Blood pressure modulation with spinal cord stimulation

Abstract

Systems, methods, and devices deliver stimulation to a patient based on one or more duty cycle parameters, wherein delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters. The systems, methods, and devices maintain or update the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of a physiological parameters associated with the patient at or near a target value. The value of the one or more physiological parameters includes a mean value or average value with respect to a temporal duration. The habituation includes a physiological habituation of one or more physiologic processes of the patient to the stimulation.

Description

BLOOD PRESSURE MODULATION WITH SPINAL CORD STIMULATIONCROSS-REFERENCE TO RELATED APPLICATIONSThis application claims the benefit of the filing date of provisional U.S. Patent Application No. 63 / 533,552 filed on August 18, 2023, the entire content of each of which is incorporated herein by reference.FIELD OF INVENTION

[0001] The present disclosure is generally directed to the treatment of hypertension, and relates more particularly to the treatment of hypertension using cycled spinal cord stimulation.BACKGROUND

[0002] 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 pain treatment to a patient.BRIEF SUMMARY

[0003] Example aspects of the present disclosure include:

[0004] According to one aspect, a system is provided that includes: a processor; and a memory storing instructions thereon that, when executed by the processor, cause the processor to: control delivery of stimulation to a patient based on one or more duty cycle parameters; and maintain or update the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

[0005] In some embodiments, the value of the one or more physiological parameters comprises a mean value or average value of the one or more physiological parameters with respect to a temporal duration.

[0006] In some embodiments, the habituation comprises a physiological habituation of one or more physiologic processes of the patient to the stimulation.

[0007] In some embodiments, the instructions are further executable by the processor to: compare the value of the one or more physiological parameters to the target value, wherein maintaining or updating the one or more duty cycle parameters is based on a result of the comparing.

[0008] In some embodiments, the instructions are further executable by the processor to: calculate the value of the one or more physiological parameters associated with the patient.

[0009] In some embodiments, the instructions are further executable by the processor to: calculate a difference value between the value of the one or more physiological parameters and the target value, wherein maintaining or updating the one or more duty cycle parameters is based on the difference value.

[0010] In some embodiments: the value of the one or more physiological parameters is calculated with respect to a temporal duration; and the temporal duration comprises one or more instances of delivering the stimulation.

[0011] In some embodiments, the one or more duty cycle parameters comprise a temporal duration, wherein the temporal duration is equal to about 1 second, about 2 seconds, about 5 seconds, about 10 seconds, about 20 seconds, or about 50 seconds.

[0012] In some embodiments, the stimulation comprises neurostimulation.

[0013] In some embodiments, the one or more physiological parameters comprise blood pressure of the patient.

[0014] In some embodiments, the one or more physiological parameters are associated with one or more sympathetic nerves of the patient.

[0015] In some embodiments, the stimulation is delivered to one or more anatomical elements of the patient, wherein the one or more anatomical elements comprise one or more spinal nerves.

[0016] In some embodiments, the one or more duty cycle parameters comprise: duty cycle timing; duration of stimulation ON; duration of stimulation OFF; a percentage of electrical pulses to be suppressed; and a quantity of the electrical pulses to be suppressed.

[0017] In some embodiments, the system further includes a controller that controls the one or more duty cycle parameters and one or more stimulation parameters in association with delivering the stimulation.

[0018] In some embodiments, delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters.

[0019] In some embodiments, the plurality of electrical pulses are delivered based on one or more stimulation parameters, wherein the one or more stimulation parameters comprise signal frequency and signal amplitude.

[0020] In some embodiments, maintaining or updating the one or more duty cycle parameters is based on a user input.

[0021] In some embodiments, the instructions are further executable by the processor to: receive a data signal from one or more sensors comprised in the system; determine a plurality of measurement values of the one or more physiological parameters based on the data signal; and calculate the value of the one or more physiological parameters based on the plurality of measurement values.

[0022] In some embodiments, the system further includes a device to at least one of: deliver the stimulation based on the one or more duty cycle parameters; and calculate the value based on a data signal received from one or more sensors comprised in the system. The device may include at least one of a medical device, a wearable device, and an implanted device.

[0023] In some embodiments, the system further includes: a pulse generator configured to generate the stimulation; and at least one electrode in communication with the pulse generator to deliver the stimulation.

[0024] In some embodiments, the at least one electrode includes: a first electrode to deliver the stimulation; and a second electrode to sense a response to the stimulation.

[0025] According to another aspect, a device for providing therapy is provided, the device including: one or more electrodes; and a controller device that controls one or more duty cycle parameters in association with delivering stimulation to one or more anatomical elements via the one or more electrodes, where providing the therapy includes: delivering the stimulation to the one or more anatomical elements of a patient based on the one or more duty cycle parameters; and maintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

[0026] According to another aspect, a method is provided that includes: delivering stimulation to a patient based on one or more duty cycle parameters, wherein delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters; and maintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

[0027] Any aspect in combination with any one or more other aspects.

[0028] Any one or more of the features disclosed herein.

[0029] Any one or more of the features as substantially disclosed herein.

[0030] Any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein.

[0031] Any one of the aspects / features / implementations in combination with any one or more other aspects / features / implementations.

[0032] Use of any one or more of the aspects or features as disclosed herein.

[0033] 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 implementation.

[0034] 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.

[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, implementations, and configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, implementations, 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 implementation 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, implementations, and configurations of the disclosure, as illustrated by the drawings referenced below.

[0038] Fig. 1 illustrates an example of a system that supports aspects of the present disclosure.

[0039] Fig. 2 illustrates an example of the system as supported by aspects of the present disclosure.

[0040] Fig. 3 illustrates an example view of a stimulation signal and a response waveform in accordance with example aspects of the present disclosure.

[0041] Fig. 4 illustrates an example view of a stimulation signal and a response waveform in accordance with example aspects of the present disclosure.

[0042] Fig. 5 illustrates an example of a process flow in accordance with aspects of the present disclosure.DETAILED DESCRIPTION

[0043] 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 implementation, 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 implementations 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.

[0044] 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). 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., RAM, 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).

[0045] 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; AMDAthlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple Al l, A12, A12X, A12Z, or Al 3 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0046] Before any implementations 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 implementations 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.

[0047] The terms proximal and distal are used in this disclosure with their conventional medical meanings, proximal being closer to the operator or user of the system, and further from the region of surgical interest in or on the patient, and distal being closer to the region of surgical interest in or on the patient, and further from the operator or user of the system.

[0048] For some neuromodulation therapies, a therapeutic electrical signal generated by a pulse generator may be sent to a stimulation target (e.g., nerves, non-neuronal cells, etc.). In a closed-loop neuromodulation therapy, a biopotential (e.g., a 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.).

[0049] Spinal cord stimulation (SCS) is 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. In some cases, SCS 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 the contacts 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 cause a desired electrophysiologic, biochemical, or genetic response when applied to the stimulation target.

[0050] Spinal cord stimulation (SCS) has been investigated as a treatment for pain and as a method to modulate sympathetic activation, and for example, blood pressure. However, results associated with some SCS approaches have been mixed (e.g., showing no, hyper-, or hypo-tensive effects). For example, some other approaches may have no effect on blood pressure or heart rate, result in increasing arterial blood pressure in individuals with SCI-induced cardiovascular deficits, or involve applying electrical energy to a neural target site and sensors for detecting resultant blood pressure.

[0051] According to example aspects of the present disclosure, systems and techniques are described that support controlling blood pressure with SCS through application of appropriate stimulation to an appropriate anatomical location. For example, the systems and techniques may support lateral placement of an SCS lead in the lower thoracic spine (e.g., T12) through the upper lumbar vertebrae, which places the electrodes close to the least splanchnic nerve associated with the renal plexus and the lumbar splanchnic nerves. The least splanchnic nerves originate from the medial branches of the 11th and / or the 12th thoracic sympathetic ganglia. In some aspects, the anatomical elements (e.g., lower thoracic spine (T12), least splanchnic nerves) described herein where SCS leads are placed and to which stimulation is applied may be particularly well suited for neuromodulation intended to modulate blood pressure.

[0052] The systems and techniques described herein may include duty cycling stimulation to a target anatomical element (e.g., least splanchnic nerves, etc.) while accounting for habituation of a neural target, example aspects of which are described herein.

[0053] Fig. 1 illustrates an example of a system 100 that supports aspects of the present disclosure.

[0054] The system 100 includes a computing device 102, a database 130, a cloud network 134 (or other network), a system 160, and / or a wearable device 170. Systems according to other implementations of the present disclosure may include more or fewer components than the system100. For example, the system 100 may omit and / or include additional instances of one or more components of the computing device 102, a database 130, a cloud network 134 (or other network), a system 160, and / or a wearable device 170. In an example, the system 100 may omit any instance of the computing device 102, database 130, cloud network 134 (or other network), system 160, and / or wearable device 170. The system 100 may support the implementation of one or more other aspects of one or more of the methods disclosed herein.

[0055] The computing device 102 includes a processor 104, a memory 106, a communication interface 108, and a user interface 110. Computing devices according to other implementations of the present disclosure may include more or fewer components than the computing device 102. The computing device 102 may be, for example, a control device including electronic circuitry associated with providing control signals to a therapy device 162 of the system 160.

[0056] The processor 104 of the computing device 102 may be any processor described herein or any similar processor. The processor 104 may be configured to execute instructions stored in the memory 106, which instructions may cause the processor 104 to carry out one or more computing steps utilizing or based on data received from the database 130, the cloud network 134 (or other network), the system 160, and / or the wearable device 170.

[0057] The memory 106 may be or include 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 106 may store information or data associated with completing, for example, any step of the methods described herein, or of any other methods. The memory 106 may store, for example, instructions and / or machine learning models that support one or more functions of the computing device 102, the system 160, and / or the wearable device 170. For instance, the memory 106 may store content (e.g., instructions and / or machine learning models) that, when executed by the processor 104, enable signal processing engine 152 and / or therapy determination engine 156. Such content, if provided as in instruction, may, in some implementations, be organized into one or more applications, modules, packages, layers, or engines.

[0058] Alternatively or additionally, the memory 106 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 104 to carry out the various method and features described herein. Thus, although various contents of memory 106 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 104 tomanipulate data stored in the memory 106 and / or received from or via the computing device 102, the database 130, the cloud network 134, the system 160, and / or the wearable device 170.

[0059] The computing device 102 may also include a communication interface 108. The communication interface 108 may be used for receiving data or other information from an external source (e.g., the database 130, the cloud network 134, the system 160, the wearable device 170, and / or any other system or component separate from the system 100), and / or for transmitting instructions, data (e.g., control signals, data signals, waveforms, etc.), or other information to an external system or device (e.g., another computing device 102the database 130, the cloud network 134, the system 160, the wearable device 170, and / or any other system or component not part of the system 100). The communication interface 108 may include one or more wired interfaces (e.g., a USB port, an Ethernet port, a Firewire port) and / or one or more wireless transceivers or interfaces (configured, for example, to transmit and / or receive information via one or more wireless communication protocols such as 702.1 la / b / g / n, Bluetooth, NFC, ZigBee, and so forth). In some implementations, the communication interface 108 may support communication between the therapy device 162 and one or more other processors 104 or computing devices 102, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason.

[0060] The computing device 102 may also include one or more user interfaces 110. The user interface 110 may be or include 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 110 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 100 (e.g., by the processor 104 or another component of the system 100) or received by the system 100 from a source external to the system 100. In some implementations, the user interface 110 may support user modification (e.g., by a surgeon, medical personnel, a patient, etc.) of instructions to be executed by the processor 104 according to one or more implementations of the present disclosure, and / or to user modification or adjustment of a setting of other information displayed on the user interface 110 or corresponding thereto.

[0061] In some implementations, the computing device 102 may utilize a user interface 110 that is housed separately from one or more remaining components of the computing device 102. In some implementations, the user interface 110 may be located proximate one or more other components of the computing device 102, while in other implementations, the user interface 110 may be located remotely from one or more other components of the computer device 102.

[0062] The system 160 may include a therapy device 162, electrodes 166, and leads 168. The therapy device 162 may include an implantable pulse generator (e.g., pulse generator 164). Example aspects of the system 160 and the wearable device 170 are later described herein (e.g., with reference to Fig. 2). The therapy device 162 may be configured to generate a current (e.g., therapeutic electrical signal, stimulation signal, electrical stimulation signal, etc.), and the leads 168 and the electrodes 166 may comprise a plurality of electrodes configured to carry the current from the therapy device 162 and apply the current to an anatomical element based on the electrodes being implanted on or near the anatomical element (e.g., stimulation target, for example, the spinal cord 149 of the patient 148 and / or nearby nerves to the spinal cord 149). In some examples, the therapy device 162, leads 168, and electrodes 166 may be configured to measure a physiological response of the patient 148 (e.g., prior to applying the current to the anatomical element, during application of the current, after the current is applied, etc.).

[0063] The system 160 may communicate with the computing device 102 to receive instructions for applying a current to the anatomical element and / or delivering therapy (e.g., electrical stimulation, pharmacological agent, etc.) to the anatomical element. The system 160 may also provide data (such as data received from an electrodes 166 capable of recording data), which may be used to optimize the electrodes 166 (e.g., optimize electrode placement) and / or to optimize parameters of the current generated by the therapy device 162.

[0064] Signal processing engine 152 enables the processor 104 to implement features associated with processing of data signals, data analysis with respect to the signals, waveform generation, and waveform analysis as described herein. For example, signal processing engine 152 may support features for calculating values of one or more physiological parameters as described herein.

[0065] The therapy determination engine 156 enables the processor 104 to determine one or more parameters (e.g., duty cycle parameters, frequency, amplitude, etc.) in association with delivering therapy to a patient 148. The therapy determination engine 156 enables the processor 104 to maintain or update the one or more parameters (e.g., duty cycle parameters, etc.) in association with counteracting habituation and maintaining a value of one or more physiological parameters (e.g., blood pressure, etc.) associated with the patient 148 at or near a target value.

[0066] In an example, the therapy determination engine 156 may determine parameters or instructions that cause the therapy device 162 to employ the pulse generator 164 to generate a stimulus (e.g., electrical stimulation, neurostimulation, etc.) or that cause the therapy device 162 to deliver other therapy (e.g., a pharmacological agent, etc.). In some aspects, the therapy determination engine 156 may be referred to as a clinician programmer application.

[0067] The processor 104 may utilize data stored in memory 106 as a neural network. The neural network may include a machine learning architecture. In some aspects, the neural network may be or include one or more classifiers. In some other aspects, the neural network may be or include any machine learning network such as, for example, a deep learning network, a convolutional neural network, a reconstructive neural network, a generative adversarial neural network, or any other neural network capable of accomplishing functions of the computing device 102 described herein. Some elements stored in memory 106 may be described as or referred to as instructions or instruction sets, and some functions of the computing device 102 may be implemented using machine learning techniques.

[0068] The neural network architecture may support various inputs supportive of implementing aspects of the present disclosure. For example, the neural network architecture may support generating outputs based on model inputs in association with configuring parameters (e.g., stimulation parameters described herein) for delivering therapy to a patient 148.

[0069] The neural network architecture may include various appropriate model types supportive of implementing aspects of the present disclosure. For example, the neural network architecture may include statistical machine learning models (e.g., linear regression, logistic regression, decision trees, random forest, Naive bayes, ensemble methods, support vector machines, k-nearest neighbor, etc.). In some examples, the neural network architecture may include deep learning models (e.g., convolutional neural network, recurrent neural network, deep reinforcement network, deep belief network, transformer network, etc.). In some examples, the machine learning model(s) 138 may include vector machines (SVMs), convolutional neural network (CNN) models, or other machine learning models appropriate with implementing aspects of the present disclosure as described herein.

[0070] The neural network architecture may support unsupervised machine learning algorithms (e.g., principal component analysis (PC A) algorithms), semi-supervised machine learning algorithms, and supervised machine learning algorithms. The neural network architecture may support locked execution modes and continuous learning execution modes. The neural network architecture may support providing outputs including content, classifications, predictions, recommendations, and decisions.

[0071] The processor 104 may support machine learning model(s) 138 which may be trained and / or updated based on data (e.g., training data 146) provided or accessed by any of the computing device 102, the database 130, the cloud network 134, the system 160, and / or the wearable device 170. The machine learning model(s) 138 may be built and updated by the computing device 102 based on the training data 146 (also referred to herein as training data and feedback).

[0072] For example, the machine learning model(s) 138 may be trained with one or more training sets included in the training data 146. The training data 146 may include a training data set associated with one or more therapies delivered to reference patients 148. In an example, the training data 146 may include reference data signals received from sensors (e.g., electrodes 166, etc.) based on therapies delivered to the reference patients 148. In some examples, the training data 146 may include reference data signals and respective classifications corresponding to the reference data signals. In some cases, the training data 146 may include respective classifications associated with waveforms (or portions of the waveforms) that corresponding to the data signals 126.

[0073] In some aspects, the training data 146 may include multiple training sets. In an example, the training data 146 may include training sets including reference data of any of the data described herein. In some examples, based on the training data 146, the neural network may generate one or more algorithms (e.g., processing algorithms) supportive of the features described herein.

[0074] Though not shown, the system 100 may include a controller, though in some implementations the system 100 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 implemented by any processor (e.g., processor 104) 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 implementations, the controller may be configured to simply convert signals received from the computing device 102 (e.g., via a communication interface 108) into commands for operating the system 160 (and more specifically, for actuating the therapy device 162 and the pulse generator(s) 164 thereof). In other implementations, the controller may be configured to process and / or convert signals received from the system 160 or the wearable device 170. Further, the controller may receive signals from one or more sources (e.g., system 160, wearable device 170) and may output signals to one or more sources.

[0075] The database 130 may store information that correlates one coordinate system to another (e.g., one or more robotic coordinate systems to a patient coordinate system and / or to a navigation coordinate system). The database 130 may additionally or alternatively store, for example, one or more surgical plans (including, for example, pose information about a target and / or image information about a patient’s anatomy at and / or proximate the surgical site, for use by a robotic system, a navigation system, and / or a user of the computing device 102 or of the system 100); one or more images useful in connection with a surgery to be completed by or with the assistance of one or more other components of the system 100; and / or any other useful information. The database 130may additionally or alternatively store, for example, training data 144, classification data, and the like.

[0076] The database 130 may be configured to provide any such information to the computing device 102 or to any other device of the system 100 or external to the system 100, whether directly or via the cloud network 134. In some implementations, the database 130 may include treatment information (e.g., a therapy plan) associated with a patient. In some implementations, the database 130 may be or include 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 including image data.

[0077] In some aspects, the computing device 102 may communicate with a server(s) and / or a database (e.g., database 130) directly or indirectly over a communications network (e.g., the cloud network 134). The communications network may include any type of known communication medium or collection of communication media and may use any type of protocols to transport data between endpoints. The communications network may include wired communications technologies, wireless communications technologies, or any combination thereof.

[0078] Wired communications technologies may include, for example, Ethernet-based wired local area network (LAN) connections using physical transmission mediums (e.g., coaxial cable, copper cable / wire, fiber-optic cable, etc.). Wireless communications technologies may include, for example, cellular or cellular data connections and protocols (e.g., digital cellular, personal communications service (PCS), cellular digital packet data (CDPD), general packet radio service (GPRS), enhanced data rates for global system for mobile communications (GSM) evolution (EDGE), code division multiple access (CDMA), single-carrier radio transmission technology (1 xRTT), evolution-data optimized (EVDO), high speed packet access (HSPA), universal mobile telecommunications service (UMTS), 3G, long term evolution (LIE), 4G, and / or 5G, etc.), Bluetooth®, Bluetooth® low energy, Wi-Fi, radio, satellite, infrared connections, and / or ZigBee® communication protocols.

[0079] The Internet is an example of the communications network that constitutes an Internet Protocol (IP) network consisting of multiple computers, computing networks, and other communication devices located in multiple locations, and components in the communications network (e.g., computers, computing networks, communication devices) may be connected through one or more telephone systems and other means. Other examples of the communications network may include, without limitation, a standard Plain Old Telephone System (POTS), an Integrated Services Digital Network (ISDN), the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a wireless LAN (WLAN), a Session InitiationProtocol (SIP) network, a Voice over Internet Protocol (VoIP) network, a cellular network, and any other type of packet-switched or circuit-switched network known in the art. In some cases, the communications network may include of any combination of networks or network types. In some aspects, the communications network may include any combination of communication mediums such as coaxial cable, copper cable / wire, fiber-optic cable, or antennas for communicating data (e.g., transmitting / receiving data).

[0080] The computing device 102 may be connected to the cloud network 134 via the communication interface 108, using a wired connection, a wireless connection, or both. In some implementations, the computing device 102 may communicate with the database 130 and / or an external device (e.g., a computing device) via the cloud network 134.

[0081] The system 100 or similar systems may be used, for example, to carry out one or more aspects of any of the methods described herein. The system 100 or similar systems may also be used for other purposes.

[0082] Fig. 2 illustrates an example implementation 200 of the system 100 as supported by aspects of the present disclosure. Aspects of the system 100 previously described with reference to Fig. 1 and descriptions of like elements are omitted for brevity.

[0083] The system 100, in any suitable configuration, may be used to provide stimulation to a patient 148 and / or carry out one or more other aspects of one or more of the methods disclosed herein. For example, the system 100 may support providing a neuromodulation therapy (e.g., provide electric signals) to patient 148. The system 100 may include at least a device (e.g., computing device 102, therapy device 162, wearable device 170, etc.) that is capable of providing a stimulation applied to an anatomical element (e.g., spinal cord 149, lower thoracic spine) of the patient 148 and / or to one or more nerve endings for a patient 148 (e.g., least splanchnic nerve, etc.).

[0084] The configuration illustrated in Fig. 2 shows application of stimulation (e.g., neurostimulation, a neuromodulation therapy, etc.) and sensing of a response thereto. The system 100 may control delivery of stimulation to patient 148 based on one or more stimulation parameters 180. In some examples, the one or more stimulation parameters 180 may include duty cycle parameters associated with delivering stimulation to patient 148. The system 100 may maintain or update one or more stimulation parameters 180 (e.g., duty cycle parameters, etc.) in association with counteracting a physiological habituation of one or more physiologic processes of the patient 148 to the stimulation. In some aspects, the system 100 may maintain or update one or more stimulation parameters 180 (e.g., duty cycle parameters) in association with maintaining a value of one or more physiological parameters 184 associated with the patient 148 at or near a target value.

[0085] The stimulation parameters 180 illustrated and described herein may include any stimulation parameters (e.g., amplitude, frequency, duty cycle duration, etc.) appropriate for counteracting habituation and / or maintaining a physiological parameter (e.g., blood pressure, etc.) of the patient 148 at or near a target value in accordance with aspects of the present disclosure.

[0086] In some examples, the therapy device 162 may include a pulse generator 164 described with reference to Fig. 1. The pulse generator 164 may be configured to generate a current or therapeutic electrical signal, such as a signal capable of stimulating a response in the spinal cord 149 or from one or more nerves. In some implementations, as described herein, the therapy device 162 may be implanted within the patient 148.

[0087] Additionally, the system 100 may include one or more leads 168 (e.g., electrical leads) that provide a connection between the therapy device 162 and the spinal cord 149 or nerves of the patient 148 for enabling, for example, stimulation. In some implementations, the leads 168 may be implanted wholly or partially within the patient 148. Additionally, or alternatively, aspects of the present disclosure support one or more leadless implementations of the system 100 for use with the peripheral nervous system (e.g., nerves that branch out from the spinal cord 149 or brain 150 of a patient 148). For example, the system 100 may support the detection of physiologic signals associated with the peripheral nervous system using sensing techniques that are absent leads 168.

[0088] In an example implementation, the therapy device 162 may be a leadless devices capable of delivering stimulation therapy without the use of a separate lead (e.g., without the use of a lead 168 for delivering stimulation therapy). For example, the therapy device 162 may be a unitary structured device that may be more robust and less invasive than lead-based counterpart devices. In some aspects, a leadless implementation of the therapy device 162 may include one or more sensors or electrodes configured to sense nerve activity or muscle activity, and provide closed loop feedback for adjustment of a stimulation therapy regime.

[0089] In some implementations, such as the example illustrated in Fig. 2, the one or more leads 168 may include a lead 168-a disposed on or connected to a first side of the spinal cord 149 of the patient 148 and a lead 168-b disposed on or connected to a second side of the spinal cord 149 of the patient 148. For example, the lead 168-a may be connected to the righthand side of the spinal cord 149, while the lead 168-b may be connected to the lefthand side of the spinal cord 149. However, the position and / or orientation of each lead relative to the spinal cord 149 may vary depending on, for example, the type of treatment, the type of lead, combinations thereof, and the like.

[0090] In another example, the lead 168-a and the lead 168-b may overlap one another, and may be placed proximate one another on the dorsal side of the spinal cord 149 close to a midline of thespinal cord 149. In some examples, the lead 168-a and the lead 168-b may both be placed on the midline of the spinal cord 149, where one of the leads 168 is cranial (e.g., anterior or nearer the head of the patient 148) and the other of the leads 168 is caudal (e.g., posterior or nearer the tail of the patient 148). Additionally or alternatively, the lead 168-a and the lead 168-b may both be placed on one side of the midline of the spinal cord 149.

[0091] Additionally, the one or more leads 168 may be connected, placed, or otherwise implanted near or on the spinal cord 149 within the patient 148, such that at least one of the one or more leads 168 are located near the heart 151 of the patient 148. For example, though not illustrated, the lead 168-a may be placed within the spinal canal behind the heart 151 (e.g., dorsally within the spinal canal, such as behind a foramen of the spine near the top of a vertebra of the thoracic vertebrae column of the spinal cord 149, or anteriorly within the spinal canal). Additionally or alternatively, as described previously, the systems and techniques described herein support varying the exact placement of the one or more leads 168 depending on, for example, the type of treatment, the type of lead, the patient 148, combinations thereof, and the like.

[0092] While not specifically shown in the example of Fig. 2, the one or more leads 168 may also exit the spinal cord 149 at a lumbar vertebra lower down the spinal cord 149 (e.g., the L2 vertebra, but the exact location may vary). As described herein, the one or more leads 168 being placed proximate to the heart 151 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).

[0093] In other implementations, the one or more leads 168 may include at least the lead 168-a and the lead 168-b connected to other nerves of the patient 148 (e.g., the vagus nerve, different trunks of the vagus nerve, etc.). For example, the lead 168-a may be connected to a first nerve (e.g., first vagal trunk of the patient 148, such as the anterior sub diaphragmatic vagal trunk at the hepatic branching point of the vagus nerve) and the lead 168-b may be connected to a second nerve (e.g., second vagal trunk of the patient 148, such as the posterior sub diaphragmatic vagal trunk at the celiac branching point of the vagus nerve). The lead 168-a and / or the lead 168-b may be configured to provide an electrical stimulation signal from the therapy device 162 to the respective first and / or second nerve. The connection of the leads 168 to the respective nerve (or other nerves) of the patient 148 may permit the therapy device 162 to measure and / or stimulate one or more evoked potentials (e.g., ECAPs) in the patient 148 based on the provided electrical stimulation from the pulse generator 164.

[0094] Additionally, or alternatively, one lead 168 (e.g., lead 168-a) may be connected at or near the spinal cord 149 while another lead 168 (e.g., lead 168-c) may be connected at or near the brain150 of the patient 148. Such a configuration may be used to apply a neuromodulation therapy such as a Deep Brain Stimulation (DBS). While responses to the neuromodulation therapy may be measured using one or both of the leads 168-a and 168-c, cardiac activity may also be measured using traditional medical devices, and it should be appreciated that other types of devices can be used to measure cardiac activity.

[0095] In some example implementations, the therapy device 162 (with or without the wearable device 170) may calculate or measure any appropriate physiological parameters 184 associated with the patient 148, based on the provided electrical stimulation from the pulse generator 164. Nonlimiting examples of the one or more physiological parameters 184 include heart rate, blood pressure, body temperature, oxygen saturation, respiratory rate, muscle strength, metabolic rate, and hormonal levels. In an example, the computing device 102 may calculate physiological parameters 184 associated with one or more sympathetic nerves of the patient 148.

[0096] As a non-limiting example, wearable device 170 may be provided with one or more sensors that receive a data signal from the patient 148 and convert the received signal into a cardiac electrical signal (or other appropriate signal associated with measuring biometric data of the patient 148) . In other words, traditional medical devices (e.g., purpose-built ECG monitors, portable ECG monitors, etc.), wearable devices 170, or any other appropriate type of device may be used to measure cardiac activity or other types of biometric data. Outputs of such device(s) may be analyzed and used to provide stimulation parameters 184 (e.g., duty cycle, etc.), electrode configurations 186, and the like associated with delivering therapy to patient 148 and sensing a response.

[0097] In some examples, the leads 168 may provide therapeutic electrical signals to the respective nerves via electrodes 166 or electrode devices that are connected to the nerves (e.g., sutured in place, wrapped around the nerves, etc.). In some examples, the leads 168 may be referenced as cuff electrodes or may otherwise include the cuff electrodes (e.g., at an end of the leads 168 not connected or plugged into the therapy device 162). Examples of the electrodes 166 include electrode devices, cuff electrodes, paddle electrodes, or different types of electrodes, and electrodes 166 may be disposed at a distal end of each of the leads 168.

[0098] In other examples, the leads 168 may be or comprise linear SCS leads capable of delivering one or more stimulation signals (e.g., generated by the therapy device 162) to the spinal cord 149. The leads 168 may comprise a plurality of electrodes 166 disposed along the length of the lead, such that the leads 168 contact the spinal cord 149 at multiple points along a length of the spinal cord 149. A first set of the electrodes 166 on each lead may pass an electrical signal into the spinal cord 149, while a second set of the electrodes 166 on each lead may sense one or more signals generated inresponse by the spinal cord 149 (e.g., recorded signals). In one or more implementations, the electrodes 166 may be able to sense, measure, or otherwise collected data related to ECAPs (e.g., ECAP waveforms). Additionally or alternatively, the electrodes 166 may be able to sense, measure, or otherwise collected data related to cardiac metrics for the patient 148 (e.g., HR, HRV, respiration, or other ECG measurements). In some examples, the therapy device 162 may be used as a contact and / or may include additional contacts for sensing, measuring, or otherwise collecting data related to biometric data (e.g., cardiac metrics) for the patient 148. A plurality of the configurations can be used to record different vectors of biometric activity towards deriving various biometric metrics.

[0099] Additionally, the system 100 may include one or more processors 104 (e.g., one or more Digital Signal Processors (DSPs), general purpose microprocessors, graphics processing units, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), or other equivalent integrated or discrete logic circuitry) shown and described in Fig. 1 that are programmed to carry out one or more aspects of the present disclosure. In some examples, the one or more processors 104 may include a memory 106 or may be otherwise configured to perform the aspects of the present disclosure. For example, the one or more processors 104 may provide instructions to the therapy device 162, the leads 168, the electrodes 166, or other components of the system 100 not explicitly shown or described with reference to Fig. 2 for applying a neuromodulation therapy, stimulation, performing measurements (e.g., biometric measurements, cardiac metrics, ECAPs, etc.), and analyzing the same, as described herein. In some examples, the one or more processors 104 may be part of the therapy device 162 or part of a control unit for the system 100 (e.g., where the control unit is in communication with the therapy device 162 and / or other components of the system 100).

[0100] The therapy device 162 and / or wearable device 170 may be programmed to measure and record movements of the patient 148 (e.g., for the purpose of life, sleep, and activity tracking). For example, the therapy device 162 and / or wearable device 170 may comprise an accelerometer and / or other components that are designed to track and record movements of the patient 148 (e.g., whether the patient 148 is moving, not moving, laying down, standing up, running, walking, etc.). Additionally, the leads 168 and / or electrodes 166 disposed at the distal end of the leads 168 may be programmed to measure a physiological response of the patient 148. In some cases, the wearable device 170 may include one or more sensors or sensor arrays supportive of measuring blood pressure of the patient 148. In an example, the wearable device 170 may provide data 125-b to the computing device 102, and the data 125-b may include measured blood pressure and / or data based on which the computing device 102 may derive or calculate blood pressure, trends in blood pressure, and the like.

[0101] In some examples, the physiological response may comprise an evoked change in one or more physiological parameters (e.g., blood pressure, etc.) based on applying therapy (e.g., a therapeutic electrical signal, for example, a stimulation signal) generated by the therapy device 162 to the spinal cord 149 and / or to nearby nerves as described previously. In another example, the physiological response may include spontaneous activity (e.g., spontaneous physiological responses) by the patient 148. Additionally or alternatively, as described herein, the physiological response may comprise biometric data, for example, cardiac signals (e.g., HR, HRV, respiration, other cardiac electrogram-related measurements, etc.) of the patient 148, before, during, and after the therapeutic electrical signal is applied. In some examples, the therapy device 162 may be programmed to measure and record the biometric data (e.g., cardiac signals) via an electrode vector and / or electrodes 166 placed on an outer surface of the therapy device 162 and / or within the therapy device 162, in addition or alternative to the leads 168 and / or electrodes 166. Additionally or alternatively, an additional device (e.g., implanted within the patient 148, an external device, etc.) may be configured or programmed to record activity of the patient 148 representative of a physiological response and / or activity based on which a physiological response may be derived.

[0102] With reference to Figs. 1 and 2, example aspects are described that support treatment of hypertension, and in some example aspects, the treatment of hypertension using cycled spinal cord stimulation. In some aspects, the techniques described herein may include delivering cycled spinal cord stimulation in the thoracic spine (e.g., lower thoracic spine) / lumbar spine (e.g., upper lumbar spine).

[0103] The system 100 may support the communication of data 125 (e.g., data 125-a, data 125-b, etc.) between computing device 102, therapy device 162, and wearable device 170. In an example, the system 100 may support receiving a data signal 126 (e.g., data signal 126-a) from one or more sensors (e.g., an electrode 166, an accelerometer associated with therapy device 162, a sensor integrated or coupled to wearable device 170, etc.) associated with the system 100 in response to therapy delivered to patient 148. In an example, the computing device 102 may receive data signals 126 via therapy device 162 and / or wearable device 170. Additionally, or alternatively, the computing device 102, if integrated with the therapy device 162, may receive the data signals 126 directly from the electrodes 166.

[0104] In some aspects, the data signal 126 (e.g., data signal 126-a, data signal 126-b) may include data 125 (e.g., data 125-a, data 125-b) including values of physiological parameters 184 (e.g., heart rate, blood pressure, body temperature, oxygen saturation, respiratory rate, muscle strength,metabolic rate, hormonal levels, etc.). Additionally, or alternatively, the computing device 102 may calculate the values of the physiological parameters 184 based on the data 125.

[0105] In some aspects, the data signal 126 (e.g., data signal 126-a from therapy device 162) may include an evoked compound action potential (ECAP) signal or an evoked compound muscle action potential (ECMAP) signal. In some other cases, the data signal 126 may include both an ECAP signal and an ECMAP signal. For example, the data signal 126 may include a sacral evoked response (SER) (also referred to herein as a pelvic health electrically evoked response (PEER)) which may include components of both ECAP and ECMAP.

[0106] The therapy may include neuromodulation therapy. In some example implementations, the therapy may include spinal cord stimulation (SCS), deep brain stimulation (DBS), pelvic health stimulation (e.g., associated with urinary incontinence, fecal incontinence, pelvic pain, sexual dysfunction, and other pelvic floor disorders), or other appropriate stimulation. In some example implementations, the therapy may include cycled SCS, delivered to the thoracic spine (e.g., lower thoracic spine) / lumbar spine (e.g., upper lumbar spine).

[0107] The system 100 may support delivery of the therapy via the therapy device 162 and / or the wearable device 170. In some aspects, computing device 102 may provide a control signal 155 to the therapy device 162 and / or the wearable device 170 in association with delivering therapy to the patient 148. In another example, the wearable device 170 may provide a control signal (not illustrated) to the therapy device 162 in association with delivering therapy to the patient 148. The example therapy described herein with reference to Fig. 2 may include delivery of electrical stimulation, but is not limited thereto. For example, the therapy may include delivery of one or more pharmacological agents.

[0108] Fig. 3 illustrates an example view 300 of a stimulation signal 305 provided by a device (e.g., therapy device 162) and a response waveform 310 in accordance with example aspects of the present disclosure.

[0109] Referring to Fig. 3, the system 100 may support applying continuous stimulation at “STIM ON” to one or more anatomical elements (e.g., spinal cord 149, lower thoracic spine) of the patient 148 and / or to one or more nerve endings (e.g., least splanchnic nerve, etc.), which may result in increased blood pressure long term. In the example of Fig. 3, SCS is delivered continuously at a stimulation frequency of 20 Hz (600 ps pulse width) for 45 seconds.

[0110] Based on the delivered stimulation, the mean blood pressure is about 75 mm Hg and rises to about 83 mm Hg at the end of the recording. Accordingly, for example, aspects of the presentdisclosure support blood pressure rise with continuous SCS, with a transient decrease in blood pressure prior to the longer-term increase in blood pressure.

[0111] Fig. 4 illustrates an example view 400 of a stimulation signal 405 provided by a device (e.g., therapy device 162) and a response waveform 410 in accordance with example aspects of the present disclosure.

[0112] Aspects of the present disclosure include leveraging the example effect (e.g., transient decrease in blood pressure prior to the longer-term increase in blood pressure) described with reference to Fig. 3 to achieve a mean decrease in blood pressure of a patient 148. In an example, the system 100 may support duty-cycling the stimulation. For example, the system 100 may control delivery of the stimulation based on one or more duty cycle parameters.

[0113] Referring to the example of Fig. 4, the system 100 may control delivery of the stimulation in association with counteracting habituation and / or maintaining a physiological parameter (e.g., blood pressure, etc.) of the patient 148 at or near a target value. For example, the system 100 may implement duty cycling of the stimulation, such that the stimulation is repeatedly turned on for a defined period, then turned off for the same defined period or a different defined period.

[0114] In an example implementation, the stimulation (e.g., stimulation frequency of 20 Hz (600 ps pulse width)) is repeatedly turned on for 6 seconds, then turned off for 6 seconds. In another example implementation, referring to stimulation signal 405 of Fig. 4, the stimulation (e.g., stimulation frequency of 20 Hz (600 ps pulse width)) is repeatedly turned on for 6 seconds, then turned off for 9 seconds.

[0115] Referring to response waveform 410 of Fig. 4, the duty cycling of the stimulation in accordance with aspects of the present disclosure may result in an increased variability in the instantaneous blood pressure. In some aspects, the duty cycling of the stimulation may result in a reduction of the long term mean blood pressure.

[0116] The techniques described herein of duty cycling the stimulation account for habituation of the neural target, which provides advantages over other stimulation techniques (e.g., improved treatment effect). In some aspects, the system 100 may maintain or update the duty cycle parameters in association with counteracting a physiological habituation of one or more physiologic processes of the patient 148 to the stimulation. The system 100 may maintain or update the duty cycle parameters in association with maintaining a value of one or more physiological parameters (e.g., blood pressure, etc.) of the patient 148 at or near a target value.

[0117] The systems and techniques described herein may support configuring the duty cycle (e.g., configuring the ON / OFF durations) in an open-loop manner. For example, the systems andtechniques may support configuring the duty cycle based on a user input via computing device 102. In some alternative and / or additional aspects, the systems and techniques described herein may support configuring the duty cycle (e.g., configuring the ON / OFF durations) in a closed-loop manner. For example, the systems and techniques may support configuring the duty cycle in response to data provided by a measurement device (e.g., wearable device 170, a blood pressure sensor, etc.). In some examples, the data provided by the measurement device (and based on which the systems and techniques support configuring the duty cycle) may include a measure of sympathetic tone (e.g., cardiac sympathetic tone). In some cases, the data may include aspects of data 125-b described herein.

[0118] In some example implementations, the duty cycle durations may be equal to about 1 s, about 2 s, about 5 s, about 10 s, about 20 s, or about 50 seconds.

[0119] It is to be understood that the stimulation parameters (e.g., amplitude, frequency, duty cycle durations, etc.) illustrated and described herein may include any stimulation parameters appropriate for counteracting habituation and / or maintaining a physiological parameter (e.g., blood pressure, etc.) of the patient 148 at or near a target value in accordance with aspects of the present disclosure.

[0120] Fig. 5 illustrates an example of a process flow in accordance with aspects of the present disclosure. In some examples, the process flow may be implemented by aspects of system 100 (e.g., computing device 102, system 160, etc.) described with reference to Figs. 1 and 2.

[0121] In the following descriptions of the process flow, the operations may be performed in a different order than the order shown, or the operations may be performed in different orders or at different times. Certain operations may also be left out of the process flow, or one or more operations may be repeated, or other operations may be added to the process flow.

[0122] It is to be understood that any appropriate device (e.g., computing device 102, therapy device 162, wearable device 170, another device in communication with the computing device 102, therapy device 162, or wearable device 170, etc.) may perform the operations shown.

[0123] The process flow may be implemented by a system 100 including: a processor (e.g., processor 104) and a memory (e.g., memory 106) storing data thereon that, when processed by the processor, cause the processor to perform one or more operations of the process flow.

[0124] At 505, the process flow 500 may include controlling delivery of stimulation to a patient based on one or more duty cycle parameters. For example, via a therapy device (e.g., therapy device 162 of Fig. 1), the system 100 may deliver the stimulation to one or more anatomical elements of a patient based on the one or more duty cycle parameters.

[0125] In some aspects, the one or more duty cycle parameters include a temporal duration, wherein the temporal duration is equal to about 1 second, about 2 seconds, about 5 seconds, about 10 seconds, about 20 seconds, or about 50 seconds.

[0126] In some aspects, the stimulation includes neurostimulation.

[0127] In some aspects, the stimulation is delivered to one or more anatomical elements of the patient, wherein the one or more anatomical elements include one or more spinal nerves.

[0128] In some aspects, the one or more duty cycle parameters include: duty cycle timing; duration of stimulation ON; duration of stimulation OFF; a percentage of electrical pulses to be suppressed; and a quantity of the electrical pulses to be suppressed.

[0129] In some aspects, delivering the stimulation includes delivering a plurality of electrical pulses based on the one or more duty cycle parameters. In an example, the plurality of electrical pulses are delivered based on one or more stimulation parameters, wherein the one or more stimulation parameters include signal frequency and signal amplitude.

[0130] At 510, the process flow 500 may include calculating the value of one or more physiological parameters associated with the patient. In an example, the process flow 500 may include receiving a data signal from one or more sensors included in the system, determining a plurality of measurement values of the one or more physiological parameters based on the data signal, and calculating the value (e.g., mean value, average value, etc.) of the one or more physiological parameters based on the plurality of measurement values.

[0131] At 515, the process flow 500 may include maintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

[0132] In an example, at 520, the process flow 500 may include comparing the value of the one or more physiological parameters to the target value. In some aspects, maintaining or updating the one or more duty cycle parameters is based on a result of the comparing.

[0133] In an example, at 525, the process flow 500 may include calculating a difference value between the value of the one or more physiological parameters and the target value, wherein maintaining or updating the one or more duty cycle parameters is based on the difference value.

[0134] In some aspects, the one or more physiological parameters include blood pressure of the patient.

[0135] In some aspects, the one or more physiological parameters are associated with one or more sympathetic nerves of the patient.

[0136] In some aspects, the value of the one or more physiological parameters includes a mean value or average value of the one or more physiological parameters with respect to a temporal duration.

[0137] In some aspects, the habituation includes a physiological habituation of one or more physiologic processes of the patient to the stimulation.

[0138] In some aspects, the value of the one or more physiological parameters is calculated with respect to a temporal duration; and the temporal duration includes one or more instances of delivering the stimulation.

[0139] In some aspects, maintaining or updating the one or more duty cycle parameters is based on a user input.

[0140] In some aspects, the system 100 may include a controller that controls the one or more duty cycle parameters and one or more stimulation parameters in association with delivering the stimulation.

[0141] In some aspects, the system 100 may include a device to at least one of: deliver the stimulation based on the one or more duty cycle parameters; and calculate the value of the one or more physiological parameters based on a data signal received from one or more sensors included in the system. In some examples, the device includes at least one of a medical device, a wearable device, and an implanted device.

[0142] In some aspects, the system 100 may further include: a pulse generator configured to generate the stimulation; and at least one electrode in communication with the pulse generator to deliver the stimulation. In some aspects, the at least one electrode includes: a first electrode to deliver the stimulation; and a second electrode to sense a response to the stimulation.

[0143] The process flow (and / or one or more operations thereof) described herein 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) 104 of the computing device 102 described above. The at least one processor may be part of system 160, therapy device 162, or wearable device 170. A processor other than any processor described herein may also be used to execute the process flow. The at least one processor may perform operations of the process flow by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more operations of a function as shown in the process flow. One or more portions of the process flow may be performed by the processor executing any of the contents of memory.

[0144] As noted above, the present disclosure encompasses methods with fewer than all of the steps identified the method(s) and process flow(s) described herein The present disclosure also encompasses methods that include 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 include a registration or any other correlation.

[0145] 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, implementations, and / or configurations for the purpose of streamlining the disclosure. The features of the aspects, implementations, and / or configurations of the disclosure may be combined in alternate aspects, implementations, and / or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects he in less than all features of a single foregoing disclosed aspect, implementation, 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 implementation of the disclosure.

[0146] Moreover, though the foregoing has included description of one or more aspects, implementations, 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, implementations, 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.

[0147] The phrases “at least one,” “one or more,” “or,” 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,” “A, B, and / or C,” and “A, B, 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.

[0148] 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.

[0149] The term “automatic” and variations thereof, as used herein, refers to any process or operation, which is typically continuous or semi-continuous, done without material human input when the process or operation is performed. However, a process or operation can be automatic, even though performance of the process or operation uses material or immaterial human input, if the input is received before performance of the process or operation. Human input is deemed to be material if such input influences how the process or operation will be performed. Human input that consents to the performance of the process or operation is not deemed to be “material.”

[0150] Aspects of the present disclosure may take the form of an implementation that is entirely hardware, an implementation that is entirely software (including firmware, resident software, microcode, etc.) or an implementation combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module,” or “system.” Any combination of one or more computer- readable medium(s) may be utilized. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium.

[0151] A computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non- exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0152] A computer-readable signal medium may include a propagated data signal with computer- readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electromagnetic, optical, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including, but not limited to, wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0153] The terms “determine,” “calculate,” “compute,” and variations thereof, as used herein, are used interchangeably and include any type of methodology, process, mathematical operation or technique.

[0154] This disclosure is further described in connection with the following examples.

[0155] Example 1. A system comprising: a processor; and a memory storing instructions thereon that, when executed by the processor, cause the processor to: control delivery of stimulation to a patient based on one or more duty cycle parameters; and maintain or update the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

[0156] Example 2. The system of example 1, wherein the value of the one or more physiological parameters comprises a mean value or average value of the one or more physiological parameters with respect to a temporal duration.

[0157] Example 3. The system of example 1, wherein the habituation comprises a physiological habituation of one or more physiologic processes of the patient to the stimulation.

[0158] Example 4. The system of example 1, wherein the instructions are further executable by the processor to: compare the value of the one or more physiological parameters to the target value, wherein maintaining or updating the one or more duty cycle parameters is based on a result of the comparing.

[0159] Example 5. The system of example 1, wherein the instructions are further executable by the processor to: calculate the value of the one or more physiological parameters associated with the patient.

[0160] Example 6. The system of example 1, wherein the instructions are further executable by the processor to: calculate a difference value between the value of the one or more physiological parameters and the target value, wherein maintaining or updating the one or more duty cycle parameters is based on the difference value.

[0161] Example 7. The system of example 1, wherein: the value of the one or more physiological parameters is calculated with respect to a temporal duration; and the temporal duration comprises one or more instances of delivering the stimulation.

[0162] Example 8. The system of example 1, wherein the one or more duty cycle parameters comprise a temporal duration, wherein the temporal duration is equal to about 1 second, about 2 seconds, about 5 seconds, about 10 seconds, about 20 seconds, or about 50 seconds.

[0163] Example 9. The system of example claim 1, wherein the stimulation comprises neurostimulation.

[0164] Example 10. The system of example 1, wherein the one or more physiological parameters comprise blood pressure of the patient.

[0165] Example 11. The system of example 1, wherein the one or more physiological parameters are associated with one or more sympathetic nerves of the patient.

[0166] Example 12. The system of example 1, wherein the stimulation is delivered to one or more anatomical elements of the patient, wherein the one or more anatomical elements comprise one or more spinal nerves.

[0167] Example 13. The system of example 1, wherein the one or more duty cycle parameters comprise: duty cycle timing; duration of stimulation ON; duration of stimulation OFF; a percentage of electrical pulses to be suppressed; and a quantity of the electrical pulses to be suppressed.

[0168] Example 14. The system of example 1, wherein the system further comprises a controller that controls the one or more duty cycle parameters and one or more stimulation parameters in association with delivering the stimulation.

[0169] Example 15. The system of example 1, wherein delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters.

[0170] Example 16. The system of example 15, wherein: the plurality of electrical pulses are delivered based on one or more stimulation parameters, wherein the one or more stimulation parameters comprise signal frequency and signal amplitude.

[0171] Example 17. The system of example 1, wherein maintaining or updating the one or more duty cycle parameters is based on a user input.

[0172] Example 18. The system of example 1, wherein the instructions are further executable by the processor to: receive a data signal from one or more sensors comprised in the system; determine a plurality of measurement values of the one or more physiological parameters based on the data signal; and calculate the value of the one or more physiological parameters based on the plurality of measurement values.

[0173] Example 19. The system of example 1, further comprising a device to at least one of: deliver the stimulation based on the one or more duty cycle parameters; and calculate the value based on a data signal received from one or more sensors comprised in the system.

[0174] Example 20. The system of example 19, wherein the device comprises at least one of a medical device, a wearable device, and an implanted device.

[0175] Example 21. The system of example 1, further comprising: a pulse generator configured to generate the stimulation; and at least one electrode in communication with the pulse generator to deliver the stimulation.

[0176] Example 22. The system of example 21, wherein the at least one electrode comprises: a first electrode to deliver the stimulation; and a second electrode to sense a response to the stimulation.

[0177] Example 23. A device for providing therapy, the device comprising: one or more electrodes; and a controller device that controls one or more duty cycle parameters in association with delivering stimulation to one or more anatomical elements via the one or more electrodes, wherein providing the therapy comprises: delivering the stimulation to the one or more anatomical elements of a patient based on the one or more duty cycle parameters; maintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

[0178] Example 24. A method comprising: delivering stimulation to a patient based on one or more duty cycle parameters, wherein delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters; and maintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

Claims

CLAIMSWhat is claimed is:

1. A system comprising: a processor; and a memory storing instructions thereon that, when executed by the processor, cause the processor to: control delivery of stimulation to a patient based on one or more duty cycle parameters; and maintain or update the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

2. The system of claim 1, wherein the value of the one or more physiological parameters comprises a mean value or average value of the one or more physiological parameters with respect to a temporal duration.

3. The system of claim 1, wherein the habituation comprises a physiological habituation of one or more physiologic processes of the patient to the stimulation.

4. The system of claim 1, wherein the instructions are further executable by the processor to: compare the value of the one or more physiological parameters to the target value, wherein maintaining or updating the one or more duty cycle parameters is based on a result of the comparing.

5. The system of claim 1, wherein the instructions are further executable by the processor to: calculate the value of the one or more physiological parameters associated with the patient.

6. The system of claim 1, wherein the instructions are further executable by the processor to: calculate a difference value between the value of the one or more physiological parameters and the target value, wherein maintaining or updating the one or more duty cycle parameters is based on the difference value.

7. The system of claim 1 , wherein: the value of the one or more physiological parameters is calculated with respect to a temporal duration; and the temporal duration comprises one or more instances of delivering the stimulation.

8. The system of claim 1, wherein the one or more duty cycle parameters comprise a temporal duration, wherein the temporal duration is equal to about 1 second, about 2 seconds, about 5 seconds, about 10 seconds, about 20 seconds, or about 50 seconds.

9. The system of claim 1 , wherein the stimulation comprises neurostimulation.

10. The system of claim 1, wherein the one or more physiological parameters comprise blood pressure of the patient.

11. The system of claim 1, wherein the one or more physiological parameters are associated with one or more sympathetic nerves of the patient.

12. The system of claim 1, wherein the stimulation is delivered to one or more anatomical elements of the patient, wherein the one or more anatomical elements comprise one or more spinal nerves.

13. The system of claim 1, wherein the one or more duty cycle parameters comprise: duty cycle timing; duration of stimulation ON; duration of stimulation OFF; a percentage of electrical pulses to be suppressed; and a quantity of the electrical pulses to be suppressed.

14. The system of claim 1, wherein the system further comprises a controller that controls the one or more duty cycle parameters and one or more stimulation parameters in association with delivering the stimulation.

15. The system of claim 1, wherein delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters.

16. The system of claim 15, wherein: the plurality of electrical pulses are delivered based on one or more stimulation parameters, wherein the one or more stimulation parameters comprise signal frequency and signal amplitude.

17. The system of claim 1, wherein maintaining or updating the one or more duty cycle parameters is based on a user input.

18. The system of claim 1, wherein the instructions are further executable by the processor to: receive a data signal from one or more sensors comprised in the system; determine a plurality of measurement values of the one or more physiological parameters based on the data signal; and calculate the value of the one or more physiological parameters based on the plurality of measurement values.

19. A device for providing therapy, the device comprising: one or more electrodes; and a controller device that controls one or more duty cycle parameters in association with delivering stimulation to one or more anatomical elements via the one or more electrodes, wherein providing the therapy comprises: delivering the stimulation to the one or more anatomical elements of a patient based on the one or more duty cycle parameters; maintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

20. A method comprising: delivering stimulation to a patient based on one or more duty cycle parameters, wherein delivering the stimulation comprises delivering a plurality of electrical pulses based on the one or more duty cycle parameters; andmaintaining or updating the one or more duty cycle parameters in association with counteracting habituation and maintaining a value of one or more physiological parameters associated with the patient at or near a target value.

Images