Detecting signals with muscle activity using a neuromodulation system

Abstract

Systems and methods for informing a therapeutic procedure are provided. The systems and methods include receiving one or more signals having muscle activity over a duration of time and comparing the muscle activity throughout the duration of time. The systems and methods also include determining muscle activity quality based on the comparison.

Description

DETECTING SIGNALS WITH MUSCLE ACTIVITY USING A NEUROMODULATIONSYSTEMCROSS-REFERENCE TO RELATED APPLICATION(S)

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 625,651, filed January 26, 2024, which is incorporated herein by reference in its entirety.BACKGROUND

[0002] The present disclosure is generally directed to therapeutic neuromodulation, and relates more particularly to detecting signals with muscle activity for supporting the therapeutic neuromodulation.

[0003] Neuromodulation therapy may be carried out by sending an electrical signal generated by a device (e.g., a pulse generator) to a stimulation target (e.g., nerves, non-neuronal cells, etc.), which may provide a desired electrophysiologic, biochemical, or genetic response in the stimulation target. Neuromodulation therapy systems may be used to deliver electrical stimulation for providing chronic pain treatment, functional treatment, and / or rehabilitation to a patient. In some neuromodulation therapies (e.g., closed-loop neuromodulation therapies), one or more signals resulting from the neuromodulation may be recorded and the therapy may be adjusted based on the recorded signals.SUMMARY

[0004] Example aspects of the present disclosure include:

[0005] A system for informing a therapeutic procedure according to at least one embodiment of the present disclosure comprises a processor; and a memory storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals having muscle activity over a duration of time; compare the muscle activity throughout the duration of time; and determine muscle activity quality based on the comparison.

[0006] Any of the aspects herein, further comprising: a pulse generator configured to generate a therapeutic electrical signal; one or more leads in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes; and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

[0007] Any of the aspects herein, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

[0008] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: identify the muscle activity, ECAP, cardiac activity, or a combination thereof in the one or more signals.

[0009] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: determine the muscle activity quality falls outside of a predetermined threshold; and adjust one or more therapy parameters for applying the therapeutic electrical signal to the anatomical element based at least in part on determining the muscle activity quality falls outside of the predetermined threshold, or provide, via a user interface, an alert indicating that the muscle activity quality falls outside of the predetermined threshold.

[0010] Any of the aspects herein, wherein the one or more adjusted therapy parameters comprise an amplitude adjustment, adjustment of duty cycling, adjustment of cycling of high frequency or low frequency components independently, adjustment of frequency, adjustment of pulse width, adjustment of charge balancing strategy, adjustment of selection of the plurality of electrodes, or a combination thereof.

[0011] Any of the aspects herein, wherein the duration of time is at least one of one or more subseconds, one or more hours, one or more hours, one or more days, one or more weeks, one or more months, or one or more years.

[0012] Any of the aspects herein, wherein the comparison comprises comparing at least one of amplitude, power, coherence, fatigue, or longevity of activation over the duration of time.

[0013] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: receive one or more sensor signals from at least one sensor over a duration of time, wherein determining the muscle activity quality is also based on the one or more sensor signals.

[0014] A system for informing a therapeutic procedure according to at least one embodiment of the present disclosure comprises a processor; and a memory storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals with muscle activity of a patient for a first time period; adjust one or more parameters of a stimulation therapy; receive one or more signals with the muscle activity of the patient for a second time period; compare the muscle activity from the first time period with the muscle activity from the second time period; and determine muscle activity quality based on the comparison.

[0015] Any of the aspects herein, a pulse generator configured to generate a therapeutic electrical signal; one or more leads in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes; and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

[0016] Any of the aspects herein, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

[0017] Any of the aspects herein, wherein electrodes of the plurality of electrodes configured to apply the electrical signal comprise stimulation electrodes and electrodes of the plurality of electrodes configured to measure the one or more signals comprise recording electrodes.

[0018] Any of the aspects herein, wherein adjusting the one or more stimulation parameters comprises adjusting a position of the one or more leads.

[0019] A system for informing a therapeutic procedure according to at least one embodiment of the present disclosure comprises a processor; and a memory storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals with muscle activity of a patient for a first time period; determine one or more activities based on the one or more signals; generate a plurality of templates, each template corresponding to an activity of the one or more activities; receive one or more signals with the muscle activity of the patient for a second time period; and identify at least one activity in the one or more signals at the second time period based on the plurality of templates.

[0020] Any of the aspects herein, further comprising: a pulse generator configured to generate a therapeutic electrical signal; one or more leads in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes; and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

[0021] Any of the aspects herein, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

[0022] Any of the aspects herein, wherein electrodes of the plurality of electrodes configured to apply the electrical signal comprise stimulation electrodes and electrodes of the plurality of electrodes configured to measure the one or more signals comprise recording electrodes.

[0023] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: receive one or more sensor signals from atleast one sensor, wherein determining the one or more activities is also based on the one or more sensor signals.

[0024] Any of the aspects herein, wherein the at least one sensor comprises at least one of an accelerometer, a gyroscope, or a posture sensor.

[0025] Any aspect in combination with any one or more other aspects.

[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 identifykey 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 and alternative 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 block diagram of a system according to at least one embodiment of the present disclosure;

[0039] Fig. 2A is an example signal measurement according to at least one embodiment of the present disclosure;

[0040] Fig. 2B is an example signal measurement according to at least one embodiment of the present disclosure;

[0041] Fig. 3 is an example power spectrum according to at least one embodiment of the present disclosure;

[0042] Fig. 4 is a diagram of a system according to at least one embodiment of the present disclosure;

[0043] Fig. 5 is a flowchart of a method according to at least one embodiment of the present disclosure;

[0044] Fig. 6 is a flowchart of a method according to at least one embodiment of the present disclosure;

[0045] Fig. 7 is a flowchart of a method according to at least one embodiment of the present disclosure; and

[0046] Fig. 8 is a flowchart of a method according to at least one embodiment of the present disclosure.DETAILED DESCRIPTION

[0047] 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 medical device.

[0048] 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).

[0049] 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 i9 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, A12, A12X, A12Z, or A13 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 specificintegrated 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.

[0050] 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.

[0051] The terms proximal and distal are used in this disclosure with their conventional medical meanings, proximal being closer to a device, operator, or user of the system, and distal being further from the device, operator, or user of the system.

[0052] For some neuromodulation therapies such as, for example closed-loop neuromodulation, a therapeutic electrical signal generated by a pulse generator may be sent to a stimulation target (e.g., nerves, non-neuronal cells, etc.). A biopotential (e.g., recorded signal) elicited with the therapeutic electrical signal may be recorded. The elicited biopotential may provide information by which to adjust the therapeutic electrical signal. Other types of closed-loop neuromodulation therapies may use and sense other types of signals to determine adjustments for the therapeutic electrical signal, such as outputs of other sensors implanted in or placed on a patient (e.g., posture sensor, accelerometer, etc.).

[0053] In some examples, spinal cord stimulation (SCS) (e.g., a form of neuromodulation that includes applying a therapeutic electrical signal or stimulation signal to nerves of the spinal cord or nerves near the spinal cord to elicit a desired electrophysiologic, biochemical, or genetic response) may be practiced in a closed-loop manner. When SCS is performed in a closed-loop manner, contacts (e.g., leads, electrodes, etc.) may be placed near a stimulation target (e.g., patient’s spinal cord or a proximate structure (such as the dorsal root ganglion) or one or more targets), where thecontacts are configured to apply a therapeutic electrical signal to the stimulation target to obtain a desirable electrophysiologic, biochemical, or genetic state (e.g., that leads to pain relief). For example, the therapeutic electrical signal may be configured to change how the patient’s body interprets a pain signal based on causing a desired electrophysiologic, biochemical, or genetic response when applied to the stimulation target.

[0054] While SCS neuromodulation or neurostimulation systems are typically used to deliver electrical stimulation for chronic pain, physiological recordings from the SCS system can provide key information about the health state of the patient. Recent developments in SCS systems have enabled the sensing of a variety of signals, including spinal evoked compound action potentials (ECAPs) and far-field cardiac electrical signals. In addition, the SCS system can pick up electrical signals from far-field muscle activity while the person is moving or performing and activity. It will be appreciated that though the far-field muscle activity is not identical to electromyography signals (EMG) as the far-field muscle activity may not be EMG since it may not be directly over or into the muscle, that far-field muscle activity may be described as EMG throughout the present disclosure. These signals are often regarded as noise, but may hold information about aspects of muscle recruitment. This may provide objective measures of improvement in activity or muscle function as a response to therapy. It can also be used to help guide lead implantation during surgery. Further, using the detected muscle activity on SCS leads as an indicator of muscle function may be used as a biomarker of wellness or activity.

[0055] In some embodiments according to the present disclosure, the detected muscle activity can be paired with specific tasks in clinic. For example, a clinician may ask a patient to bend over or arch their back while the neuromodulation system is recording the muscle activity. This may be in the presence of therapeutic stimulation or in a recording / sensing mode.

[0056] The detected muscle activity can also be used in informing a patient whether they are targeting a specific muscle contraction profile for muscle training. For example, when patient does a back- or neck-strengthening exercise, the muscle signals may be recorded while the patient tries to target an EMG amplitude or duration of contraction.

[0057] Alternatively, the neuromodulation system may be used to record evoked compound muscle action potential(s) (ECMAPs). For example, a spinal lead could be used to sense resulting muscle contractions and observe therapy (titrate, evaluate effectiveness). Or the SCS lead could target L2 dorsal roots for lower back (or any other desired area) and stimulation could be set to cause temporary muscle contractions for pain relief / muscle strengthening and / or rehabilitation of the muscle that is recorded and monitored by the lead.

[0058] Alternatively, the neuromodulation system may be used to sensing unwanted motor contractions to titrate the desired SCS therapy (e.g., minimize undesired stimulation to maximize desired / beneficial aspects of the SCS therapy). The system can be used to identify low-level signals that correspond to SCS pulses that might indicate some level of undesired stimulation or non-optimal lead placement. In addition, ECMAPs may also be recorded to indicate sub-optimal lead placement. Various features may be used including latency of muscle and / or ECMAP activity, size, power and / or threshold. In addition, the relationship of muscle activity to ECAPs may be used (e.g., the ratio of muscle activity threshold to ECAP threshold) to indicate suboptimal placement.

[0059] The neuromodulation system may record the muscle activity in-clinic only or continuous over weeks, months, or years, with summary metrics saved over time to indicate the amount / type / duration of movement.

[0060] Metrics of the muscle activity may be compared over time (e.g., pre SCS implantation to post SCS implantation) as an objective measure of pain or improvement in movements. Metrics may include increased amplitudes, increased power, increased coherence, decreased fatigue, or increase longevity of activation. Data may also be paired with other signals (accelerometer on the device, external wearable / accelerometer, and / or imaging of the patient’s movements) to improve the metrics and / or have additional metrics such as increased range of motion.

[0061] Muscle activity may be analyzed in a variety of ways, including time domain analysis and / or frequency domain analysis techniques. Metrics could include total power, fatigue index, max amplitude, rms amplitude, etc. Muscle activity may be detected by a threshold filter, the relative power with spectral domain, and / or using additional signals such as an accelerometer.

[0062] Embodiments of the present disclosure beneficially enable objective measures of muscle activity to inform a user such as, for example, a patient, a physician, or a physical therapist of whether target muscles are successfully activated and / or target muscle metrics are successfully achieved. Embodiments of the present disclosure also beneficially provide information based on muscle activity that can be used to adjust neuromodulation therapy parameters or components (e.g., lead placement). Embodiments of the present disclosure also beneficially enable comparison of muscle activity metrics over a duration of time that can be used to inform users of changes in muscle activity quality.

[0063] Turning to Fig. 1, a diagram of aspects of a neuromodulation therapy system 100 according to at least one embodiment of the present disclosure is shown. The neuromodulation therapy system 100 may be used to provide electric signals for a patient and / or carry out one or more other aspects of one or more of the methods disclosed herein. The neuromodulation therapy system 100 may beopen-loop or closed-loop. In some examples, the device 102 may be referred to as a pulse generator. The pulse generator may be implantable in a patient or may be external to the patient. Additionally, the neuromodulation therapy system 100 may include one or more wires or leads 104 that provide a connection between the device 102 and nerves of the patient for enabling the stimulation / blocking therapy.

[0064] Neuromodulation 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 or pharmaceutical agents directly to a target area) may be used to provide a desired electrophysiological, biochemical, or genetic response in the stimulation target for assisting in treatments for different diseases, disorders, or ailments of a patient, such as, for example chronic pain. Neuromodulation techniques may also be used to facilitate function, movement, and / or motor in conditions such as, for example, spinal cord injury. Accordingly, as described herein, the neuromodulation techniques may be used for altering the pain signals in the nervous system. For example, the device 102 may provide electrical stimulation to one or more nerves in the spinal cord of the patient (e.g., via the one or more leads 104) to modulate or block the pain signals from being received by the brain. In other examples, the device 102 may provide electrical stimulation to the brain. It will be appreciated that the system 100 may include one device 102, two devices 102, or more than two devices 102.

[0065] In some examples, as shown in Fig. 1, the one or more leads 104 may include one lead 104. In other embodiments, the one or more leads 104 may include multiple leads such as a first lead 102 A and a second lead 102B. In such embodiments, some of the leads 104 may provide active stimulation (using, for example, stimulation electrodes) and other leads 104 may record a physiological response to the stimulation (using, for example, recording electrodes). It will be appreciated that in some embodiments that the lead 104 may both stimulate and record (e.g., some electrodes may provide the stimulation and other electrodes on the same lead may record the physiological response or the same electrodes may provide stimulation and recording). The lead 104 may be implanted on or near any anatomical element targeted for therapy. In some examples, the lead 104 is implanted near the spinal cord and more specifically, in the epidural space between the spinal cord and the vertebrae. Once implanted, the lead 104 may provide an electrical signal (whether stimulating or blocking) from the device 102 to the anatomical element (e.g., one or more nerves in the spinal cord, the brain, etc.). The device 102 in some embodiments, may be implanted in the patient, though in other embodiments the device 102 may be external to the patient’s body.

[0066] In some examples, the lead 104 may provide the electrical signals to the respective nerves via electrodes that are connected to the nerves (e.g., sutured in place, wrapped around the nerves, etc.). In some examples, the lead 104 may be referenced as cuff electrodes or may otherwise include the cuff electrodes (e.g., at an end of the lead 104 not connected or plugged into the device 102). Additionally or alternatively, while shown as physical wires that provide the connection between the device 102 and the one or more nerves, the electrodes may provide the electrical signals to the one or more nerves wirelessly (e.g., with or without the device 102). In still other embodiments, it will be appreciated that the electrodes may not be positioned on the lead 104. For example, the electrodes may be on the device 102.

[0067] Additionally, the one or more leads 104 may be connected, placed, or otherwise implanted near or on a spinal cord 108 within the patient, such that at least one of the one or more leads 104 are located near a heart 110 of the patient. For example, as shown in the inset or zoomed- in portion of the example of Fig. 1 which depicts a side view of the encircled area within the patient, the first lead 104A may be placed within the spinal canal (for example, behind the foramen of the spine near the top of a vertebra of the thoracic vertebrae column) of the spinal cord 108 (e.g., T8 vertebrae) behind the heart 110. Additionally or alternatively, as described previously, the exact placement of the one or more leads 104 may vary depending on, for example, the type of treatment, the type of lead, the patient, combinations thereof, and the like. While not specifically shown in the example of Fig. 1, the one or more leads 104 may also exit the spinal cord 108 at a lumbar vertebra lower down the spinal cord 108 (e.g., the L2 vertebra, but the exact location may vary). As described herein, the one or more leads 104 being placed proximate to the heart 110 may enable the system 100 to more effectively capture signals that include cardiac activity before, during, and / or after providing a neuromodulation therapy (e.g., SCS therapy).

[0068] Additionally, while not shown, the neuromodulation therapy 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) that are programmed to carry out one or more aspects of the present disclosure. In some examples, the one or more processors may be used to control one or more parameters of the neuromodulation therapy system 100. In other examples, 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, the electrodes, or other components of the neuromodulation therapy system 100 not explicitly shown or described with reference to Fig. 1 for providing the pain blocking therapy to regulate chronic pain in a patient as described herein. In someexamples, the one or more processors may be part of the device 102 or part of a control unit for the neuromodulation therapy system 100 (e.g., where the control unit is in communication with the device 102 and / or other components of the neuromodulation therapy system 100).

[0069] The device 102 may be programmed to measure and record movements of the patient (e.g., for the purpose of life, sleep, and activity tracking). For example, the device 102 may comprise an accelerometer and / or other components that are designed to track and record movements of the patient (e.g., whether the patient is moving, not moving, laying down, standing up, running, walking, etc.). Additionally, the leads 104 and / or electrodes disposed at the distal end of the leads 104 may be programmed to measure a physiological response of the patient . In some examples, the physiological response may comprise an evoked response (e.g., ECAP measurement) based on applying the therapeutic electrical signal (e.g., stimulation signal) generated by the device 102 to the spinal cord 108 (e.g., and / or to nearby nerves as described previously). Additionally or alternatively, as described herein, the physiological signals may comprise muscle activity signals (described in more detail in Figs. 2 and 3) which can be used to provide real-time feedback regarding muscle activity, used to track long-term muscle activity, to identify one or more activity patterns, etc. In some examples, the device 102 may be programmed to measure and record signals in addition or alternative to the leads 104 and / or electrodes.

[0070] Figs. 2A, 2B, and 3 illustrate an example signal measurement 200, another example signal measurement 206, and an example power spectrum 300, respectively, according to at least one embodiment of the present disclosure. The muscle activity may be identified in the signal measurement 200 and / or the power spectrum 300, as described below.

[0071] The signal measurements 200 and / or 206 may be acquired by one or more aspects of Fig. 1. For example, the signal measurement 200 may represent or include a raw signals 202, 208 recorded from SCS leads, where the SCS leads may be an example of the leads 104 and / or electrodes as described with reference to Fig. 1. The raw signal 202 may include far-field muscle activity when the patient is active (e.g., moving, performing an activity, etc.). In the illustrated example of Fig. 2A, the patient begins walking around 2 seconds, which is visible as an increase in noise 204. The far- field muscle activity is often regarded as the noise, but may be used as objective measures of, for example, improvements in activity or muscle function in response to therapy and / or can be used to guide lead implantation during a surgical operation. The muscle activity may also be paired with specific tasks given to a patient by a clinician and the muscle activity can be used to determine if the patient has sufficiently performed the task. For example, the patient may be asked to bend or archtheir back until the muscle activity recorded in the signal has reached a target EMG amplitude or duration of contraction of the corresponding target muscles of the muscle activity.

[0072] Fig. 2B illustrates an example of an ECMAP activity 212 that may follow an ECAP 210. The ECMAP activity 212 may be used to, as previously described, sense resulting muscle contractions and observe therapy. The ECMAP activity 212 may also be used to indicate lead migration in instances where the ECMAP activity 212 is observed in SCS therapy, as ECMAPs typically do not appear in SCS signals.

[0073] The muscle activity may also be used in adjusting parameters of a patient’s stimulation therapy and / or evaluating the stimulation therapy. The raw signal 202 may be measured continuously (e.g., over weeks, months, or years) or may be measured at time periods. The raw signal 202 may also be measured based on user input. When the raw signal 202 is measured over time, the muscle activity may be compared over time as an objective measure of pain and / or improvement in muscle activity or movement.

[0074] The muscle activity may be analyzed in a variety of ways, including using time domain analysis and / or frequency domain analysis techniques. Muscle activity metrics may include total power, fatigue index, max amplitude, rms amplitude, etc. Muscle activity may be detected by a threshold filter, the relative power with spectral domain (as shown in Fig. 3), and / or using additional signals such as an accelerometer. As shown in Fig. 3, an increased power 304 shown in the power measurement 300 may indicate muscle activity. Such information may be paired with additional signals such as, for example, an accelerometer, a gyroscope, a posture sensor, etc. to identify the muscle activity. The additional signals may also aid in identifying a type of activity being performed outside of, for example, a clinical setting.

[0075] Turning to Fig. 4, a block diagram of a system 400 according to at least one embodiment of the present disclosure is shown. The system 400 may be used to record and evaluate muscle activity (which may be a part of, for example, a physiological response of the patient) recorded by a system 412 which may be the same as or similar to the neuromodulation therapy system 100. In some examples, the system 400 may implement aspects of or may be implemented by aspects of Fig. 1 as described herein. For example, the system 400 may be used with a device 414, leads 416, and / or electrodes 418, and / or carry out one or more other aspects of one or more of the methods disclosed herein. The device 414 may represent an example of the device 102 or a component of the device 102 as described with reference to Fig. 1 (e.g., implantable pulse generator), where the leads 416 and the electrodes 418 may represent the leads 104 and corresponding electrodes / cuff electrodes as described with reference to Fig. 1. The system 400 comprises a computing device 402, a system 412,one or more sensors 426, a database 430, and / or a cloud or other network 434. Systems according to other embodiments of the present disclosure may comprise more or fewer components than the system 400. For example, the system 400 may not include one or more components of the computing device 402, the database 430, and / or the cloud 434.

[0076] The system 412 may comprise the device 414, leads 416, and the electrodes 418. As previously described, the device 414 may be configured to generate a current (e.g., therapeutic electrical signal, stimulation signal, electrical stimulation signal, etc.), and the leads 416 and the electrodes 418 may comprise a plurality of electrodes configured to carry the current from the device 414 and apply the current to an anatomical element based on the electrodes being implanted on or near the anatomical element (e.g., stimulation target, such as the spinal cord 108 and / or nearby nerves to the spinal cord 108). In some examples, the device 414, leads 416, and electrodes 418 may be configured to measure a physiological response of the patient (e.g., prior to applying the current to the anatomical element, after the current is applied, etc.).

[0077] The system 412 may communicate with the computing device 402 to receive instructions such as instructions 424 for applying a current to the anatomical element. The system 412 may also provide data (such as data received from an electrodes 418 capable of recording data), which may be used to optimize the electrodes 418 and / or to optimize parameters of the current generated by the device 414.

[0078] The computing device 402 comprises a processor 404, a memory 406, a communication interface 408, and a user interface 410. Computing devices according to other embodiments of the present disclosure may comprise more or fewer components than the computing device 402.

[0079] The processor 404 of the computing device 402 may be any processor described herein or any similar processor. The processor 404 may be configured to execute instructions 424 stored in the memory 406, which instructions may cause the processor 404 to carry out one or more computing steps utilizing or based on data received from the system 412, the database 430, and / or the cloud 434.

[0080] The memory 406 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 406 may store information or data useful for completing, for example, any steps of the methods 600, 700, and / or 800 described herein, or of any other methods. The memory 406 may store, for example, instructions and / or machine learning models that support one or more functions of the system 412. For instance, the memory 406 may store content (e.g., instructions and / or machine learning models) that, when executed by theprocessor 404, enable a cardiac metric measurement 420, an activity determination 422, and a therapy determination 424.

[0081] The muscle activity measurement 420 enables the processor 404 to measure and / or receive (e.g., via the device 414, the leads 416, and / or the electrodes 418) one or more signals with muscle activity (e.g., far- field muscle activity, low-level signals, evoked compound muscle action potentials (ECMAPs), EMG, etc.) of the patient. The muscle activity measurement 420 also enables the processor 404 to process the one or more signals to identify the muscle activity. The muscle activity may be identified by, for example, a threshold filter (e.g., signals that meet or exceed the threshold filters correspond to muscle activity), analyzing a relative power in a spectral domain (shown in Fig. 3), user input, and / or using additional sensor data from the sensor 426 (e.g., sensors such as an accelerometer may be used to indicate that the patient is walking or running). The muscle activity may also be identified by, for example, principal component analysis, independent component analysis, and / or template matching techniques, which also may be used to differentiate the muscle activity from ECAPs and / or cardiac data (e.g., ECG). The muscle activity may be analyzed using, for example, time domain analysis and / or frequency domain analysis techniques. Metrics such as, for example, total power, fatigue index, max amplitude, rms amplitude, etc. may be obtained from the analysis. Further, the muscle activity can be differentiated from ECAP and / or cardiac data (e.g., ECG) also using time domain analysis and / or frequency domain analysis techniques and may further use temporal analysis of the latency and / or time from the stimulation pulse.

[0082] The activity determination 422 enables the processor 404 to identify one or more activities based on the muscle activity detected in a measured signal. The activity determination 420 may also enable the processor 404 to generate or form templates for each activity once an activity is identified. The template(s) can be used to identify one or more activities in subsequent signal measurements.

[0083] The therapy determination 428 enables the processor 404 to determine one or more parameters for applying the therapeutic electrical signal to the anatomical element based at least in part on the one or more muscle activities detected in a measured signal. In some embodiments, the therapy determination 428 may enable the processor 404 to determine a muscle activity or muscle activity quality (described in more detail in Fig. 5) falls outside of a predetermined threshold and to adjust one or more parameters of the therapy based at least in part on determining the muscle activity quality falls outside of the predetermined threshold. For example, a ratio of muscle activity compared to an ECAP threshold may indicate suboptimal placement of the lead 416 and thus, a new position of the lead 416 may be determined.

[0084] In some embodiments, multiple components of the system 400 may work together to perform the techniques described herein (e.g., for reporting or providing the longitudinal trend data, leveraging information or signals from additional devices, etc.). For example, the cloud 434 may leverage signals from wearables and / or other information for deriving the muscle activity and / or activity patterns described herein. In some embodiments, the algorithm described herein may combine information stored in the cloud 434, the database 430, or elsewhere outside the system 412 and / or outside the computing device 402 to determine the cardiac metrics. For example, the algorithm may use images (e.g., X-rays, fluoroscopy images, magnetic resonance (MR) images, etc.), medical records, etc., that are stored in the cloud 434, the database 430, or elsewhere outside the system 412 and / or outside the computing device 402 to refine and / or update algorithm parameters. Additionally, some of the therapy adjustment analysis, algorithm updates, etc., may be performed off-device (e.g., outside the system 412 and / or outside the computing device 402), in the cloud 434, etc., and the analysis, updates, etc., can then be pushed back to components of the system 412 and / or the computing device 402.

[0085] Content stored in the memory 406, 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 406 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 404 to carry out the various method and features described herein. Thus, although various contents of memory 406 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 404 to manipulate data stored in the memory 406 and / or received from or via the system 412, the database 430, and / or the cloud 434.

[0086] The computing device 402 may also comprise a communication interface 408. The communication interface 408 may be used for receiving data (for example, data from the electrodes 418 capable of recording data such as recording electrodes) or other information from an external source (such as the system 412, the database 430, the cloud 434, and / or any other system or component not part of the system 400), and / or for transmitting instructions, images, or other information to an external system or device (e.g., another computing device 402, the system 412, the database 430, the cloud 434, and / or any other system or component not part of the system 400). The communication interface 408 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, forexample, to transmit and / or receive information via one or more wireless communication protocols such as 802.11a / b / g / n, Bluetooth, NFC, ZigBee, and so forth). In some embodiments, the communication interface 408 may be useful for enabling the device 402 to communicate with one or more other processors 404 or computing devices 402, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason.

[0087] The computing device 402 may also comprise one or more user interfaces 410. The user interface 410 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 410 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 400 (e.g., by the processor 404 or another component of the system 400) or received by the system 400 from a source external to the system 400. In some embodiments, the user interface 410 may be useful to allow a surgeon or other user to modify instructions to be executed by the processor 404 according to one or more embodiments of the present disclosure, and / or to modify or adjust a setting of other information displayed on the user interface 410 or corresponding thereto.

[0088] Although the user interface 410 is shown as part of the computing device 402, in some embodiments, the computing device 402 may utilize a user interface 410 that is housed separately from one or more remaining components of the computing device 402. In some embodiments, the user interface 410 may be located proximate one or more other components of the computing device 402, while in other embodiments, the user interface 410 may be located remotely from one or more other components of the computer device 402.

[0089] The sensor(s) 426 may be configured to measure one or more characteristics of the patient such as, for example, heart rate, respiratory rate, patient movement, patient posture, etc. and provide sensor data. The sensor data may be used to, for example, confirm muscle activity sensed in a measured signal. The sensor 426 may also be used to provide feedback in, for example, a neuromodulation therapy system such as the neuromodulation therapy system 100. The sensor 426 may be an integral component of the system 400 or the neuromodulation system 100 or may be a component separate from the system 400 or the neuromodulation system 100. In some embodiments, the sensor 426 may be part of a wearable device such as, for example, a smart watch, a cell phone, a smart cell phone, smart glasses, etc. The sensor 426 can include one sensor, two sensors, or more than two sensors. The sensor may comprise, for example, a position sensor, a proximity sensor, amagnetometer, an accelerometer, a linear encoder, a rotary encoder, an image sensor, or an incremental encoder.

[0090] Though not shown, the system 400 may include a controller, though in some embodiments the system 400 may not include the controller. The controller may be an electronic, a mechanical, or an electro-mechanical controller. The controller may comprise or may be any processor described herein. The controller may comprise a memory storing instructions for executing any of the functions or methods described herein as being carried out by the controller. In some embodiments, the controller may be configured to simply convert signals received from the computing device 402 (e.g., via a communication interface 104) into commands for operating the system 412 (and more specifically, for actuating the device 414 and / or the electrodes 418). In other embodiments, the controller may be configured to process and / or convert signals received from the system 412.Further, the controller may receive signals from one or more sources (e.g., the system 412) and may output signals to one or more sources.

[0091] The database 430 may store information such as patient data, results of a stimulation and / or neuromodulation procedure, stimulation and / or neuromodulation parameters, current parameters, electrode parameters, etc. The database 430 may be configured to provide any such information to the computing device 402 or to any other device of the system 400 or external to the system 400, whether directly or via the cloud 434. In some embodiments, the database 430 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.

[0092] The cloud 434 may be or represent the Internet or any other wide area network. The computing device 402 may be connected to the cloud 434 via the communication interface 408, using a wired connection, a wireless connection, or both. In some embodiments, the computing device 402 may communicate with the database 430 and / or an external device (e.g., a computing device) via the cloud 434.

[0093] The system 400 or similar systems may be used, for example, to carry out one or more aspects of any of the methods 500, 600, 700, and / or 800 as described herein. The system 400 or similar systems may also be used for other purposes.

[0094] Fig. 5 depicts a method 500 that may be used, for example, to measure one or more signals with muscle activity.

[0095] The method 500 (and / or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as orsimilar to the processor(s) 404 of the computing device 402 described above. The at least one processor may be the same as or similar to the processor(s) of the device 104, 414 described above. The at least one processor may be part of the device 104, 414 (such as an implantable pulse generator) or part of a control unit in communication with the device 104, 414. A processor other than any processor described herein may also be used to execute the method 500. The at least one processor may perform the method 500 by executing elements stored in a memory such as the memory 506. The elements stored in 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 a muscle activity measurement 420, an activity determination 422, and / or a therapy determination 424.

[0096] The method 500 comprises measuring one or more signals having muscle activity over a duration of time (step 504). The one or more signals may be measured using a neuromodulation system such as the neuromodulation system 100 and a system such as the system 400. It will be appreciated that the one or more signals may be measured with or without therapeutic stimulation. The one or more signals may be processed using a processor such as the processor 404 using a muscle activity measurement such as the muscle activity measurement 420 to measure and / or receive (e.g., via a device such as the device 106, 414, leads such as the leads 104, 416, and / or electrodes such as the electrodes 418) one or more signals with muscle activity (e.g., far-field muscle activity, low-level signals, ECMAPs, EMGs etc.) of the patient. In some embodiments, the muscle activity may correspond to a specific muscle. In other embodiments, the muscle activity may correspond to a grouping of muscles or a region of muscles.

[0097] The processor may also use the muscle activity measurement to process the one or more signals to identify the muscle activity. The muscle activity may be identified by, for example, a threshold filter (e.g., signals that meet or exceed the threshold filters correspond to muscle activity), analyzing a relative power in a spectral domain (shown in Fig. 3), user input, and / or using additional sensor data from a sensor such as the sensor 426 (e.g., sensors such as an accelerometer may be used to indicate that the patient is walking or running). The muscle activity may be analyzed using, for example, time domain analysis and / or frequency domain analysis techniques. Metrics such as, for example, total power, fatigue index, max amplitude, RMS amplitude, etc. may be obtained from the analysis.

[0098] The one or more signals may be measured for the duration of time, which may be subseconds, seconds, hours, days, weeks, months, or years. It will be appreciated that the step 504 maybe repeated such that the one or more signals are measured for a first duration of time, a second duration of time, etc. In some instances, summary metrics may be saved over time to indicate an amount, type, and / or duration of movement as indicated by the muscle activity.

[0099] The method 500 also comprises comparing the muscle activity throughout the duration of time (step 508). Comparing the muscle activity may include, for example, comparing metrics such as increased amplitudes, increased power, increased coherence, decreased fatigue, and / or increase longevity of activation of a muscle. The comparison may also include comparing sensor data obtained from the sensor over the duration of time. In other words, the muscle activity may also be paired with sensor data (e.g., accelerometer on the device, external wearable / accelerometer, images of the patient’s movement, and / or imaging of the patient’s movements) to improve the metrics and / or have additional metrics such as increased range of motion.

[0100] The muscle activity may be compared over the duration of time. For example, the muscle activity may be compared pre-implantation of the neuromodulation therapy system and after implantation of the neuromodulation therapy system. Metrics of the muscle activity that may be compared may include increased amplitudes, increased power, increased coherence, decreased fatigue, or increase duration of activation.

[0101] The method 500 also comprises determining muscle activity quality based on the comparison (step 512). The muscle activity quality may correspond to whether the muscle activity has improved over the duration of time. For example, an increase in a longevity or a duration of activation of a muscle may indicated increased performance and / or use of the muscle. In another example, a decrease in fatigue of the muscle may indicate an increase in muscle strength.

[0102] The method 500 also comprises determining that the muscle activity quality falls outside of a predetermined threshold (step 516). The predetermined threshold may correspond to a target muscle activity quality. For example, the target muscle activity quality may be a target increase in power over the duration of time. In another example, the target muscle activity quality may be a decrease in muscle fatigue over the duration of time.

[0103] The muscle activity quality may be continuously monitored to determine when the muscle activity quality has fallen outside of the predetermined threshold throughout the duration of time. In other instances, the muscle activity quality may be monitored to determine when the muscle activity quality has fallen outside of the predetermined threshold at predetermined intervals throughout the duration of time.

[0104] The method 500 also comprises adjusting one or more stimulation therapy parameters (step 520 A). When the muscle activity falls outside of the predetermined threshold, this may indicate thatthe stimulation therapy and / or placement of the lead is inadequate. The one or more stimulation therapy parameters may be adjusted by the processor using a therapy determination such as the therapy determination 424. Adjusting the one or more parameters (whether open-looped or closed- loop stimulation) may include one or more of changing a threshold or a rate of increase and / or decrease in stimulation, beginning or stopping a cycling of therapy, increasing or decreasing the cycling of therapy, increasing or decreasing the cycling of high-frequency stimulation, changing the ON / OFF cycling times while maintaining a cycling ratio, and / or adjustment of charge balancing strategy or recharge settings (e.g., how charge balance is achieved, such as making recharge adjustments between active recharge, passive recharge, a combination of active and passive recharge, frequency, duration, or any type of recharge). Additionally, adjusting one or more parameters may also include one or more of changing stimulation amplitude, frequency, pulse width, or electrode contact. It will be appreciated that in some embodiments adjustments to the one or more parameters may be outputted by the processor to a user interface such as the user interface 410. In such embodiments, the one or more parameters may be adjusted manually by a user such as, for example, the patient, a medical provider, or clinician.

[0105] The method 500 may also comprise providing an alert (step 520B). The alert may be provided when the muscle activity quality falls outside of the predetermined threshold. The alert may be an audible and / or a visual notification which may be displayed on the user interface or a user device such as, for example, a cell phone, a wearable device, a smart cell phone, a smart wearable device, etc.

[0106] It will be appreciated that the step 520B may be optional. In other words, in some embodiments, an alert may not be provided when the muscle activity quality falls outside of the predetermined threshold.

[0107] The method 500 may be beneficial in evaluating, for example, a stimulation therapy. For example, back muscles such as the lumbar extensors and multifidus muscles often show atrophy in chronic back pain patients. With SCS providing pain relief, patients may have the ability to work on rehabilitation and functional improvement of their back muscles. This could be done through various back strengthening exercises. Over time, the EMG signal might be an objective indicator of functional muscle improvement. EMGs could be recorded immediately after SCS implant with the SCS implant off for baseline muscle function. As the patient goes through sessions of rehabilitation exercises, EMGs could be recorded to look for improvement various metrics with stimulation off as a marker of functional changes. EMGs could also be recorded during functional activities with the SCS implant on and with the SCS implant off. Assuming the SCS is helping to modulate thepatient’s pain, the patient may then be able to do more activities. In other words, the EMG can be used as an objective measure to show the patient or physician (or any other user) that the therapy is helping the patient improve their function.

[0108] 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.

[0109] Fig. 6 depicts a method 600 that may be used, for example, to measure one or more signals with muscle activity.

[0110] The method 600 (and / or one or more steps thereof) 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) 404 of the computing device 402 described above. The at least one processor may be the same as or similar to the processor(s) of the device 104, 414 described above. The at least one processor may be part of the device 104, 414 (such as an implantable pulse generator) or part of a control unit in communication with the device 104, 414. A processor other than any processor described herein may also be used to execute the method 600. The at least one processor may perform the method 600 by executing elements stored in a memory such as the memory 506. The elements stored in 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 a muscle activity measurement 420, an activity determination 422, and / or a therapy determination 424.

[0111] The method 600 comprises measuring one or more signals with muscle activity at a first time period (step 604A). The step 604 may be the same as or similar to the step 504 of the method 500 above.

[0112] The method 600 comprises measuring one or more sensor signals at the first time period (step 604B). The one or more sensor signals may be received from, for example, a sensor such as the sensor 426. As previously described, the sensor(s) may be configured to measure one or more characteristics of the patient such as, for example, heart rate, respiratory rate, patient movement, patient posture, etc. and provide sensor data. The sensor data may be used to, for example, confirm muscle activity sensed in a measured signal. The sensor may be an integral component of a system such as the system 400 or may be a component separate from the system. In some embodiments, the sensor may be part of a wearable device such as, for example, a smart watch, a cell phone, a smart cell phone, smart glasses, etc. The sensor can include one sensor, two sensors, or more than twosensors. The sensor may comprise, for example, a position sensor, a proximity sensor, a magnetometer, an accelerometer, a linear encoder, a rotary encoder, an image sensor, or an incremental encoder.

[0113] The method 600 also determining one or more activities based on the one or more signals and / or the one or more sensor signals (step 608). The one or more activities may be determined by a processor such as the processor 404 using an activity determination such as the activity determination 422 to identify one or more activities based on the muscle activity detected in the measured signal and / or sensor data. The one or more activities may be determined based on patterns detected in the one or more signals. For example, a walking pattern may be determined in the one or more signals. In some instances, the patient may be instructed to perform the activity (e.g., walk) such that the pattern may be more easily identified in the signal. The activity determination may also use the one or more sensor signals to determine or confirm the one or more activities. For example, accelerometer data may be used to confirm that the patient is walking.

[0114] The method 600 also comprises generating a plurality of templates, each template corresponding to an activity of the one or more activities (step 612). The processor may also use the activity determination to generate or form templates for each activity once an activity is identified. The template(s) can be used to identify one or more activities in subsequent signal measurements. The template(s) may be stored in, for example, a memory such as the memory 406, a database such as the database 430, and / or a cloud such as the cloud 434.

[0115] The method 600 also comprises measuring one or more signals with muscle activity at a second time period (step 616). The step 616 may be the same as or similar to the step 504 of the method 500. The second time period may be after the first time period. In some embodiments, the one or more signals may be measured continuously for a duration of time, which may include the first time period and the second time period.

[0116] The method 600 also comprises identifying at least one activity in the one or more signals at the second time period based on the plurality of templates (step 618). The at least one activity may be identified automatically based on the plurality of templates using, for example, the processor. In other instances, the at least one activity may be identified automatically by the processor, then a user such as a medical provider or the patient may be prompted to confirm or approve of the identified activity.

[0117] The at least one activity may be identified by the processor comparing the measured one or more signals with the plurality of templates. The at least one activity may be identified when at least a portion of the one or more signals matches at least one template of the plurality of templates. Atleast one activity may be further identified when the portion of the one or more signals is within a threshold of the at least one template. In other words, a difference between the portion of the one or more signals and the at least one template falls within the threshold.

[0118] The method 600 also comprises adjusting one or more stimulation therapy parameters based on the identified at least one activity (step 622). Identifying the at least one activity could be a trigger to adjust the one or more stimulation therapy parameters. For example, if a patient goes from standing to walking (or a larger bend compared to a smaller one, with a larger activation of the muscle as indicated by EMG signal, or repeated bends within a short amount of time as indicated by the EMG signal) they may need a different or a stronger therapy level due to increased activity. In other words, the increase in detected EMG signal or the detection of a specific EMG pattern could be a trigger to adapt therapy to a new pre-programmed setting relevant for that specific activity.

[0119] The one or more stimulation therapy parameters may be adjusted by a processor such as the processor 404 using a therapy determination such as the therapy determination 424. Adjusting the one or more parameters may include one or more of beginning or stopping a cycling of therapy, increasing or decreasing the cycling of therapy, increasing or decreasing the cycling of high- frequency stimulation, changing the ON / OFF cycling times while maintaining a cycling ratio, and / or adjustment of charge balancing strategy or recharge settings (e.g., how charge balance is achieved, such as making recharge adjustments between active recharge, passive recharge, a combination of active and passive recharge, frequency, duration, or any type of recharge). Additionally, adjusting one or more parameters may also include one or more of changing stimulation amplitude, frequency, pulse width, or electrode contact. It will be appreciated that in some embodiments adjustments to the one or more parameters may be outputted by the processor to a user interface such as the user interface 410. In such embodiments, the one or more parameters may be adjusted manually by a user such as, for example, the patient, a medical provider, or clinician.

[0120] 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.

[0121] Fig. 7 depicts a method 700 that may be used, for example, to measure one or more signals with muscle activity.

[0122] The method 700 (and / or one or more steps thereof) 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) 404 of the computing device 402 described above. The at least one processor may be the same as or similar to the processor(s) of the device 104, 414 described above.The at least one processor may be part of the device 104, 414 (such as an implantable pulse generator) or part of a control unit in communication with the device 104, 414. A processor other than any processor described herein may also be used to execute the method 700. The at least one processor may perform the method 700 by executing elements stored in a memory such as the memory 506. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 700. One or more portions of a method 700 may be performed by the processor executing any of the contents of memory, such as a muscle activity measurement 420, an activity determination 422, and / or a therapy determination 424.

[0123] The method 700 comprises measuring one or more signals with muscle activity at a first time period (step 704). The step 704 may be the same as or similar to the step 504 of the method 500 above.

[0124] The method 700 also adjusting one or more stimulation therapy parameters (step 708). The one or more stimulation therapy parameters may be adjusted by a processor such as the processor 404 using a therapy determination such as the therapy determination 424. Adjusting the one or more parameters may include one or more of beginning or stopping a cycling of therapy, increasing or decreasing the cycling of therapy, increasing or decreasing the cycling of high-frequency stimulation, changing the ON / OFF cycling times while maintaining a cycling ratio, and / or adjustment of charge balancing strategy or recharge settings (e.g., how charge balance is achieved, such as making recharge adjustments between active recharge, passive recharge, a combination of active and passive recharge, frequency, duration, or any type of recharge). Additionally, adjusting one or more parameters may also include one or more of changing stimulation amplitude, frequency, pulse width, or electrode contact. It will be appreciated that in some embodiments adjustments to the one or more parameters may be outputted by the processor to a user interface such as the user interface 410. In such embodiments, the one or more parameters may be adjusted manually by a user such as, for example, the patient, a medical provider, or clinician.

[0125] In some embodiments, one or more stimulation therapy parameters may be adjusted for a closed-loop system. For example, the muscle activity can be detected and a change in amplitude or the closed-loop algorithm that detects neural signals (e.g., change in the increasing or decreasing rate) may be detected. In such examples, the muscle activity measured in the step 704 (for example) may be used to adjust an amplitude (whether increased, decreased, or scaled) of the closed-loop system as compared to a neural signal. In another example, detecting the muscle activity may result in using a different threshold for neural signal with muscle activity is present or not present. In afurther example, detecting the muscle activity may result in using a different algorithm (e.g., principal component analysis and / or independent component analysis) to differentiate between signals (e.g., muscle activity, cardiac data, etc.).

[0126] The method 700 also comprises measuring one or more signals with muscle activity at a second time period (step 712). The step 712 may be the same as or similar to the step 504 of the method 500 above. It will be appreciated that the one or more signals may be recorded

[0127] The method 700 also comprises determining if the stimulation therapy is satisfactory (step 716). Determining if the stimulation therapy is satisfactory may include, for example, comparing the muscle activity at the first time period with the muscle activity at the second time period (e.g., after the stimulation therapy is adjusted). The comparison may be used to sense undesired motor contractions, which can be used to titrate SCS therapy. This sensing can identify low-level signals that correspond to SCS pulses that might indicate some level of undesired stimulation or non-optimal lead placement. In addition, suboptimal lead placement or a shift in the lead placement may be identified using ECMAPS, latency of muscle and / or ECMAP activity, size, power, and / or threshold. In addition, the relationship of muscle activity to ECAPs may be used (e.g., the ratio of muscle activity threshold to ECAP threshold) to indicate suboptimal placement. For example, because ECMAPs are not commonly recorded on by leads used in SCS, the presence of ECMAPs or a change in the latency may indicate a lead migration. Similarly, a marked change in metrics of the far field muscle activity (non-evoked) may also indicate lead migration.

[0128] Alternatively or additionally, the one or more signals may be recorded to measure stimulation-induced muscle contractions induced by, for example, a neuromodulation therapy system such as the neuromodulation therapy system 100. In other words, a lead such as the lead 104, 416 positioned at a spine of a patient could be used to sense resulting muscle contractions and observe the stimulation therapy (titrate, evaluate effectiveness). In some instances, the lead could be used to target an anatomical element such as, for example, L2 dorsal roots for a patient’s lower back and stimulation could be set to cause temporary muscle contractions for pain relief / muscle strengthening that is recorded and monitored by the lead. In examples where the target anatomical element is the L2 dorsal roots, patients with L2 dorsal root stimulation may use lower frequency stimulation (2-20 Hz) at an amplitude high enough to engage muscle activity for up to, for example, 30 minutes. The purpose of this type of stimulation is for pain relief but also potentially for muscle strengthening. Recording SCS-induced EMG from this lead or another SCS lead can be used to titrate the therapy to a desired EMG level.

[0129] Determining if the stimulation therapy is satisfactory may include may include comparing the muscle activity to one or more thresholds. Additionally or alternatively, user input may be used to determine if the stimulation therapy is satisfactory. If the stimulation therapy is unsatisfactory, the step 708 may be repeated. It will be appreciated that if the step 708 is repeated, then any of the steps 712 and / or 716 may also be repeated.

[0130] The method 700 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0131] Fig. 8 depicts a method 800 that may be used, for example, to measure one or more signals with muscle activity.

[0132] The method 800 (and / or one or more steps thereof) 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) 404 of the computing device 402 described above. The at least one processor may be the same as or similar to the processor(s) of the device 104, 414 described above. The at least one processor may be part of the device 104, 414 (such as an implantable pulse generator) or part of a control unit in communication with the device 104, 414. A processor other than any processor described herein may also be used to execute the method 800. The at least one processor may perform the method 800 by executing elements stored in a memory such as the memory 506. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 800. One or more portions of a method 800 may be performed by the processor executing any of the contents of memory, such as a muscle activity measurement 420, an activity determination 422, and / or a therapy determination 424.

[0133] The method 800 also comprises instructing a patient to perform an activity and / or movement for a duration of time (step 804). The patient may be instructed to perform an activity and / or a movement such as, for example, walking, bending, arching, moving specific limbs, running, sitting, standing, laying down, etc. for a duration of time. The patient may be instructed by, for example, a clinician or other medical provider. For example, a clinician may instruct a patient to bend over or arch their back while one or more signals are measured for the duration of time.

[0134] The method 800 comprises measuring one or more signals with muscle activity for the duration of time (step 808). The step 808 may be the same as or similar to the step 504 of the method 500 above.

[0135] The method 800 also comprises determining if the patient is activating target muscle(s) (step 812). Determining if the patient is activating the target muscle(s) includes analyzing the muscle activity measured and identified in the step 812 above.

[0136] Such movement(s) or activities performed in the step 804 above may target a specific muscle contraction profile for, for example, muscle training. For example, when a patient does a back- or neck- strengthening exercise, the one or more signals may be recorded while the patient tries to target an EMG amplitude or duration of contraction.

[0137] It will be appreciated that if the patient is not activating the target muscle(s), the steps 804 and 808 may be repeated until the target muscle is activated.

[0138] The method 800 may be beneficial in applications such as, for example, physical therapy where a patient is targeting a specific muscle contraction. The method 800 may provide additional information regarding whether the patient is successfully activating the target muscle. For example, a patient may perform certain exercises to help with chronic low back pain - both for pain relief and for functional restoration of the muscles. For example, lumbar extensor strengthening and training may help with chronic low back pain as these muscles often show signs of atrophy in patients with chronic low back pain. A user such as physical therapists or even patients themselves might use the muscle activity measured during the lumbar extensors as an indicator of 1) targeting the right muscle group; 2) targeting a specific EMG amplitude; and / or 3) feedback on duration of muscle contraction. Using the EMG signals from muscles near the spine could be motivating for the patient and provide feedback for the physical therapist (or any other user) that muscle work is being successfully performed. Over time, the EMG signal might be an objective indicator of functional muscle improvement.

[0139] The present disclosure encompasses embodiments of the method 800 that comprise more or fewer steps than those described above, and / or one or more steps that are different than the steps described above.

[0140] As noted above, the present disclosure encompasses methods with fewer than all of the steps identified in Figs. 5, 6, 7, and 8 (and the corresponding description of the methods 500, 600, 700, and / or 800), as well as methods that include additional steps beyond those identified in Figs. 5, 6, 7, and 8 (and the corresponding description of the methods 500, 600, 700, and / or 800). The present disclosure also encompasses methods that comprise one or more steps from one method described herein, and one or more steps from another method described herein. Any correlation described herein may be or comprise a registration or any other correlation.

[0141] 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 lie 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.

[0142] 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.

[0143] The following statements provide non-limiting examples of systems and methods for setting and fixing one or more anatomical elements of the present disclosure:

[0144] Statement 1. A system for informing a therapeutic procedure, comprising: a processor; and a memory storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals having muscle activity over a duration of time; compare the muscle activity throughout the duration of time; and determine muscle activity quality based on the comparison.

[0145] Statement 2. The system of Statement 1, further comprising: a pulse generator configured to generate a therapeutic electrical signal; one or more leads in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes; and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

[0146] Statement 3. The system of Statement 2, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

[0147] Statement 4. The system of Statement 2, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: identify the muscle activity, ECAP, cardiac activity, or a combination thereof in the one or more signals.

[0148] Statement 5. The system of any of Statements 1-4, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: determine the muscle activity quality falls outside of a predetermined threshold; and adjust one or more therapy parameters for applying the therapeutic electrical signal to the anatomical element based at least in part on determining the muscle activity quality falls outside of the predetermined threshold, or provide, via a user interface, an alert indicating that the muscle activity quality falls outside of the predetermined threshold.

[0149] Statement 6. The system of Statement 5, wherein the one or more adjusted therapy parameters comprise an amplitude adjustment, adjustment of duty cycling, adjustment of cycling of high frequency or low frequency components independently, adjustment of frequency, adjustment of pulse width, adjustment of charge balancing strategy, adjustment of selection of the plurality of electrodes, or a combination thereof.

[0150] Statement 7. The system of any of Statements 1 -6, wherein the duration of time is at least one of one or more sub-seconds, one or more hours, one or more hours, one or more days, one or more weeks, one or more months, or one or more years.

[0151] Statement 8. The system of any of Statements 1-7, wherein the comparison comprises comparing at least one of amplitude, power, coherence, fatigue, or longevity of activation over the duration of time.

[0152] Statement 9. The system of any of Statements 1-8, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: receive one or more sensor signals from at least one sensor over a duration of time, wherein determining the muscle activity quality is also based on the one or more sensor signals.

[0153] Statement 10. A system for informing a therapeutic procedure, comprising: a processor; and a memory storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals with muscle activity of a patient for a first time period; adjust one or more parameters of a stimulation therapy; receive one or more signals with the muscle activity of the patient for a second time period; compare the muscle activity from the first timeperiod with the muscle activity from the second time period; and determine muscle activity quality based on the comparison.

[0154] Statement 11. The system of Statement 10, further comprising: a pulse generator configured to generate a therapeutic electrical signal; one or more leads in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes; and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

[0155] Statement 12. The system of Statement 11, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

[0156] Statement 13. The system of Statement 11, wherein electrodes of the plurality of electrodes configured to apply the electrical signal comprise stimulation electrodes and electrodes of the plurality of electrodes configured to measure the one or more signals comprise recording electrodes.

[0157] Statement 14. The system of any of Statements 10-13, wherein adjusting the one or more stimulation parameters comprises adjusting a position of the one or more leads.

[0158] Statement 15. A system for informing a therapeutic procedure, comprising: a processor; and a memory storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals with muscle activity of a patient for a first time period; determine one or more activities based on the one or more signals; generate a plurality of templates, each template corresponding to an activity of the one or more activities; receive one or more signals with the muscle activity of the patient for a second time period; and identify at least one activity in the one or more signals at the second time period based on the plurality of templates.

[0159] Statement 16. The system of Statement 15, further comprising: a pulse generator configured to generate a therapeutic electrical signal; one or more leads in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes; and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

[0160] Statement 17. The system of Statement 16, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

[0161] Statement 18. The system of Statement 16, wherein electrodes of the plurality of electrodes configured to apply the electrical signal comprise stimulation electrodes and electrodes of the plurality of electrodes configured to measure the one or more signals comprise recording electrodes.

[0162] Statement 19. The system of any of Statements 15-18, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: receive one or more sensor signals from at least one sensor, wherein determining the one or more activities is also based on the one or more sensor signals.

[0163] Statement 20. The system of Statement 19, wherein the at least one sensor comprises at least one of an accelerometer, a gyroscope, or a posture sensor.

Claims

CLAIMSWhat is claimed is:

1. A system (100, 400) for informing a therapeutic procedure, comprising: a processor (404); and a memory (406) storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals having muscle activity over a duration of time; compare the muscle activity throughout the duration of time; and determine muscle activity quality based on the comparison.

2. The system of claim 1, further comprising: a pulse generator (106, 414) configured to generate a therapeutic electrical signal; one or more leads (104,416) in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes (418); and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

3. The system of claim 2, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

4. The system of claim 2, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: identify the muscle activity, ECAP, cardiac activity, or a combination thereof in the one or more signals.

5. The system of any of claims 1-4, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: determine the muscle activity quality falls outside of a predetermined threshold; and adjust one or more therapy parameters for applying the therapeutic electrical signal to the anatomical element based at least in part on determining the muscle activity quality falls outside of the predetermined threshold, orprovide, via a user interface, an alert indicating that the muscle activity quality falls outside of the predetermined threshold.

6. The system of claim 5, wherein the one or more adjusted therapy parameters comprise an amplitude adjustment, adjustment of duty cycling, adjustment of cycling of high frequency or low frequency components independently, adjustment of frequency, adjustment of pulse width, adjustment of charge balancing strategy, adjustment of selection of the plurality of electrodes, or a combination thereof.

7. The system of any of claims 1-6, wherein the duration of time is at least one of one or more sub-seconds, one or more hours, one or more hours, one or more days, one or more weeks, one or more months, or one or more years.

8. The system of any of claims 1-7, wherein the comparison comprises comparing at least one of amplitude, power, coherence, fatigue, or longevity of activation over the duration of time.

9. The system of any of claims 1-8, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: receive one or more sensor signals from at least one sensor over a duration of time, wherein determining the muscle activity quality is also based on the one or more sensor signals.

10. A system (100, 400) for informing a therapeutic procedure, comprising: a processor (404); and a memory (406)storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals with muscle activity of a patient for a first time period; adjust one or more parameters of a stimulation therapy; receive one or more signals with the muscle activity of the patient for a second time period; compare the muscle activity from the first time period with the muscle activity from the second time period; anddetermine muscle activity quality based on the comparison.

11. The system of claim 10, further comprising: a pulse generator (106, 414) configured to generate a therapeutic electrical signal; one or more leads (104,416) in communication with the pulse generator and configured to transmit the electrical signal to a plurality of electrodes (418); and the plurality of electrodes in communication with the one or more leads, the plurality of electrodes configured to apply the electrical signal to an anatomical element of a patient and configured to measure the one or more signals.

12. The system of claim 11, wherein the plurality of electrodes configured to measure the one or more signals are configured to continuously measure the one or more signals.

13. The system of claim 11, wherein electrodes of the plurality of electrodes configured to apply the electrical signal comprise stimulation electrodes and electrodes of the plurality of electrodes configured to measure the one or more signals comprise recording electrodes.

14. The system of any of claims 10-13, wherein adjusting the one or more stimulation parameters comprises adjusting a position of the one or more leads.

15. A system (100, 400) for informing a therapeutic procedure, comprising: a processor (404); and a memory (406) storing data for processing by the processor, the data, when processed, causes the processor to: receive one or more signals with muscle activity of a patient for a first time period; determine one or more activities based on the one or more signals; generate a plurality of templates, each template corresponding to an activity of the one or more activities; receive one or more signals with the muscle activity of the patient for a second time period; and identify at least one activity in the one or more signals at the second time period based on the plurality of templates.

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