyze collected data to evaluate movement and / or displacement (e.g., over a relevant time period) of one of leads 130 and / or one or more electrodes 132, and / or one or more electrodes 134. In other cases, however, IMD 110 may send stored data relating to a patient status, delivered therapy, and / or a position or movement of one of leads 130 and / or one or more electrodes 132, and / or one or more electrodes 134 to server 360, either wirelessly or via access point 350 and network 358, for remote processing and analysis.

[0157] For example, IMD 110 may sense, process, trend and evaluate sensed data (e.g., including data related to therapy delivery and / or data and / or information related to the positions of leads 130 and / or electrodes 132 and / or electrodes 134). This communication may occur in real time, and network 358 may allow a remote clinician to review the data (e.g., data and / or information related to the positions of leads 130 and / or electrodes 132 and / or electrodes 134) by receiving a presentation of the data on a remote display, e.g., computing device 362A. Alternatively, processing, trending and evaluation functions may be distributed to other devices such as external programmer 150 or server 360, which are coupled to network 358. In addition, data may be archived by any of such devices, e.g., for later retrieval and analysis by a clinician.

[0158] In some cases, server 360 may be configured to provide a secure storage site for archival of data that has been collected from IMD 110 and / or external programmer 150. Network 358 may comprise a local area network, wide area network, or global network, such as the Internet. In other cases, external programmer 150 or server 360 may assemble data and / or information in web pages or other documents for viewing by trained professionals, such as clinicians, via viewing terminals associated with computing devices 362A–362N. System 1300 may be implemented, in some aspects, with general network technology and functionality similar to that provided by the Medtronic CareLink® Network developed by Medtronic, Inc., of Minneapolis, MN.

[0159] Although some examples of the disclosure may involve information related to the positions and / or movement of leads and / or electrodes and related data, system 1300 may be employed to distribute any information relating to the treatment of patient 105 and theDocket No.: A0010253WO01 / 1123-791WO01 operation of any device associated therewith. For example, system 1300 may allow therapy errors or device errors to be immediately reported to the clinician. In addition, system 1300 may allow the clinician to remotely intervene in the therapy and reprogram IMD 110, programmer 150, or communicate with patient 105. In an additional example, the clinician may utilize system 1300 to monitor multiple patients and share data with other clinicians in an effort to coordinate rapid evolution of effective treatment of patients.

[0160] The following examples are described herein:

[0161] Example 1. A system comprising: processing circuitry configured to: determine a plurality of impedance values for a plurality of electrodes implanted within a patient; apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and output information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0162] Example 2. The system of example 1, wherein to output the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes, the processing circuitry is configured to output, via a display, a user interface, or an alert, the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0163] Example 3. The system of any of examples 1 or 2, wherein the processing circuitry is configured to determine a quality metric based on a fit of the plurality of impedance values to the model.

[0164] Example 4. The system of any of examples 1 to 3, wherein a first subset of the plurality of electrodes is configured to provide a pre-defined current, wherein a second subset of the plurality of electrodes is configured to record a resulting voltage from the pre-define current, and wherein the plurality of impedance values is based on the pre-defined current and the resulting voltage.

[0165] Example 5. The system of example 4, wherein the pre-defined current includes a first pre-defined current value, wherein the processing circuitry is configured to update the pre-defined current to a second pre-defined current value based on the resulting voltage of the second subset of the plurality of electrodes.

[0166] Example 6. The system of any of examples 1 to 5, further comprising a plurality of leads, wherein the plurality of electrodes is disposed on the plurality of leads, and whereinDocket No.: A0010253WO01 / 1123-791WO01 the processing circuitry is further configured to determine, based on the one or more distances, an orientation of a first lead of the plurality of leads with respect to a second lead of the plurality of leads.

[0167] Example 7. The system of example 6, wherein the orientation of the first lead of the plurality of leads with respect to the second lead of the plurality of leads comprises one or more of parallel, disposed at an angle, and crossed.

[0168] Example 8. The system of any of examples 1 to 7, wherein the processing circuitry is configured to: determine, based on a bioelectric signal, a proximity of one or more electrodes of the plurality of electrodes to an anatomical feature of the patient; and output information indicative of the proximity of the one or more electrodes of the plurality of electrodes to the anatomical feature of the patient.

[0169] Example 9. The system of example 8, further comprising stimulation generation circuitry configured to deliver electrical stimulation to the patient, wherein the bioelectric signal comprises one or more evoked compound action potential (ECAP) signals, wherein the electrical stimulation comprises a plurality of pulses, and wherein one or more pulses of the plurality of pulses is configured to elicit a respective ECAP signal of the one or more ECAP signals.

[0170] Example 10. The system of example 9, wherein the processing circuitry is configured to: determine, based on a latency of the one or more ECAP signals, a proximity of the one or more electrodes to a midline of the epidural space of the patient; and output information indicative of the proximity of the one or more electrodes to the midline of the epidural space of the patient.

[0171] Example 11. The system of any of examples 8 to 10, wherein the model defines a relationship between the plurality of impedance values and the proximity of the one or more electrodes of the plurality of electrodes to the anatomical feature of the patient.

[0172] Example 12. The system of any of examples 8 to 11, wherein the processing circuitry is configured to select an electrode combination for ECAP recording at least in part based on the one or more ECAP signals and the plurality of impedance values.

[0173] Example 13. The system of any of examples 1 to 12, wherein to determine the plurality of impedance values for the plurality of electrodes, the processing circuitry is configured to: determine the plurality of impedance values using different pulses with different pulse widths.

[0174] Example 14. The system of any of examples 1 to 13, wherein the processing circuitry is configured to: determine one or more electrodes of the plurality of electrodesDocket No.: A0010253WO01 / 1123-791WO01 associated with one or more impedance values above a maximum impedance threshold; and exclude, from application to the model, the one or more impedance values above the maximum impedance threshold.

[0175] Example 15. The system of any of examples 1 to 14, wherein the processing circuitry is configured to: detect a trigger event; in response to detecting the trigger event, determine a plurality of updated impedance values for the plurality of electrodes; apply the plurality of updated impedance values to the model; determine, based on an updated output of the model, one or more updated distances between the two or more electrodes of the plurality of electrodes; and determine a difference between the one or more distances and the one or more updated distances.

[0176] Example 16. The system of example 15, wherein the processing circuitry is configured to output, via a display, a user interface, or an alert, information indicative of the determined difference between the one or more distances and the one or more updated distances.

[0177] Example 17. The system of any of examples 1 to 16, wherein the model comprises at least one of a neural network or an iterative maximum likelihood estimator, wherein an input into the at least one of the neural network or the iterative maximum likelihood estimator includes the plurality of impedance values, where an output of the at least one of the neural network or the iterative maximum likelihood estimator includes the one or more distances between the two or more electrodes of the plurality of electrodes, and wherein the at least one of the neural network or the iterative maximum likelihood estimator is trained with at least one of medical imaging data or data indicative of positional measurements between leads.

[0178] Example 18. The system of example 17, where the input into the at least one of the neural network or the iterative maximum likelihood estimator further includes at least one of a gender, a body mass index (BMI), or a spinal disease state.

[0179] Example 19. The system of any of examples 1 to 18, further comprising at least one of a programmer or an implantable medical device (IMD) that comprises some or all of the processing circuitry.

[0180] Example 20. The system of any of examples 1 to 19, wherein the processing circuitry is configured to select one or more stimulation parameters based on the one or more distances and control delivery of electrical stimulation to the patient according to the one or more stimulation parameters.Docket No.: A0010253WO01 / 1123-791WO01

[0181] Example 21. The system of example 20, wherein the one or more stimulation parameters includes selective activation of a subset of the plurality of electrodes for therapy delivery.

[0182] Example 22. The system of any of examples 1 to 21, wherein the one or more distances comprises one or more vertical distances between the two or more electrodes of the plurality of electrodes or one or more horizontal distances between the two or more electrodes of the plurality of electrodes.

[0183] Example 23. The system of any of examples 1 to 22, wherein to output the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes, the processing circuitry is configured to: present, on a display, the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0184] Example 24. The system of any of examples 1 to 23, wherein the system further comprises: a memory configured to store at least one of the plurality of impedance values, the one or more distances between the two or more electrodes of the plurality of electrodes, or the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0185] Example 25. A method comprising: determining, by processing circuitry, a plurality of impedance values for a plurality of electrodes implanted within a patient; applying, by the processing circuitry, the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determining, by the processing circuitry and based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and outputting, by the processing circuitry, information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0186] Example 26. The method of example 25, wherein outputting the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes, includes outputting, via a display, a user interface, or an alert, the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

[0187] Example 27. The method of any of examples 25 or 26, further comprising: determining, by the processing circuitry, a quality metric based on a fit of the plurality of impedance values to the model.Docket No.: A0010253WO01 / 1123-791WO01

[0188] Example 28. The method of any of examples 25 to 27 further comprising determining, by the processing circuitry and based on the one or more distances, an orientation of a first lead of a plurality of leads with respect to a second lead of the plurality of leads, wherein the plurality of electrodes is disposed on the plurality of leads.

[0189] Example 29. The method of any of examples 25 to 28, further comprising: determining, by the processing circuitry and based on a bioelectric signal, a proximity of one or more electrodes of the plurality of electrodes to an anatomical feature of the patient; and outputting, by the processing circuitry, information indicative of the proximity of the one or more electrodes of the plurality of electrodes to the anatomical feature of the patient.

[0190] Example 30. The method of any of examples 25 to 29, where determining, by the processing circuitry, the plurality of impedance values for the plurality of electrodes comprises: determining, by the processing circuitry, the plurality of cross-impedance values using different pulses with different pulse widths.

[0191] Example 31. The method of any of examples 25 to 30, further comprising: generating an implantation template based on a trial period; and generating information for chronic lead fixation based on the implantation template.

[0192] Example 32. The method of any of examples 25 to 31, wherein the model comprises at least one of a neural network or an iterative maximum likelihood estimator, wherein an input into the at least one of the neural network or the iterative maximum likelihood estimator includes the plurality of impedance values, where an output of the at least one of the neural network or the iterative maximum likelihood estimator includes the one or more distances between the two or more electrodes of the plurality of electrodes, and wherein the at least one of the neural network or the iterative maximum likelihood estimator is trained with at least one of medical imaging data or data indicative of positional measurements between leads.

[0193] Example 33. A computer-readable medium comprising instructions that, when executed, control processing circuitry to: determine a plurality of impedance values for a plurality of electrodes implanted within a patient; apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and output information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.Docket No.: A0010253WO01 / 1123-791WO01

[0194] 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.

[0195] 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.

[0196] 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

Docket No.: A0010253WO01 / 1123-791WO01 WHAT IS CLAIMED IS:

1. A system comprising: processing circuitry configured to: determine a plurality of impedance values for a plurality of electrodes implanted within a patient; apply the plurality of impedance values to a model, the model defining a relationship between the plurality of impedance values for the plurality of electrodes and one or more distances between two or more electrodes of the plurality of electrodes; determine, based on an output of the model, the one or more distances between the two or more electrodes of the plurality of electrodes; and output information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

2. The system of claim 1, wherein to output the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes, the processing circuitry is configured to output, via a display, a user interface, or an alert, the information indicative of the one or more distances between the two or more electrodes of the plurality of electrodes.

3. The system of any of claims 1 and 2, wherein the processing circuitry is configured to determine a quality metric based on a fit of the plurality of impedance values to the model.

4. The system of any of claims 1 through 3, wherein a first subset of the plurality of electrodes is configured to provide a pre-defined current, wherein a second subset of the plurality of electrodes is configured to record a resulting voltage from the pre-define current, and wherein the plurality of impedance values is based on the pre-defined current and the resulting voltage.

5. The system of any of claims 1 through 4, further comprising a plurality of leads, wherein the plurality of electrodes is disposed on the plurality of leads, andDocket No.: A0010253WO01 / 1123-791WO01 wherein the processing circuitry is further configured to determine, based on the one or more distances, an orientation of a first lead of the plurality of leads with respect to a second lead of the plurality of leads.

6. The system of any of claims 1 through 5, wherein the processing circuitry is configured to: determine, based on a bioelectric signal, a proximity of one or more electrodes of the plurality of electrodes to an anatomical feature of the patient; and output information indicative of the proximity of the one or more electrodes of the plurality of electrodes to the anatomical feature of the patient.

7. The system of claim 6, further comprising stimulation generation circuitry configured to deliver electrical stimulation to the patient, wherein the bioelectric signal comprises one or more evoked compound action potential (ECAP) signals, wherein the electrical stimulation comprises a plurality of pulses, and wherein one or more pulses of the plurality of pulses is configured to elicit a respective ECAP signal of the one or more ECAP signals.

8. The system of claim 7, wherein the processing circuitry is configured to: determine, based on a latency of the one or more ECAP signals, a proximity of the one or more electrodes to a midline of the epidural space of the patient; and output information indicative of the proximity of the one or more electrodes to the midline of the epidural space of the patient.

9. The system of any of claims 1 through 8, wherein to determine the plurality of impedance values for the plurality of electrodes, the processing circuitry is configured to: determine the plurality of impedance values using different pulses with different pulse widths.

10. The system of any of claims 1 through 9, wherein the processing circuitry is configured to:Docket No.: A0010253WO01 / 1123-791WO01 determine one or more electrodes of the plurality of electrodes associated with one or more impedance values above a maximum impedance threshold; and exclude, from application to the model, the one or more impedance values above the maximum impedance threshold.

11. The system of any of claims 1 through 10, wherein the processing circuitry is configured to: detect a trigger event; in response to detecting the trigger event, determine a plurality of updated impedance values for the plurality of electrodes; apply the plurality of updated impedance values to the model; determine, based on an updated output of the model, one or more updated distances between the two or more electrodes of the plurality of electrodes; and determine a difference between the one or more distances and the one or more updated distances.

12. The system of claim 11, wherein the processing circuitry is configured to output, via a display, a user interface, or an alert, information indicative of the determined difference between the one or more distances and the one or more updated distances.

13. The system of any of claims 1 through 12, wherein the model comprises at least one of a neural network or an iterative maximum likelihood estimator, wherein an input into the at least one of the neural network or the iterative maximum likelihood estimator includes the plurality of impedance values, where an output of the at least one of the neural network or the iterative maximum likelihood estimator includes the one or more distances between the two or more electrodes of the plurality of electrodes, and wherein the at least one of the neural network or the iterative maximum likelihood estimator is trained with at least one of medical imaging data or data indicative of positional measurements between leads.

14. The system of any of claims 1 through 13, further comprising at least one of a programmer or an implantable medical device (IMD) that comprises some or all of the processing circuitry.Docket No.: A0010253WO01 / 1123-791WO01 15. The system of any of claims 1 through 14, wherein the processing circuitry is configured to: select one or more stimulation parameters based on the one or more distances; and control delivery of electrical stimulation to the patient according to the one or more stimulation parameters.

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