Systems and methods for calibrating and adjusting a device based on a hybrid assessment

Abstract

Systems and methods for calibrating and adjusting a device based on a hybrid assessment are provided. A device configured to generate a stimulation and a lead configured to deliver the stimulation to a target anatomical region are provided. The device may be programmed with one or more parameters. The device may be caused to deliver the stimulation and stimulation data may be received corresponding to the stimulation received by the user. Sensor data may also be received. The device may be calibrated based on the stimulation data and the sensor data.

Description

SYSTEMS AND METHODS FOR CALIBRATING AND ADJUSTING A DEVICE BASED ON A HYBRID ASSESSMENTCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application Serial No. 63 / 530,204, filed August 1, 2023, 2024, the entire content of which is incorporated herein by reference.BACKGROUND

[0002] The present disclosure is generally directed to neuromodulation and, more specifically, is directed toward calibrating and adjusting one or more parameters of a device based on a hybrid assessment.

[0003] Neuromodulation therapy may be carried out by sending an electric signal generated by a pulse generator to a stimulation target (e.g., nerves, non-neuronal cells, etc.), which may provide a stimulating or blocking therapy to the stimulation target. Overstimulation or under stimulation of the stimulation target may occur, which could lead to patient dissatisfaction.BRIEF SUMMARY

[0004] Example aspects of the present disclosure include:

[0005] A system according to at least one embodiment of the present disclosure comprises a device configured to generate a stimulation; a lead configured to deliver the stimulation to a target anatomical region; a processor; and a memory capable of storing data thereon that, when processed by the processor, cause the processor to: program the device with one or more parameters; cause the device to deliver the stimulation; receive stimulation data corresponding to the stimulation received by the user; receive sensor data; and calibrate the device based on the stimulation data and the sensor data.

[0006] Any of the aspects herein, further comprising: a sensor configured to measure output corresponding to a distance between the lead and the target anatomical region and to yield the sensor data corresponding to the measured distance.

[0007] Any of the aspects herein, wherein calibrating the device includes measuring an output corresponding to an initial distance between the lead and the target anatomical element and correlating the initial distance with the stimulation data.

[0008] Any of the aspects herein, wherein the output comprises at least one of a voltage, current, or capacitance.

[0009] Any of the aspects herein, wherein the sensor comprises at least one of an ultrasound sensor or a near-infrared reflectometry sensor.

[0010] Any of the aspects herein, wherein the stimulation is generated to a level where a target evoked compound action potential (ECAP) is detected in the stimulation data.

[0011] Any of the aspects herein, wherein calibrating the device includes correlating the sensor data and the stimulation data.

[0012] Any of the aspects herein, wherein the data further causes the processor to: detect a recalibration event; and recalibrate the device when the recalibration event is detected.

[0013] Any of the aspects herein, wherein the recalibration event comprises at least one of a period of time has passed, a number of stimulations have been delivered, a user input has been received, a change in one or more parameters of an ECAP has occurred, or a change in user activity, user posture, or user biochemical state has occurred.

[0014] A system according to at least one embodiment of the present disclosure comprises a device configured to generate a stimulation; a lead configured to deliver the stimulation to a target anatomical region; a processor; and a memory capable of storing data thereon that, when processed by the processor, cause the processor to: cause the pulse generator to generate the stimulation and deliver the stimulation to the target anatomical region via the lead; receive stimulation data corresponding to the stimulation delivered to the user; receive sensor data; and adjust one or more one or more parameters of the device based on the sensor data.

[0015] Any of the aspects herein, further comprising: a sensor configured to measure an output corresponding to a distance between the lead and the target anatomical region, the sensor configured to yield the sensor data.

[0016] Any of the aspects herein, wherein the one or more parameters are adjusted based on a difference between an output corresponding to an initial distance and an output corresponding to a detected distance.

[0017] Any of the aspects herein, wherein the output corresponding to the initial distance is determined during a calibration of the device.

[0018] Any of the aspects herein, wherein the sensor comprises at least one of an ultrasound sensor or a near-infrared reflectometry.

[0019] Any of the aspects herein, wherein the data further causes the processor to: detect a recalibration event; and recalibrate the device when the recalibration event is detected.

[0020] Any of the aspects herein, wherein the recalibration event comprises at least one of a period of time has passed, a number of stimulations have been delivered, a user input has been received, a change in one or more parameters of an ECAP has occurred, or a change in user activity, user posture, or user biochemical state has occurred.

[0021] A system according to at least one embodiment of the present disclosure comprises a device configured to generate a stimulation; a lead configured to deliver the stimulation to a target anatomical region; a processor; and a memory capable of storing data thereon that, when processed by the processor, cause the processor to: cause the pulse generator to generate the stimulation and deliver the stimulation to the target anatomical region via the lead; receive stimulation data corresponding to the stimulation delivered to the user; receive sensor data; adjust one or more one or more parameters of the device based on the sensor data; and determine whether the stimulation meets or exceeds a predetermined threshold.

[0022] Any of the aspects herein, wherein the predetermined threshold corresponds to a level of the stimulation where an ECAP can be detected.

[0023] Any of the aspects herein, wherein the data further causes the processor to: adjust one or more parameters of the device based on the stimulation data when the stimulation is at or above the predetermined threshold.

[0024] Any of the aspects herein, wherein the stimulation data comprises an ECAP.

[0025] Any feature in combination with any one or more other features.

[0026] Any one or more of the features disclosed herein.

[0027] Any one or more of the features as substantially disclosed herein.

[0028] Any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein.

[0029] Any one of the aspects / features / embodiments in combination with any one or more other aspects / features / embodiments .

[0030] Use of any one or more of the aspects or features as disclosed herein.

[0031] It is to be appreciated that any feature described herein can be claimed in combination with any other feature(s) as described herein, regardless of whether the features come from the same described embodiment.

[0032] The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims.

[0033] The phrases “at least one”, “one or more”, and “and / or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and / or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. When each one of A, B, and C in the above expressions refers to an element, such as X, Y, and Z, or class of elements, such as XI -Xn, Yl-Ym, and Zl-Zo, the phrase is intended to refer to a single element selected from X, Y, and Z, a combination of elements selected from the same class (e.g., XI and X2) as well as a combination of elements selected from two or more classes (e.g., Y1 and Zo).

[0034] The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably.

[0035] The preceding is a simplified summary of the disclosure to provide an understanding of some aspects of the disclosure. This summary is neither an extensive nor exhaustive overview of the disclosure and its various aspects, embodiments, and configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, embodiments, and configurations of the disclosure are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.

[0036] Numerous additional features and advantages of the present disclosure will become apparent to those skilled in the art upon consideration of the embodiment descriptions provided hereinbelow.BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

[0037] The accompanying drawings are incorporated into and form a part of the specification to illustrate several examples of the present disclosure. These drawings, together with the description, explain the principles of the disclosure. The drawings simply illustrate preferred andalternative examples of how the disclosure can be made and used and are not to be construed as limiting the disclosure to only the illustrated and described examples. Further features and advantages will become apparent from the following, more detailed, description of the various aspects, embodiments, and configurations of the disclosure, as illustrated by the drawings referenced below.

[0038] Fig. 1 is a diagram of a system according to at least one embodiment of the present disclosure;

[0039] Fig. 2 is a diagram of a pulse generator with leads connected to nerves according to at least one embodiment of the present disclosure;

[0040] Fig. 3 is a diagram of a system according to at least one embodiment of the present disclosure;

[0041] Fig. 4 is a flowchart according to at least one embodiment of the present disclosure;

[0042] Fig. 5 is a flowchart according to at least one embodiment of the present disclosure; and

[0043] Fig. 6 is a flowchart according to at least one embodiment of the present disclosure.DETAILED DESCRIPTION

[0044] It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example or embodiment, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, and / or may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the disclosed techniques according to different embodiments of the present disclosure). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a computing device and / or a device.

[0045] In one or more examples, the described methods, processes, and techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Alternatively or additionally, functions may be implemented using machine learning models, neural networks, artificial neural networks, or combinations thereof (alone or in combination with instructions). Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., random-access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0046] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i7 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Cortex Mx; Apple A10 or 10X Fusion processors; Apple Al l, Al 2, A12X, A12Z, or Al 3 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000- series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0047] Before any embodiments of the disclosure are explained in detail, it is to be understood that the disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Further, the present disclosure may use examples to illustrate one or more aspects thereof. Unless explicitly stated otherwise, the use or listing of one or more examples (which may be denoted by “for example,” “by way of example,” “e.g.,” “such as,” or similar language) is not intended to and does not limit the scope of the present disclosure.

[0048] Evoked compound action potentials (ECAPs) are valuable for providing electrophysiologic insight into neural tissue excited through a variety of means (e.g., electrical, mechanical, and ultrasound). More specifically, spinal ECAPs may be used as part of a closed- loop spinal cord stimulator for spinal cord stimulation (SCS) to maintain consistent neural activation as the spacing between the stimulating electrodes and the cord varies with patient movement. The ECAP amplitude grows as more neural tissue is activated, and vice versa. These changes in ECAP amplitude may be used as a control signal to adjust the stimulator output to compensate for variability in neural activation.

[0049] ECAPs, however, may only manifest when the stimulation is perceptible to the patient. With spinal ECAPs, for instance, the ECAP begins to manifest near the patient’s perceptual threshold. This may limit sub-perception therapeutic options for patients receiving ECAP- controlled, closed-loop spinal cord stimulation. Further, the stimulation pulse used to elicit the ECAP may result in stimulation artifact. Stimulation artifact is electrical noise that can interfere with the ability to accurately resolve the ECAP.

[0050] An option for closed-loop SCS is to use a control signal other than the ECAP to continuously assess spacing between the stimulation lead and the spinal cord. For example, nearinfrared reflectometry (NIR) and ultrasound may be used as the control signal as both approaches can (1) provide for high resolution measurement of spacing changes and (2) are not encumbered by SA like ECAP measurements. While these methods may correlate with the ECAP, however, they are not a direct measure of neural activation. Further, they may require extensive or complex calibration to provide clinically relevant information. Thus, in at least one embodiment of the present disclosure, systems and methods for providing both ECAPs and either ultrasound or NIR to enable biologically calibrated, sub-perception, stimulation artifact-free closed-loop control are provided. In such systems or methods ECAPs and an alternative method (such as ultrasound or NIR) are used to enable a hybrid assessment of coupling between neural tissue and the stimulation source (such as a lead body connected to an implantable neurostimulator).

[0051] Calibration of the device used in the systems or methods may be done once at initial calibration, or as triggered by a calibration event such as, for example:

[0052] After a certain period of time: this may be once every day, once every hour, once every minute, once every second, once every 100 milliseconds, or once every 10 milliseconds;

[0053] With respect to a number of stimulation pulses delivered: this may be after about 10 million stimulation pulses, about 1 million stimulation pulses, about 100,000 stimulation pulses, about 10,000 stimulation pulses, about 1,000 stimulation pulses, about 100 pulses, about 10 pulses, about 5 pulses, or after every other stimulation pulse;

[0054] In response to a physician or clinician request; and / or

[0055] In response to a change in activity, posture, or biochemical state.

[0056] The frequency of the calibration may also change dynamically. For instance, if any aspect of the ECAP (such as the amplitude, area under the curve, latency, number of peaks / troughs, spectral content, or rise / fall time) changes by more than 50%, about 40%, about 30%, about 20%, about 10%, about 5%, about 2% or about 1%, a more frequent calibration can be scheduled before returning to the default state.

[0057] Calibration may include increasing the stimulation until a desired ECAP is detected. This may include instructing the user to hold a particular position or avoiding certain activities to limit stimulation artifact. The alternative method is then enabled, and the output of the alternative method is used as a setpoint. The stimulation amplitude may then be reduced to a percentage of the amplitude (e.g., 50%) used during calibration. Closed-loop stimulation is then enabled but the output of the alternative method (here, NIR or US) — instead of the ECAP — is used as a control signal to servo the stimulation amplitude. Recalibration can occur when desired as described above.

[0058] Embodiments of the present disclosure beneficially enable a hybrid assessment of an effectiveness of stimulation delivered to a user (e.g., a patient). Embodiments of the present disclosure also beneficially enable adjusting therapy-providing devices based on ECAP measurements and / or data from another source such as, for example, a sensor (e.g., an ultrasound sensor, a NIR sensor, ect.). Embodiments of the present disclosure further beneficially improve patient comfort by adjusting the parameters associated with therapy-providing devices based on one or more sources of data.

[0059] Turning to Figs. 1-2, diagrams of aspects of a system 100 according to at least one embodiment of the present disclosure are shown. The system 100 may be used to provide electric signals to a patient and / or carry out one or more other aspects of one or more of the methods disclosed herein. For example, the system 100 may include at least a device 102 (which may be, for example, a close-loop spinal cord stimulation) that is capable of providing a stimulation tothe spinal cord 108 of the patient and / or to one or more nerve endings for a patient. In some examples, the device 102 may be referred to as a close-loop spinal cord stimulation, a pulse generator, an implantable neural stimulator, an internal neural stimulator, or the like, which may be implantable in some embodiments. More specifically, the device 102 may be configured to generate a current or electrical signal, such as a signal capable of stimulating one or more ECAPs or ECAP responses in the spinal cord 108 or from one or more nerves. Additionally, the system 100 may include one or more leads 104 (e.g., electrical leads) that provide a connection between the device 102 and the spinal cord or nerves of the patient for enabling, for example, stimulation. In some embodiments, the leads 104 may be implanted wholly or partially within the patient. The leads 104 may be, for example, paddle leads and / or percutaneous leads.

[0060] Neurostimulation techniques (e.g., technologies that act directly upon nerves of a patient, such as the alteration, or “modulation,” of nerve activity by delivering electrical impulses directly to a target area) may be used for assisting in treatments for different diseases, disorders, or ailments (e.g., chronic pain) of a patient. As discussed herein, neuromodulation techniques may be used to relieve chronic pain. Additionally or alternatively, neuromodulation techniques may be used to stimulate or prevent other neurological signals from traveling to or from the patient’s brain for the purposes of assisting with patient treatment. In some embodiments, the device 102 may provide electrical stimulation of the spinal cord 108 of the patient (or one or more nerves therein) to relieve chronic pain.

[0061] In some embodiments, the one or more leads 104 may include a first lead 104A disposed on or connected to a first side of the spinal cord 108 of the patient and a second lead 104B disposed on or connected to a second side of the spinal cord 108 of the patient. For example, the first lead 104A may be connected to the righthand side of the spinal cord 108, while the second lead 104B may be connected to the lefthand side of the spinal cord 108. However, the position and / or orientation of each lead relative to the spinal cord 108 may vary depending on, for example, the type of treatment, the type of lead, combinations thereof, and the like. In another example, the first lead 104A and the second lead 104B may overlap one another, and may be placed proximate one another on the dorsal side of the spinal cord 108 close to a midline of the spinal cord 108. In some examples, the first lead 104A and the second lead 104B may both be placed on the midline of the spinal cord 108, where one of the leads 104 is cranial (e.g., anterior or nearer the head of the patient) and the other of the leads 104 is caudal (e.g., posterioror nearer the tail of the patient). Additionally or alternatively, the first lead 104A and the second lead 104B may both be placed on one side of the midline of the spinal cord 108.

[0062] In other embodiments, the one or more leads 104 may include at least the first lead 104A and the second lead 104B connected to respective vagal trunks (e.g., different trunks of the vagus nerve) or to other respective nerves in a patient. For example, the first lead 104 A may be connected to a first vagal trunk of the patient (e.g., the anterior sub diaphragmatic vagal trunk at the hepatic branching point of the vagus nerve) and the second lead 104B may be connected to a second vagal trunk of the patient (e.g., the posterior sub diaphragmatic vagal trunk at the celiac branching point of the vagus nerve). The first lead 104A and / or the second lead 104B may be configured to provide an electrical stimulation signal from the device 102 to the respective first and / or second vagal trunk. The connection of the leads 104 to the respective vagal trunk (or other nerves) of the patient may permit the device 102 to measure and / or stimulate one or more ECAPs in the patient based on the provided electrical stimulation from the device 102.

[0063] In some examples, the leads 104 may provide the electrical signals to the respective vagal trunks via electrodes or electrode devices that extend from the leads 104 and connect to the vagal trunks (e.g., sutured in place, wrapped around the nerves of the vagal trunks, etc.). In some examples, the leads 104 may be referenced as cuff electrodes or may otherwise include cuff electrodes (e.g., at an end of the leads 104 not connected or plugged into the device 102).

[0064] In other examples, the leads 104 may be or comprise linear spinal cord stimulation (SCS) leads capable of delivering one or more stimulation signals to the spinal cord 108, as discussed in further detail below. The leads 104 may comprise a plurality of electrodes disposed along the length of the lead, such that the leads 104 contact the spinal cord 108 at multiple points along a length of the spinal cord 108. A first set of the electrodes on each lead may pass an electrical signal into the spinal cord 108, while a second set of the electrodes on each lead may sense one or more signals generated in response by the spinal cord 108. In one embodiment, the electrodes may be able to sense, measure, or otherwise collect data related to ECAPs (e.g., ECAP waveforms).

[0065] Fig. 2 depicts the device 102 and the leads 104 connected to the spinal cord 108 of the patient, the leads 104 including one or more electrodes 208, 210 that receive a current or other stimulant instructions from the device 102 (e.g., via the leads 104). In some examples, the electrodes 208, 210 may each include a body and a plurality of electrodes 208A-208D, 210A-21 OD that are disposed on respective first and second sides 204A, 204B of the spinal cord 108, where the plurality of electrodes 208A-208D, 210A-210D are configured to apply the current generated by the device 102 to the spinal cord 108. It will be appreciated that in other embodiments or examples, the leads 104 may include any number of electrodes. As shown, a first electrode 208 may be configured for placement on the spinal cord 108 to apply a current to the spinal cord 108 (e.g., carried via a first lead 104A and emitted from one or more of the electrodes 208A-208D), and a second electrode 210 may also be configured for placement on the spinal cord 108 to apply a current to the spinal cord (e.g., carried via a second lead 104B and emitted from one or more of the electrodes 210A-210D). In some examples, the electrodes 208, 210 may be referred to as cuff electrodes.

[0066] The application of current to the spinal cord 108 may stimulate an ECAP in the spinal cord or nerve of the patient, and data or information associated with the ECAP may be captured using, for example, one or more sensors, or the one or more of the electrodes 208A-208D, 210A- 210D. For example, one or more of the electrodes 208A-208D, 210A-210D may generate an electric signal that stimulates the spinal cord 108. The stimulation may cause one or more ECAP responses, which may be sensed, detected, and / or measured by the electrodes 208A-208D, 210A- 210D that were not used to stimulate the spinal cord. In some embodiments, the electrodes 208A-208D may stimulate the spinal cord 108, while the electrodes 210A-210D sense the ECAP response. In other embodiments, a first set of electrodes (e.g., the electrodes 208 A, 208B, 210A, 210B) may stimulate the spinal cord 108, while a second set of electrodes (e.g., the electrodes 208C, 208D, 210C, 210D) may measure the spinal cord 108 response, including capturing ECAP waveform data.

[0067] In some embodiments one or more leads 104 may include a sensor 212 configured to measure a distance between the lead 104 and the spinal cord 108 (or any target anatomical element). As shown in the illustrated device, the sensor 212 may be disposed at an end of the lead 104A. It will be appreciated that in other embodiments the sensor 212 may be disposed on any portion of the lead 104A or may be a component separate from the lead 104A. The sensor 212 can include one sensor, two sensors, or more than two sensors. The sensor 212 may comprise, for example, a near-infrared reflectometry (NIR) sensor, an ultrasound sensor, or any sensor capable of measuring the distance between the lead 104 and a target anatomical element.

[0068] The measured distance is beneficial in cases where, for example, an ECAP cannot be measured (e.g., the stimulation delivered is below a perceptual threshold) or stimulation artifacts may obscure the ECAP. In such instances, the measured distance is not affected by the stimulation artifacts and can be recorded below the perceptual threshold. Thus, in some embodiments, the measured distance may be used to adjust one or more parameters of the device 102 when the stimulation is below a predetermined threshold (and thus, the ECAP cannot be measured or may have stimulation artifacts) and may use the ECAP or a combination of the ECAP and the measured distance to adjust the one or more parameters when the stimulation is above the predetermined threshold (and thus, the ECAP can be measured with little or no stimulation artifact).

[0069] The measured distance can be used to control the device 104 by adjusting the one or more parameters of the device 104 based on a difference between the measured distance and an initial distance measured during, for example, calibration of the device 104. For example, if the measured distance is greater than the initial distance and results in a positive distance (indicating that the lead 104 is spaced further away from the spinal cord 108 than desired), then one or more parameters of the device 104 may be adjusted to increase the stimulation. Conversely, if the measured distance is less than the initial distance and results in a negative distance (indicating that the lead 104 is spaced closer to the spinal cord 108 than desired), then one or more parameters of the device 102 may be adjusted to decrease the stimulation.

[0070] The system 100 or similar systems may be used, for example, to carry out one or more aspects of the methods 400, 500, or 600 described herein. The system 100 or similar systems may also be used for other purposes. It will be appreciated that the human body has many nerves and the stimulation and / or measurement described herein may be applied to one or more nerves, which may reside at any location of a patient (e.g., lumbar, thoracic, etc.). Further, the use of the leads 104 to stimulate and / or measure ECAPs may occur with different portions of the nervous system. For example, the leads 104 may be connected to one or more of nerve endings in the spinal cord, the brain or portions thereof, combinations thereof, and the like.

[0071] Additionally, while not shown in Figs. 1-2, the system 100 may include one or more processors (e.g., one or more DSPs, general purpose microprocessors, graphics processing units, ASICs, FPGAs, or other equivalent integrated or discrete logic circuitry) shown and described in Fig. 3 that are programmed to carry out one or more aspects of the present disclosure. In someexamples, the one or more processors may include a memory or may be otherwise configured to perform the aspects of the present disclosure. For example, the one or more processors may provide instructions to the device 102 or other components of the system 100 not explicitly shown or described with reference to Fig. 1 for generating stimulation of one or more nerves, measuring ECAPs, measuring a distance between the lead 104, 104A, 104B and a target anatomical element, and / or adjusting provided therapies based on the measured ECAPs, the measured distance, or a combination thereof, as described herein. In some examples, the one or more processors may be part of the device 102 or part of a control unit for the system 100 (e.g., where the control unit is in communication with the device 102 and / or other components of the system 100).

[0072] Turning to Fig. 3, a block diagram of a system 300 according to at least one embodiment of the present disclosure is shown. The system 300 may be used with the system 100 or components thereof, and / or may carry out one or more other aspects of one or more of the methods disclosed herein. The system 300 comprises the device 102, a computing device 302, a database 330, and / or a cloud or other cloud network 334. Systems according to other embodiments of the present disclosure may comprise more or fewer components than the system 300. For example, the system 300 may not include one or more components of the computing device 302, the database 330, and / or the cloud network 334. While the computing device 302 of the system 300 is illustrated as being in communication with the device 102, it is to be understood that the computing device 302 may be disposed as a sub-component within the device 102, or may alternatively be an external device that communicates with the device 102 using, for example, a communication interface 308, or through the cloud 334 or other network. In some embodiments, the device 102 may include any one or more components of the system 300 including, but not limited to, the computing device 302, the processor 304, the memory 306, the communication interface 308, the database 330, a data model 332, combinations thereof, and the like.

[0073] The device 102 may comprise the leads 104, the electrodes 208, 210, and the sensor(s) 212. As previously described, the leads 104 and the electrodes 208, 210 may be configured to apply the current to an anatomical element (e.g., the spinal cord, one or more nerves, etc.). The device 102 may communicate with the computing device 302 to receive instructions such as instructions for applying a current to the anatomical element. The device 102 may also providedata (such as data received from or measured by the electrodes 208, 210 and / or measured by the sensors 212), which may be used to calibrate and / or control the device 102.

[0074] As previously described, the sensor(s) 212 are configured to measure a distance between the lead 104 and a target anatomical element such as, for example, a spinal cord. The sensor 212 may be disposed at an end of the lead 104. It will be appreciated that in other embodiments the sensor 212 may be disposed on any portion of the lead 104 or may be a component separate from the lead 104. The sensor 212 can include one sensor, two sensors, or more than two sensors. The sensor may comprise, for example, a NIR sensor, an ultrasound sensor, or any sensor capable of measuring the distance between the lead 104 and a target anatomical element.

[0075] The computing device 302 comprises a processor 304, a memory 306, a communication interface 308, and a user interface 310. Computing devices according to other embodiments of the present disclosure may comprise more or fewer components than the computing device 302.

[0076] The processor 304 of the computing device 302 may be any processor described herein or any similar processor. The processor 304 may be configured to execute instructions stored in the memory 306, which instructions may cause the processor 304 to carry out one or more computing steps utilizing or based on data received from the device 102, the database 330, and / or the cloud network 334.

[0077] The memory 306 may be or comprise RAM, DRAM, SDRAM, other solid-state memory, any memory described herein, or any other tangible, non-transitory memory for storing computer-readable data and / or instructions. The memory 306 may store information or data useful for completing, for example, one or more steps of the method 500 described herein, or of any other methods. The memory 306 may store, for example, instructions and / or machine learning models (e.g., neural networks) that support one or more functions of the device 102. For instance, the memory 306 may store content (e.g., instructions and / or machine learning models) that, when executed by the processor 304, sensor processing 322, calibration 324, and / or parameter adjustment(s) 326.

[0078] The sensor processing 322 enables the processor 104 to process sensor data received from, for example, a sensor such as the sensor 212. The sensor data may be processed to obtain, for example, a distance between the sensor 212 (disposed on or integrated with, for example, a lead such as the lead 104) and a target anatomical element. Such information may be used todetermine if the lead 104 has moved closer to or further away from the target anatomical element and whether the stimulation generated by the device 102 needs to be increased or decreased to supplement for the changing distance between the lead 104 and the target anatomical element.

[0079] The calibration 324 enables the processor 104 to calibrate the device 102 using, for example, sensor data and / or stimulation data. The sensor data may be sensor data as processed from the sensor processing 322 and / or may be received directly from the sensor 212. The stimulation data may include, for example, ECAPs and / or parameters of the stimulation delivered. The calibration 324 may include correlating the sensor data and the stimulation data such that the sensor data and / or the stimulation data can be used control or adjust the device 102. For example, in some embodiments the sensor data and the stimulation data may be used separately or together to control or adjust the device 102. In other instances, the correlation may enable the processor to determine whether to use the sensor data, the stimulation data, or a combination thereof to control or adjust the device 102 based on a predetermined threshold (e.g., a perceptual threshold).

[0080] The parameter adjustment(s) 326 enables the processor 104 to control or adjust one or more parameters related to stimulation of the device 102. The one or more parameters may be adjusted based on the sensor data and / or the stimulation data. For example, the sensor data may indicate that the lead 104 has moved away from a target anatomical element and is thus, less effective. The parameter adjustment(s) 326 may enable the processor 104 to adjust the one or more parameters to increase the stimulation accordingly. In another example, the stimulation data may include an ECAP with some stimulation artifact. In such examples, the sensor data can be used with the stimulation data as, for example, supplemental data to adjust the one or more parameters accordingly. For example, the ECAP may indicate overstimulation and the sensor data may be used to confirm that the lead has moved closer to the target anatomical element - thus also indicating and confirming overstimulation.

[0081] Content stored in the memory 306, if provided as in instruction, may, in some embodiments, be organized into one or more applications, modules, packages, layers, or engines. Alternatively or additionally, the memory 306 may store other types of content or data (e.g., machine learning models, artificial neural networks, deep neural networks, etc.) that can be processed by the processor 304 to carry out the various method and features described herein. For example, the memory 306 may store one or more parameters of the device 104 and / or one ormore predetermined thresholds which may be used to, for example, determine which sets of data to use to adjust the one or more parameters. Thus, although various contents of memory 306 may be described as instructions, it should be appreciated that functionality described herein can be achieved through use of instructions, algorithms, and / or machine learning models. The data, algorithms, and / or instructions may cause the processor 304 to manipulate data stored in the memory 306 and / or received from or via the device 102, the database 330, and / or the cloud network 334.

[0082] The computing device 302 may also comprise a communication interface 308. The communication interface 308 may be used for receiving data (for example, data from the device 102) or other information from an external source (such as the device 102, the database 330, the cloud network 334, and / or any other system or component not part of the system 300), and / or for transmitting instructions, images, or other information to an external system or device (e.g., another computing device 302, the device 102, the database 330, the cloud network 334, and / or any other system or component not part of the system 300). The communication interface 308 may comprise one or more wired interfaces (e.g., a USB port, an Ethernet port, a Firewire port) and / or one or more wireless transceivers or interfaces (configured, for example, to transmit and / or receive information via one or more wireless communication protocols such as 602.11a / b / g / n, Bluetooth, NFC, ZigBee, and so forth). In some embodiments, the communication interface 308 may be useful for enabling the computing device 302 to communicate with one or more other processors 304 or computing devices 302, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason.

[0083] The computing device 302 may also comprise one or more user interfaces 310. The user interface 310 may be or comprise a keyboard, mouse, trackball, monitor, television, screen, touchscreen, and / or any other device for receiving information from a user and / or for providing information to a user. The user interface 310 may be used, for example, to receive a user selection or other user input regarding any step of any method described herein. Notwithstanding the foregoing, any required input for any step of any method described herein may be generated automatically by the system 300 (e.g., by the processor 304 or another component of the system 300) or received by the system 300 from a source external to the system 300. In some embodiments, the user interface 310 may be useful to allow a surgeon or other user to modify instructions to be executed by the processor 304 according to one or more embodiments of thepresent disclosure, and / or to modify or adjust a setting of other information displayed on the user interface 310 or corresponding thereto.

[0084] Although the user interface 310 is shown as part of the computing device 302, in some embodiments, the computing device 302 may utilize a user interface 310 that is housed separately from one or more remaining components of the computing device 302. In some embodiments, the user interface 310 may be located proximate one or more other components of the computing device 302, while in other embodiments, the user interface 310 may be located remotely from one or more other components of the computing device 302.

[0085] The database 330 may store information such as patient data, lead parameters, ECAP waveform data or similar data, electrode parameters, threshold values, distance values, etc. The database 330 may be configured to provide any such information to the computing device 302 or to any other device of the system 300 or external to the system 300, whether directly or via the cloud network 334. In some embodiments, the database 330 may be or comprise part of a hospital image storage system, such as a picture archiving and communication system (PACS), a health information system (HIS), and / or another system for collecting, storing, managing, and / or transmitting electronic medical records.

[0086] The cloud network 334 may be or represent the Internet or any other wide area network. The computing device 302 may be connected to the cloud network 334 via the communication interface 308, using a wired connection, a wireless connection, or both. In some embodiments, the computing device 302 may communicate with the database 330 and / or an external device (e.g., a computing device) via the cloud network 334.

[0087] The system 300 or similar systems may be used, for example, to carry out one or more aspects of the methods 400, 500, and / or 600 described herein. The system 300 or similar systems may also be used for other purposes.

[0088] Fig. 4 depicts a method 400 that may be used, for example, to calibrate a device such as the device 102.

[0089] One or more steps of the method 400 may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 304 of the computing device 302 described above. The at least one processor may be part of a device (such as a device 102). A processor other than any processor described herein may also be used to execute the method 400. The at least one processor may perform stepsof the method 400 by executing elements stored in a memory such as the memory 306. The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 400. One or more portions of a method 400 may be performed by the processor executing any of the contents of memory, such as sensor processing 322, calibration 324, and / or parameter adjustment(s) 326.

[0090] The method 400 comprises programming a device with one or more parameters (step 404). The device may be the same as or similar to the device 102 and may be configured to generate a stimulation. The device may be connected to one or more leads such as the leads 104, 104 A, 104B through which the stimulation is delivered to a target anatomical element. The target anatomical element may be, for example, a spinal cord of a user. The device may be programmed with the one or more parameters as an initial or base set of parameters. The one or more parameters may be a base or standard set of parameters, may be initially tailored to the user, or may be based on other prior users similar to the user.

[0091] The method 400 also comprises causing the device to deliver a stimulation (step 408). The device may deliver the stimulation based on the one or more parameters. During calibration, the device may increase the stimulation to a level where a desired ECAP response is detected. During such calibration, the user may be instructed to maintain or hold a particular position and / or avoid activities that may induce stimulation artifacts in the ECAP.

[0092] The method 400 also comprises receiving stimulation data corresponding to the stimulation received by the user (step 412). The stimulation data may include, for example, an ECAP and / or measured characteristics of the stimulation data (e.g., ECAP amplitude, area under a stimulation curve, latency, number of peaks / troughs, spectral content, or rise / fall time).

[0093] The method 400 also comprises receiving sensor data (step 416). The sensor data may be obtained from a sensor such as the sensor 220. In some embodiments the sensor data may be processed by a processor such as the processor 304 using a sensor processing such as the sensor processing 322. The sensor data may be measured and received when the stimulation is delivered. In some embodiments, the sensor data may be continuously measured and received during neuromodulation therapies.

[0094] The sensor may be, for example, an ultrasound sensor or a NIR sensor. In other embodiments, the sensor may be any sensor capable of measuring a distance between the sensor and a target anatomical element. The sensor is beneficially unaffected by stimulation artifactsthat may obscure the ECAP. Thus, the sensor can provide sensor data helpful in controlling or adjusting the device when the ECAP is otherwise unavailable, or can be used with the ECAP to adjust the device.

[0095] The method 400 also comprises calibrating the device (step 420). The device may, in some instances, be calibrated by the processor using a calibration such as the calibration 324. Calibrating the device may include, for example, correlating the sensor data and the stimulation data. More specifically, calibrating the device may include measuring an output comprising information corresponding to an initial distance between the lead and the target anatomical element and correlating the initial distance with the stimulation data. The output may include, for example, a voltage, current, and / or capacitance that can be used to determine or correlate to a distance between the lead and the target anatomical element. As will be discussed in more detail below, a difference in the initial distance and a measured distance may be used to adjust the one or more parameters of the device.

[0096] The method 400 also comprises detecting a recalibration event (step 424). The recalibration event may include one or more of the following:

[0097] A certain period of time has passed: this may be once every day, once every hour, once every minute, once every second, once every 100 milliseconds, or once every 10 milliseconds;

[0098] With respect to a number of stimulation pulses delivered: this may be after about 10 million stimulation pulses, about 1 million stimulation pulses, about 100,000 stimulation pulses, about 10,000 stimulation pulses, about 1,000 stimulation pulses, about 100 pulses, about 10 pulses, about 5 pulses, or after every other stimulation pulse;

[0099] In response to a physician or clinician request; and / or

[0100] In response to a change in activity, posture, or biochemical state.

[0101] The frequency of the calibration may also change dynamically. For instance, if any aspect of the ECAP (such as the amplitude, area under the curve, latency, number of peaks / troughs, spectral content, or rise / fall time) changes by more than 50%, about 40%, about 30%, about 20%, about 10%, about 5%, about 2% or about 1%, a more frequent calibration can be scheduled before returning to the default state.

[0102] It will be appreciated that the recalibration event may include any event or trigger resulting in recalibration of the device.

[0103] The method 400 also comprises recalibrating the device (step 428). Recalibrating the device may include repeating any one or more of the steps 404, 408, 412, 416, and / or 420. For example, recalibrating the device may include repeating the steps 408-420 and using the current set of parameters (whether adjusted from the initial one or more parameters or not). In another example, recalibrating the device may include repeating the steps 404-420 and use the same initial one or more parameters used in the initial calibration.

[0104] It will be appreciated that in some embodiments, the method 400 or any step(s) of the method 400 may repeat. For example, recalibration event(s) may be detected multiple times and the device may be subsequently recalibrated multiple times. In other words, in some embodiments, the steps 424 and 428 may be repeated up to a certain amount of time or quantity or indefinitely as indicated by the dashed line.

[0105] The present disclosure encompasses embodiments of the method 400 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0106] Fig. 5 depicts a method 500 that may be used, for example, to adjust or control one or more stimulation parameters of a device based on a hybrid assessment.

[0107] One or more steps of the method 500 may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 304 of the computing device 302 described above. The at least one processor may be part of a device (such as a device 102). A processor other than any processor described herein may also be used to execute the method 500. The at least one processor may perform steps of the method 500 by executing elements stored in a memory such as the memory 306. The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 500. One or more portions of a method 500 may be performed by the processor executing any of the contents of memory, such as sensor processing 322, calibration 324, and / or parameter adjustment(s) 326.

[0108] The method 500 comprises causing a device to generate and deliver stimulation to a user (step 502). The step 502 may be the same as or similar to the step 408 of the method 400 above. The device may be the same as or similar to the device 102 and may be configured to generate a stimulation. The device may be connected to one or more leads such as the leads 104, 104 A, 104B through which the stimulation is delivered to a target anatomical element. The targetanatomical element may be, for example, a spinal cord of a user. In some embodiments, the device may be used in a closed-loop stimulation in which feedback as a result of the stimulation is used to adjust one or more parameters of the device, though it will be appreciated that the device can also be used in any type of stimulation in other instances. The device may be calibrated as described in the method 400 above.

[0109] The method 500 also comprises receiving stimulation data corresponding to stimulation delivered to the user (step 504). The step 504 may be the same as or similar to the step 412 of the method described above.

[0110] The method 500 also comprises receiving sensor data (step 508). The step 508 may be the same as or similar to the step 416 of the method described above.

[0111] The method 500 also comprises adjusting one or more parameters of the device based on the sensor data and / or the stimulation data (step 512). The one or more parameters may be adjusted by a processor such as the processor 304 using a parameter adjustment such as the parameter adjustment(s) 326. The one or more parameters may be adjusted based on the sensor data, the stimulation data, or a combination thereof. In other words, the one or more parameters may be adjusted based on sensor data, stimulation data, or both the sensor data and the stimulation data.

[0112] In some embodiments, the sensor data may enable adjustments to the one or more parameters of the device when stimulation data such as ECAPs cannot be recorded (e.g., the stimulation is at a level at which the ECAP cannot be recorded or measured) or are obscured by stimulation artifacts. In other embodiments, the stimulation data may be used to adjust the one or more parameters of the device when the stimulation data is free of stimulation artifacts and is above the perception threshold (and thus, detectable). It will be appreciated that in still other embodiments, the sensor data and the stimulation data may be used together to adjust the one or more parameters. For example, the sensor data may be used to confirm information obtained from the stimulation data. More specifically, the sensor data can be used in conjunction with ECAP(s) to supplement ECAPs that are partially obscured or otherwise affected by stimulation artifacts. For example, the ECAP may indicate overstimulation and the sensor data may be used to confirm that the lead has moved closer to the target anatomical element - thus also indicating and confirming overstimulation.

[0113] The method 500 also comprises detecting a recalibration event (step 516). The step 516 may be the same as or similar to the step 424 of the method 400 described above.

[0114] The method 500 also comprises recalibrating the device (step 520). The step 520 may be the same as or similar to the step 428 of the method 400 described above.

[0115] In some embodiments, the method 500 or any step(s) of the method 500 may repeat. For example, the steps 502, 504, 508, and 512 may be repeated multiple times to adjust the one or more parameters of the device as needed. For example, the steps 502, 504, 508, and 512 may repeat when the user moves from a standing position to a sitting position or vice versa. In another example, the steps 516 and 520 may be repeated as recalibration events are detected or occur.

[0116] The present disclosure encompasses embodiments of the method 500 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0117] Fig. 6 depicts a method 600 that may be used, for example, to adjust or control one or more stimulation parameters of a device based on a hybrid assessment.

[0118] One or more steps of the method 600 may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 304 of the computing device 302 described above. The at least one processor may be part of a device (such as a device 102). A processor other than any processor described herein may also be used to execute the method 600. The at least one processor may perform steps of the method 600 by executing elements stored in a memory such as the memory 306. The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 600. One or more portions of a method 600 may be performed by the processor executing any of the contents of memory, such as sensor processing 322, calibration 324, and / or stimulation adjustment 326.

[0119] The method 600 comprises causing a device to generate and deliver stimulation to a user (step 602). The step 602 may be the same as or similar to the step 408 of the method 400 described above. The device may be the same as or similar to the device 102 and may be configured to generate a stimulation. The device may be connected to one or more leads such as the leads 104, 104A, 104B through which the stimulation is delivered to a target anatomical element. The target anatomical element may be, for example, a spinal cord of a user. In some embodiments, the device may be used in a closed-loop stimulation in which feedback as a resultof the stimulation is used to adjust one or more parameters of the device, though it will be appreciated that the device can also be used in open stimulation in other instances. The device may be calibrated as described in the method 400 above.

[0120] The method 600 also comprises receiving stimulation data corresponding to stimulation delivered to a user (step 604). The step 604 may be the same as or similar to the step 412 of the method 400 described above.

[0121] The method 600 also comprises receiving sensor data (step 608). The step 608 may be the same as or similar to the step 416 of the method 400 described above.

[0122] The method 600 also comprises determining whether the stimulation meets or exceeds a predetermined threshold (step 612). The predetermined threshold may correspond to a level of stimulation where an ECAP can be detected (e.g., a perceptual threshold). At such level of stimulation and above, the ECAP may be more easily and reliably detectable and may be less affected by stimulation artifacts. Thus, it may be beneficial to use the ECAP or other stimulation data to adjust the device in such instances. Similarly, below the level of stimulation, the ECAP may not be detectable or may be obscured by stimulation artifacts. Thus, it may be beneficial to use the sensor data (which is detectable and free of stimulation artifacts) to adjust the device in such instances.

[0123] The method 600 also comprises adjusting one or more parameter(s) of the device based on the sensor data when the stimulation is at or below the predetermined threshold (step 616). The step 616 may be the same as or similar to the step 512 of the method 500 above except that sensor data is primarily used or the sensor data is used alone to adjust the one or more parameters of the device.

[0124] The one or more parameters may be adjusted by a processor such as the processor 304 using a parameter adjustment such as the parameter adjustment(s) 326. The one or more parameters may be adjusted primarily based on sensor data or based on the sensor data alone. More specifically, the sensor data may indicate that the lead has moved away from a target anatomical element and is thus, less effective. In such examples, one or more parameters may be adjusted to increase the stimulation accordingly. Similarly, the sensor data may indicate that the lead has moved towards the target anatomical element and is thus, overstimulating the target anatomical element. In such examples, one or more parameters may be adjusted to decrease the stimulation accordingly.

[0125] More specifically, a measured distance between the sensor (and thus, the lead) and the target anatomical element may be compared to an initial distance between the sensor and the target anatomical element measured during calibration. Such difference may indicate whether the lead has migrated or moved away from or towards the anatomical element and an approximate distance the lead has moved relative to the target anatomical element. Thus, the one or more parameters can be adjusted based on movement of the lead relative to the target anatomical element.

[0126] The method 600 also comprises adjusting one or more parameter(s) of the device based on the stimulation data when the stimulation is at or above the predetermined threshold (step 620). The step 620 may be the same as or similar to the step 512 of the method 500 above except that stimulation data is primarily used or the stimulation data is used alone to adjust the one or more parameters of the device.

[0127] The one or more parameters may be adjusted by a processor such as the processor 304 using a parameter adjustment such as the parameter adjustment(s) 326. The one or more parameters may be adjusted primarily based on stimulation data or based on the stimulation data alone. For example, the stimulation data (e.g., an ECAP) may indicate that the lead has moved away from a target anatomical element and is thus, less effective. In such examples, one or more parameters may be adjusted to increase the stimulation accordingly. Similarly, the stimulation data (e.g., an ECAP) may indicate that the lead has towards the target anatomical element and is thus, overstimulating the target anatomical element. In such examples, one or more parameters may be adjusted to decrease the stimulation accordingly. More specifically, the ECAP amplitude grows as more neural tissue is activated, and vice versa. These changes in ECAP amplitude may be used to adjust the one or more parameters of the device. It will be appreciated that in some embodiments, the sensor data may be used to supplement the stimulation data when adjusting the one or more parameters.

[0128] In some embodiments, the method 600 may repeat. For example, the steps 602, 604, 608, 612, and 616 may repeat when the stimulation is at or below the predetermined threshold. In another example, the steps 602, 604, 608, 612, and 620 may repeat when the stimulation is at or above the predetermined threshold.

[0129] The present disclosure encompasses embodiments of the method 600 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0130] The foregoing is not intended to limit the disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the disclosure are grouped together in one or more aspects, embodiments, and / or configurations for the purpose of streamlining the disclosure. The features of the aspects, embodiments, and / or configurations of the disclosure may be combined in alternate aspects, embodiments, and / or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects he in less than all features of a single foregoing disclosed aspect, embodiment, and / or configuration. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the disclosure.

[0131] Moreover, though the foregoing has included description of one or more aspects, embodiments, and / or configurations and certain variations and modifications, other variations, combinations, and modifications are within the scope of the disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, embodiments, and / or configurations to the extent permitted, including alternate, interchangeable and / or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and / or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.

[0132] The disclosure is further described in the following numbered examples.

[0133] Example 1. A system, comprising: a device configured to generate a stimulation; a lead configured to deliver the stimulation to a target anatomical region; a processor; and a memory capable of storing data thereon that, when processed by the processor, cause the processor to: program the device with one or more parameters; cause the device to deliver the stimulation; receive stimulation data corresponding to the stimulation received by the user; receive sensor data; and calibrate the device based on the stimulation data and the sensor data.

[0134] Example 2. The system of example 1, further comprising: a sensor configured to measure output corresponding to a distance between the lead and the target anatomical region and to yield the sensor data corresponding to the measured distance.

[0135] Example 3. The system of example 2, wherein calibrating the device includes measuring an output corresponding to an initial distance between the lead and the target anatomical element and correlating the initial distance with the stimulation data.

[0136] Example 4. The system of example 1, wherein the output comprises at least one of a voltage, current, or capacitance.

[0137] Example 5. The system of example 2, wherein the sensor comprises at least one of an ultrasound sensor or a near-infrared reflectometry sensor.

[0138] Example 6. The system of example 1, wherein the stimulation is generated to a level where a target evoked compound action potential (ECAP) is detected in the stimulation data.

[0139] Example 7. The system of example 1, wherein calibrating the device includes correlating the sensor data and the stimulation data.

[0140] Example 8. The system of example 1, wherein the data further causes the processor to: detect a recalibration event; and recalibrate the device when the recalibration event is detected.

[0141] Example 9. The system of example 8, wherein the recalibration event comprises at least one of a period of time has passed, a number of stimulations have been delivered, a user input has been received, a change in one or more parameters of an ECAP has occurred, or a change in user activity, user posture, or user biochemical state has occurred.

[0142] Example 10. A system, comprising: a device configured to generate a stimulation; a lead configured to deliver the stimulation to a target anatomical region; a processor; and a memory capable of storing data thereon that, when processed by the processor, cause the processor to: cause the pulse generator to generate the stimulation and deliver the stimulation to the target anatomical region via the lead; receive stimulation data corresponding to the stimulation delivered to the user; receive sensor data; and adjust one or more one or more parameters of the device based on the sensor data.

[0143] Example 11. The system of example 10, further comprising: a sensor configured to measure an output corresponding to a distance between the lead and the target anatomical region, the sensor configured to yield the sensor data.

[0144] Example 12. The system of example 11, wherein the one or more parameters are adjusted based on a difference between an output corresponding to an initial distance and an output corresponding to a detected distance.

[0145] Example 13. The system of example 12, wherein the output corresponding to the initial distance is determined during a calibration of the device.

[0146] Example 14. The system of example 11, wherein the sensor comprises at least one of an ultrasound sensor or a near-infrared reflectometry.

[0147] Example 15. The system of example 10, wherein the data further causes the processor to: detect a recalibration event; and recalibrate the device when the recalibration event is detected.

[0148] Example 16. The system of example 15, wherein the recalibration event comprises at least one of a period of time has passed, a number of stimulations have been delivered, a user input has been received, a change in one or more parameters of an ECAP has occurred, or a change in user activity, user posture, or user biochemical state has occurred.

[0149] Example 17. A system, comprising: a device configured to generate a stimulation; a lead configured to deliver the stimulation to a target anatomical region; a processor; and a memory capable of storing data thereon that, when processed by the processor, cause the processor to: cause the pulse generator to generate the stimulation and deliver the stimulation to the target anatomical region via the lead; receive stimulation data corresponding to the stimulation delivered to the user; receive sensor data; adjust one or more one or more parameters of the device based on the sensor data; and determine whether the stimulation meets or exceeds a predetermined threshold.

[0150] Example 18. The system of example 17, wherein the predetermined threshold corresponds to a level of the stimulation where an ECAP can be detected.

[0151] Example 19. The system of example 17, wherein the data further causes the processor to: adjust one or more parameters of the device based on the stimulation data when the stimulation is at or above the predetermined threshold.

[0152] Example 20. The system of example 19, wherein the stimulation data comprises an ECAP.

Claims

CLAIMSWhat is claimed is:

1. A system (100), comprising: a device (102) configured to generate a stimulation; a lead (104) configured to deliver the stimulation to a target anatomical region; a processor (304); and a memory (306) capable of storing data thereon that, when processed by the processor, cause the processor to: program the device with one or more parameters; cause the device to deliver the stimulation; receive stimulation data corresponding to the stimulation received by the user; receive sensor data; and calibrate the device based on the stimulation data and the sensor data.

2. The system of claim 1, further comprising: a sensor (212) configured to measure output corresponding to a distance between the lead and the target anatomical region and to yield the sensor data corresponding to the measured distance.

3. The system of claim 2, wherein calibrating the device includes measuring an output corresponding to an initial distance between the lead and the target anatomical element and correlating the initial distance with the stimulation data.

4. The system of claim 1, wherein the output comprises at least one of a voltage, current, or capacitance.

5. The system of claim 2, wherein the sensor comprises at least one of an ultrasound sensor or a near-infrared reflectometry sensor.

6. The system of claim 1 , wherein the stimulation is generated to a level where a target evoked compound action potential (ECAP) is detected in the stimulation data.

7. The system of claim 1, wherein calibrating the device includes correlating the sensor data and the stimulation data.

8. The system of claim 1, wherein the data further causes the processor to: detect a recalibration event; and recalibrate the device when the recalibration event is detected.

9. The system of claim 8, wherein the recalibration event comprises at least one of a period of time has passed, a number of stimulations have been delivered, a user input has been received, a change in one or more parameters of an ECAP has occurred, or a change in user activity, user posture, or user biochemical state has occurred.

10. A system (100), comprising: a device (102) configured to generate a stimulation; a lead (104) configured to deliver the stimulation to a target anatomical region; a processor (304); and a memory (306) capable of storing data thereon that, when processed by the processor, cause the processor to: cause the pulse generator to generate the stimulation and deliver the stimulation to the target anatomical region via the lead; receive stimulation data corresponding to the stimulation delivered to the user; receive sensor data; and adjust one or more one or more parameters of the device based on the sensor data.

11. The system of claim 10, further comprising: a sensor (212) configured to measure an output corresponding to a distance between the lead and the target anatomical region, the sensor configured to yield the sensor data.

12. The system of claim 11 , wherein the one or more parameters are adjusted based on a difference between an output corresponding to an initial distance and an output corresponding to a detected distance.

13. The system of claim 12, wherein the output corresponding to the initial distance is determined during a calibration of the device.

14. The system of claim 11, wherein the sensor comprises at least one of an ultrasound sensor or a near-infrared reflectometry.

15. The system of claim 10, wherein the data further causes the processor to: detect a recalibration event; and recalibrate the device when the recalibration event is detected.

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