CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63/420,278, filed on October 28, 2022, which application is incorporated herein by reference in its entirety.

BACKGROUND

[0002] The present disclosure is generally directed to electrical stimulation therapy and, in particular, relates to deep brain stimulation (DBS) therapy.

[0003] Medical devices may be external or implanted, and may be used to deliver electrical stimulation therapy to various tissue sites of a patient to treat a variety of symptoms or conditions such as chronic pain, tremor, Parkinson’s disease, other movement disorders, epilepsy, urinary or fecal incontinence, sexual dysfunction, obesity, or gastroparesis. A medical device delivers electrical stimulation therapy via one or more leads that include electrodes located proximate to target locations associated with the brain, the spinal cord, pelvic nerves, peripheral nerves, or the gastrointestinal tract of a patient. Electrical stimulation is used in different therapeutic applications, such as DBS, spinal cord stimulation (SCS), pelvic stimulation, gastric stimulation, or peripheral nerve field stimulation (PNFS).

BRIEF SUMMARY

[0004] Example aspects of the present disclosure include:

[0005] A system for detecting a neural state change for DBS, comprising: a signal generator configured to generate an electrical stimulation signal; one or more leads coupled to the signal generator, the one or more leads configured to carry the generated electrical stimulation signal to an anatomical element of a patient; a respective plurality of electrodes disposed at distal ends of the one or more leads, the respective plurality of electrodes configured to be implanted in the anatomical element and to apply the generated electrical stimulation signal to the anatomical element based at least in part on being implanted in the anatomical element; a processor; and a memory storing data for processing by the processor. In some embodiments, the data, when processed, may cause the processor to: cause the signal generator to provide the generated electrical stimulation signal to the anatomical element via the one or more leads and the respective plurality of electrodes at a first time instance based at least in part on a plurality of stimulation parameters; monitor for a sensed signal based at least in part on applying the generated electrical stimulation signal using the plurality of stimulation parameters, the sensed signal comprising an evoked response of applying the generated electrical stimulation signal; determine a neural state is present for the patient based at least in part on the sensed signal; and cause the signal generator to provide the generated electrical stimulation signal to the anatomical element via the one or more leads and the respective plurality of electrodes at a subsequent time instance to the first time instance based at least in part on one or more stimulation parameters, the one or more stimulation parameters corresponding to the determined neural state.

[0006] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: determine respective stimulation parameters for each of a plurality of neural states, the respective stimulation parameters being configured for providing the generated electrical stimulation signal to the anatomical element when a corresponding neural state is determined to be present for the patient.

[0007] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: monitor for an additional instance of the sensed signal subsequent to applying the generated electrical stimulation signal to the anatomical element using the one or more stimulation parameters that correspond to the determined neural state; determine a neural state change from the determined neural state to an additional neural state of the plurality of neural states based at least in part on the additional instance of the sensed signal; and cause the signal generator to provide the generated electrical stimulation signal to the anatomical element via the one or more leads and the respective plurality of electrodes using one or more additional stimulation parameters of the respective stimulation parameters based at least in part on the determined neural state change, the one or more additional stimulation parameters corresponding to the additional neural state.

[0008] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: transmit a notification to a user interface accessible by the patient based at least in part on the determined neural state change. [0009] Any of the aspects herein, wherein the neural state change is determined based at least in part on a detected shift in resonant frequency from the additional instance of the sensed signal, a peak-to-trough amplitude of the additional instance of the sensed signal, a damping of the additional instance of the sensed signal, a number of resonant peaks of the additional instance of the sensed signal, or a combination thereof.

[0010] Any of the aspects herein, wherein the one or more parameters are selected from the respective stimulation parameters for applying the generated electrical stimulation signal based at least in part on determining the neural state is present for the patient.

[0011] Any of the aspects herein, wherein the respective stimulation parameters comprise a frequency, an amplitude, a pulse width, a stimulation electrode, additional parameters, or a combination thereof for applying the generated electrical stimulation signal when the corresponding neural state is determined to be present for the patient. [0012] Any of the aspects herein, wherein the plurality of neural states comprises an awake state, an asleep state, an on-medication state, an off-medication state, a depth of anesthesia state, a disease progression state, a medication wash-in state, a medication wash-out state, a movement state, a posture of the patient, or a different neural state.

[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 feedback after the generated electrical stimulation signal is applied using the one or more stimulation parameters corresponding to the determined neural state; adjust one or more parameters of the one or more stimulation parameters based at least in part on the received feedback; and cause the signal generator to provide the generated electrical stimulation signal to the anatomical element via the one or more leads and the respective plurality of electrodes based at least in part on the one or more adjusted parameters for subsequent instances of when the neural state is determined to be present for the patient.

[0014] Any of the aspects herein, wherein the one or more parameters are adjusted autonomously by the signal generator based at least in part on a deep learning model and/or a pre-determined algorithm, manually by a clinician and/or the patient, or a combination thereof.

[0015] Any of the aspects herein, wherein the feedback comprises an input received from the patient indicating a level of satisfaction the patient experiences when the generated electrical stimulation signal is applied to the anatomical element using the one or more stimulation parameters for the determined neural state, information received from an accelerometer, a snapshot of the sensed signal, symptom biomarkers, or a combination thereof.

[0016] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: calculate a steady state behavior for the sensed signal, wherein the plurality of stimulation parameters is determined based at least in part on the steady state behavior.

[0017] Any of the aspects herein, wherein the neural state is determined to be present for the patient based at least in part on detecting a change in the sensed signal from the steady state behavior.

[0018] Any of the aspects herein, wherein the data stored in the memory that, when processed causes the processor to monitor for the sensed signal causes the system to: cause the signal generator to provide the generated electrical stimulation signal to the anatomical element via the one or more leads and the respective plurality of electrodes using a burst of a plurality of pulses; cause the signal generator to pause application of the generated electrical stimulation signal after the burst of the plurality of pulses for a time duration; and capture a neural response of the patient during the time duration, wherein the sensed signal comprises the neural response.

[0019] Any of the aspects herein, wherein the sensed signal comprises an evoked resonant neural activity signal, a local field potential signal, a high-frequency oscillations signal, or a combination thereof.

[0020] Any of the aspects herein, wherein the anatomical element comprises a brain of the patient.

[0021] Any of the aspects herein, wherein the signal generator is a part of an implantable medical device, a programmer, or both.

[0022] A system for detecting a neural state change for DBS, comprising: a processor and a memory storing data for processing by the processor, the data, when processed, causes the processor to: transmit instructions to provide an electrical stimulation signal to an anatomical element of a patient at a first time instance using a plurality of stimulation parameters; monitor for a sensed signal based at least in part on applying the electrical stimulation signal using the plurality of stimulation parameters, the sensed signal comprising an evoked response of applying the generated electrical stimulation signal; determine a neural state is present for the patient based at least in part on the sensed signal; and transmit instructions to provide the electrical stimulation signal to the anatomical element at a subsequent time instance to the first time instance using one or more stimulation parameters, the one or more stimulation parameters corresponding to the determined neural state.

[0023] Any of the aspects herein, wherein the memory stores further data for processing by the processor that, when processed, causes the processor to: determine respective stimulation parameters for each of a plurality of neural states, the respective stimulation parameters being configured for applying the electrical stimulation signal to the anatomical element when a corresponding neural state is determined to be present for the patient.

[0024] A system for detecting a neural state change for DBS, comprising: a signal generator configured to generate an electrical stimulation signal; one or more leads coupled to the signal generator, the one or more leads configured to carry the generated electrical stimulation signal to an anatomical element of a patient; and a respective plurality of electrodes disposed at distal ends of the one or more leads, the respective plurality of electrodes configured to be implanted in the anatomical element and to apply the generated electrical stimulation signal to the anatomical element based at least in part on being implanted in the anatomical element, wherein the signal generator is configured to provide the generated electrical stimulation signal to the anatomical element via the one or more leads and the respective plurality of electrodes based at least in part on one or more stimulation parameters corresponding to a neural state of the patient.

[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 Xl-Xn, Yl-Ym, and Zl-Zo, the phrase is intended to refer to a single element selected from X, Y, and Z, a combination of elements selected from the same class (e.g., XI and X2) as well as a combination of elements selected from two or more classes (e.g., Y1 and Zo).

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

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

[0036] Numerous additional features and advantages of the present disclosure will become apparent to those skilled in the art upon consideration of the embodiment descriptions provided hereinbelow.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS [0037] The accompanying drawings are incorporated into and form a part of the specification to illustrate several examples of the present disclosure. These drawings, together with the description, explain the principles of the disclosure. The drawings simply illustrate preferred 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. l is a diagram of a system according to at least one embodiment of the present disclosure;

[0039] Fig. 2 is a block diagram of an example implantable medical device (IMD) according to at least one embodiment of the present disclosure;

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

[0041] Fig. 4 is an example stimulation response according to at least one embodiment of the present disclosure;

[0042] Fig. 5 is an example stimulation response recording for a medication wash-in according to at least one embodiment of the present disclosure;

[0043] Fig. 6 is an example stimulation response recording for a medication application according to at least one embodiment of the present disclosure;

[0044] Fig. 7 is an example stimulation response recording for a medication wash-out according to at least one embodiment of the present disclosure;

[0045] Fig. 8 is a flowchart according to at least one embodiment of the present disclosure;

[0046] Fig. 9 is a flowchart according to at least one embodiment of the present disclosure; and

[0047] Fig. 10 is a flowchart according to at least one embodiment of the present disclosure.

DETAILED DESCRIPTION

[0048] 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.

[0049] 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).

[0050] 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; 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 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. The processors listed herein are not intended to be an exhaustive list of all possible processors that can be used for implementation of the described techniques, and any future iterations of such chips, technologies, or processors may be used to implement the techniques and embodiments of the present disclosure as described herein.

[0051] 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.

[0052] The terms proximal and distal are used in this disclosure with their conventional medical meanings, proximal being closer to the operator, user, or device of a system, and further from the region of medical interest in or on the patient, and distal being closer to the region of medical interest in or on the patient, and further from the operator, user, or device of the system.

[0053] This disclosure describes example techniques to optimize stimulation parameters for a therapeutic electrical stimulation signal to promote and influence either constructive or destructive resonance of an evoked resonant neural activity (ERNA) signal. The example techniques are described with respect to deep brain stimulation (DBS), but the example techniques are not so limited and may be applied to other types of therapies and/or other anatomical locations. DBS may provide relief for many different patient conditions such as essential tremors (ETs), Parkinson’s, obsessive compulsive disorder (OCD), depression, and others. For DBS, a surgeon implants one or more leads within the brain of the patient for outputting therapeutic electrical stimulation signals at depth within the brain. The one or more leads are coupled to an implantable medical device (IMD) that generates the therapeutic electrical stimulation signals for delivery through the one or more leads.

[0054] A common target for DBS (e.g., to treat Parkinson’s Disease or another condition) is the subthalamic nucleus (STN) (e.g., within the patient’s brain). In some examples, DBS therapy may incorporate sensing of local field potentials (LFPs) which are spontaneous activity representing background activity of the neural network. For example, an LFP may be an intrinsic signal within the brain of the patient. In some cases, the LFP is intrinsically generated by a signal source within the brain of the patient. The signal characteristics of the LFP may be indicative of a patient condition (e.g., brain state). [0055] Additionally or alternatively, another potential signal of interest for DBS therapy may include evoked activity. A single stimulation pulse of the therapeutic electrical stimulation signals may elicit an evoked potential (EP) response due to activation of the local neural circuitry. However, due to the complex interconnected neural network within the brain (e.g., of the basal ganglia), stimulation of the STN may activate the complex interconnected neural network such that sensing EPs in the STN will show the response to that pulse in addition to any additional feedback or underlying activity from connected structures in the brain network (e.g., in the basal ganglia network) that are also activated. When multiple stimulation pulses are delivered for the therapeutic electrical stimulation signals, the EP elicited from each pulse can add to the underlying activity from the feedback from the complex neural network activated by previous pulses.

[0056] With consecutive stimulation pulses, a sensed signal from the DBS therapy (e.g., which equals the EP from each pulse plus underlying ongoing activity from previous pulses) may show a resonant behavior, referred to as ERNA. For example, an ERNA signal is not an intrinsic signal within the brain of the patient, but is evoked due to a stimulation signal being delivered to the brain. The stimulation signal delivered to the brain that evokes the ERNA signal need not necessarily provide any therapeutic benefit, although it is possible for the stimulation signal that evokes the ERNA signal to provide therapeutic benefit. In some examples, ERNA could be an electrically evoked version of high frequency oscillations (HFO). HFOs may be brain waves with a frequency faster than approximately 80 Hertz (Hz) (e.g., generated by neuronal cell population). Additionally, HFOs can be recorded during an electroencephalagram (EEG), LFP, or electrocorti cogram (ECoG) electrophysiology recordings.

[0057] As described herein, having the ability to detect changes in a neural state of a patient (e.g., such as asleep or awake, whether the patient is on a medication, a depth of anesthesia, disease progression, whether the patient is moving or not, whether the patient is upright or laying down, etc.) is important to inform any needed adjustments to DBS therapy stimulation parameters (e.g., adjust a stimulation frequency, amplitude, pulse width, etc., based on a given neural state of the patient). Additionally, being able to detect neural changes in the patient may enable a DBS therapy system to automatically adjust the stimulation settings to optimize the DBS therapy for the patient. [0058] In some embodiments, sensing EPs elicited by DBS can give a direct measure of how the neural target is responding to the stimulation. As described previously, EPs from stimulation of the STN can start to show resonant properties (e.g., ERNA) due to the complex neural circuitry and underlying feedback from the network. While properties of the ERNA response (e.g., such as a peak-to-trough amplitude, peak latencies, damping, resonant frequency, etc.) are dependent on stimulation parameters (e.g., such as stimulation electrode, frequency, and amplitude), certain properties of a steady state ERNA signal also change as neural state changes for a patient (e.g., a detected shift in resonant frequency, a change in a peak-to-trough amplitude, a damping, a change in a number of resonant peaks, etc.). Accordingly, as described herein, changes in an ERNA signal could be used to detect neural state changes for a patient, including but not limited to: asleep/awake, depth of anesthesia, medication wash in/out, disease progression, a movement state (e.g., whether the patient is moving or not, such as indicated by an accelerometer), and a posture of the patient (e.g., upright, laying down, etc.). Additionally or alternatively, additional signals or measurements may be used (e.g., instead of or in addition to the ERNA signal) to detect neural state changes. For example, LFP sensing may indicate spontaneous neural network activity that can change with neural state, and/or HFOs (e.g., between approximately 200Hz and approximately 400Hz) may change with a neural state of the patient (e.g., different values when the patient is on medications or not on medications).

[0059] Subsequently, ERNA changes (e.g., and/or the other signal or measurement changes) can be used to inform a clinician and/or the patient of neural state changes to initiate one or more actions. For example, a clinician decision may be initiated based on the neural state change as indicated by the ERNA changes, such as monitoring anesthesia depth of the patient. Additionally or alternatively, a patient action may be initiated based on the neural state change as indicated by the ERNA changes, such as determining to take medications if a medication wash-out is detected. Additionally or alternatively, an automatic change in DBS settings may be initiated (e.g., as part of a closed-loop system) based on the neural state change as indicated by the ERNA changes, such as switching DBS settings between pre-programmed groups based on a detected neural state or a neural state change. Additional actions not expressly listed herein may be performed based on detecting a neural state or neural state change as informed by ERNA changes, LFP changes, HFO changes, etc. [0060] Fig. 1 is a conceptual diagram illustrating an example system 100 that includes an implantable medical device (IMD) 106 configured to deliver a DBS therapy to a patient 112. In some examples, the DBS may be closed-loop in the sense that IMD 106, as one example, may adjust, increase, or decrease the magnitude of one or more parameters of the DBS in response to changes in patient activity or movement, a severity of one or more symptoms of a disease of the patient, a presence of one or more side effects due to the DBS, or one or more sensed signals of the patient.

[0061] For instance, one example of system 100 is a bi-directional DBS system with capabilities to both deliver stimulation, sense intrinsic neuronal signals, and sense neural signals that are evoked in response to delivery of stimulation. System 100 may be configured to treat a patient condition, such as a movement disorder (e.g., ET, Parkinson’s, etc.), neurodegenerative impairment, a mood disorder, or a seizure disorder of patient 112. Patient 112 ordinarily is a human patient. In some cases, however, therapy system 100 may be applied to other mammalian or non-mammalian, non-human patients. While movement disorders and neurodegenerative impairment are primarily referred to herein, in other examples, therapy system 100 may provide therapy to manage symptoms of other patient conditions, such as, but not limited to, seizure disorders (e.g., epilepsy) or mood (or psychological) disorders (e.g., major depressive disorder (MDD), bipolar disorder, anxiety disorders, post-traumatic stress disorder, dysthymic disorder, and obsessive- compulsive disorder (OCD)). At least some of these disorders may be manifested in one or more patient movement behaviors. As described herein, a movement disorder or other neurodegenerative impairment may include symptoms such as, for example, muscle control impairment, motion impairment or other movement problems, such as rigidity, spasticity, bradykinesia, rhythmic hyperkinesia, nonrhythmic hyperkinesia, and akinesia. In some cases, the movement disorder may be a symptom of Parkinson’s disease or ET. However, the movement disorder may be attributable to other patient conditions.

[0062] Example therapy system 100 includes medical device programmer 104, IMD 106, lead extension 110, and leads 114A and 114B with respective sets of electrodes 116, 118. In the example shown in FIG. 1, electrodes 116, 118 of leads 114 A, 114B are positioned to deliver electrical stimulation to a tissue site within brain 120, such as a deep brain site under the dura mater of brain 120 of patient 112. In some examples, delivery of stimulation to one or more regions of brain 120, such as the STN, globus pallidus or thalamus, ventralus intermediate (VIM), anterior nucleus (ANT), ventral internal capsule/ventral striatum (VCVS), cortico-basal ganglia-thalamocortical circuit, or anterior insular cortex (AIC), may be an effective treatment to manage disorders, such as Parkinson’s disease. Some or all of electrodes 116, 118 also may be positioned to sense neurological brain signals within brain 120 of patient 112. In some examples, some of electrodes 116, 118 may be configured to sense neurological brain signals and others of electrodes 116, 118 may be configured to deliver electrical stimulation to brain 120. In other examples, all of electrodes 116, 118 are configured to both sense neurological brain signals and deliver electrical stimulation to brain 120. In some examples, unipolar stimulation may be possible where one electrode is on the housing of IMD 106.

[0063] IMD 106 includes a therapy module (e.g., which may include processing circuitry or other electrical circuitry configured to perform the functions attributed to IMD 106) that includes stimulation generation circuitry configured to generate and deliver electrical stimulation therapy to patient 112 via a subset of electrodes 116, 118 of leads 114A and 114B, respectively. The subset of electrodes 116, 118 that are used to deliver electrical stimulation to patient 112, and, in some cases, the polarity of the subset of electrodes 116, 118, may be referred to as a stimulation electrode combination. As described in further detail below, the stimulation electrode combination can be selected for a particular patient 112 and target tissue site (e.g., selected based on the patient condition). The group of electrodes 116, 118 includes at least one electrode and can include a plurality of electrodes. In some examples, the plurality of electrodes 116 and/or 118 may have a complex electrode geometry such that two or more electrodes are located at different positions around the perimeter of the respective lead.

[0064] In some examples, the neurological signals sensed within brain 120 may reflect changes in electrical current produced by the sum of electrical potential differences across brain tissue. There may be various examples of neurological brain signals that electrodes 116, 118 may be configured to sense. One example of a neurological brain signal is an LFP. An LFP may be an intrinsic signal within brain 120 of patient 112 that is generated by a signal source within brain 120 of patient 112. Another example of a neurological brain signal is an ERNA signal. Delivery of electrical stimulation within brain 120 may evoke an ERNA signal, and the ERNA signal may not be an intrinsic signal. The electrical stimulation delivered within brain 120 to evoke the ERNA signal need not necessarily provide therapeutic benefit, but therapeutic benefit from the electrical stimulation used to evoke the ERNA signal is possible. Electroencephalogram (EEG) signal or an electrocorti cogram (ECoG) signal are also examples of neurological signals. For example, neurons generate the neurological signals, and if measured at depth, it is LFP or ERNA (if evoked), if measured on the dura, it is ECoG, and if on scalp, it is EEG.

[0065] In some examples, the delivery of therapeutic electrical stimulation signals may be based on a feature of interest (e.g., biomarker). One example of the feature of interest (e.g., biomarker) within the LFPs is synchronized beta frequency band (8-33Hz) LFP activity recorded within the sensorimotor region of the STN in Parkinson’s disease or ET patients. The source of the LFP activity can be considered as a signal source, within the brain of the patient, that outputs an oscillatory electrical voltage signal that is sensed by one or more of electrodes 116 and/or 118. The suppression of pathological beta activity (e.g., suppression or squelching of the signal component of the bioelectric signals generated from the LFP source that is within the beta frequency band) by both medication and DBS may correlate with improvements in the motor symptoms of patients who have Parkinson’s disease or essential tremor.

[0066] For example, one or more of electrodes 116 and/or 118 may sense the LFP activity. Accordingly, there may be a plurality of LFP measurements of an LFP, where each of the LFP measurements may be measured with different electrodes 116 and/or 118 on leads 114A, 114B or by the same electrodes 116 and/or 118 on leads 114A, 114B. As described, the LFP is intrinsically generated by a signal source (e.g., oscillatory electrical voltage source) within brain 120 of patient 122.

[0067] In some examples, the neurological brain signals that are used to select a stimulation electrode combination may be sensed within the same region of brain 120 as the target tissue site for the electrical stimulation. As previously indicated, the target tissue sites may include tissue sites within anatomical structures such as the thalamus, STN, or globus pallidus of brain 120, as well as other target tissue sites. The specific target tissue sites and/or regions within brain 120 may be selected based on the patient condition. Thus, in some examples, both a stimulation electrode combination and sense electrode combinations may be selected from the same set of electrodes 116, 118. In other examples, the electrodes used for delivering electrical stimulation may be different than the electrodes used for sensing neurological brain signals.

[0068] Therapeutic electrical stimulation generated by IMD 106 may be configured to manage a variety of disorders and conditions. In some examples, the stimulation generation circuitry of IMD 106 is configured to generate and deliver therapeutic electrical stimulation pulses to patient 112 via electrodes of a selected stimulation electrode combination. However, in other examples, the stimulation generation circuitry of IMD 106 may be configured to generate and deliver a continuous wave signal, e.g., a sine wave or triangle wave. In either case, stimulation generation circuitry within IMD 106 may generate the electrical stimulation therapy for DBS according to a selected therapy program. In examples in which IMD 106 delivers therapeutic electrical stimulation in the form of stimulation pulses, a therapy program may include a set of therapy parameter values (e.g., parameters), such as a stimulation electrode combination for delivering stimulation to patient 112, pulse frequency, pulse width, and a current or voltage amplitude of the pulses. As previously indicated, the electrode combination may indicate the specific electrodes 116, 118 that are selected to deliver therapeutic stimulation signals to tissue of patient 112 and the respective polarities of the selected electrodes.

[0069] In some examples, electrodes 116, 118 may be circumferentially-segmented DBS arrays of electrodes, and include some non-segmented electrodes as well, such as ring electrodes. Circumferentially-segmented DBS arrays refer to electrodes that are segmented circumferentially along the lead. As one example, leads 114A and 114B may include a first set of electrodes arranged circumferentially around leads 114A and 114B that are all at the same height level on leads 114A and 114B. Each of the electrodes in the first set of electrodes is a separate segmented electrode and form a level of circumferentially- segmented array of electrodes. Leads 114A and 114B may include a second set of electrodes arranged circumferentially around leads 114A and 114B that are all at the same height level on leads 114A and 114B. Each of the electrodes in the first set of electrodes is a separate segmented electrode and form a level of circumferentially-segmented array of electrodes. The electrodes may be beneficial by enabling directional stimulation and sensing.

[0070] With the electrodes, IMD 106 may be configured to perform both directional stimulation and sensing, thereby enhancing the ability to target the source of the LFP activities (also referred to as pathological neuronal activities). For example, IMD 106 may be configured to perform directional sensing to determine a direction and/or orientation of the LFP source (e.g., signal source that generates the LFP) having the signal component in the beta frequency band. IMD 106 may direct the electrical stimulation toward the signal source to suppress (e.g., squelch) the signal component produced by the signal source in the beta frequency band, as one example. This disclosure describes example techniques to utilize ERNA signals in relation to constructive and destructive resonance states to determine optimal parameters for the therapeutic electrical stimulation signals. The example techniques may be used generally for DBS, or other types of therapy where constructive and destructive resonance states and ERNA signals are used as part of closed- loop therapy.

[0071] Further, the example techniques are not limited to examples where one or more of electrodes 116, 118 are circumferentially-segmented electrodes. The example of using circumferentially-segmented electrodes is described as a way of directional stimulation and sensing. However, the example techniques are also useable in examples where directional stimulation and sensing are not available or are not used. Moreover, there may be other ways of performing directional stimulation and sensing that do not require the use of circumferentially-segmented electrodes.

[0072] In an example, for DBS, IMD 106 may be configured to deliver therapeutic electrical stimulation signals based on one or more parameters such as amplitude, pulse width, and frequency. In some examples, shortly after implantation or during the implantation surgery for IMD 106 and/or leads 114A, 114B, a clinician/ surgeon may determine initial parameters (e.g., a first set of one or more parameters for a first set of one or more therapeutic electrical stimulation signals). As described herein, constructive and destructive resonance states may be used, in part, to guide programming of the parameters for the therapeutic electrical stimulation signals. For example, the clinician/surgeon may use the timing of a peak of an EP compared to underlying resonance to determine optimal stimulation frequency for constructive or destructive based on a desired resonant state. Additionally, the clinician/surgeon may use the ERNA from a short burst of pulses to infer the steady state resonant behavior to optimize stimulation for steady state. By being able to infer steady state from a short burst of pulses, the programming process can be shorter in time. Additionally, the steady state resonant behavior may be based on an alignment of the peak of the EP and underlying resonance or based on other properties of the ERNA signal itself (e.g., shape, symmetry of peak and trough, damping rate of response, etc.).

[0073] However, the effectiveness of the first set of one or more therapeutic electrical stimulation signals may change overtime. For instance, due to lead migration, accommodation of the neural substrate to stimulation, or worsening of patient condition, the first set of one or more therapeutic electrical stimulation signals may be insufficient to provide effective therapy. Conversely, if patient condition improves, the intensity of the first set of one or more therapeutic electrical stimulation signals may be greater than needed to provide effective therapy.

[0074] Accordingly, there may be benefit in periodically, or possibly continuously, updating the first set of one or more parameters to a second set of one or more parameters for a second set of one or more therapeutic electrical stimulation signals. In the above examples, there may be benefit in updating the initial parameters. However, in some cases, after the initial parameters are updated, there may be benefit in periodically, or possibly continuously, determining whether to update the parameters for therapeutic electrical stimulation signals.

[0075] One way to update the parameters for therapeutic electrical stimulation signals may be for patient 112 to periodically schedule an appointment with a clinician to update the parameters. Another way to update the parameters for therapeutic electrical stimulation signals may be for patient 112 to manually adjust the parameters himself/herself. In both such examples, there may be burden on patient 112 to have to schedule appointments for parameter adjustment or self-titrate the parameters, which may also lead to delay in updates to parameters.

[0076] This disclosure describes example techniques for closed-loop parameter adjustment. For example, the processing circuitry of IMD 106 may be configured to perform closed-loop adjustments to parameters of the therapeutic electrical stimulation signals to maintain an optimal resonance selection. In some embodiments, medicine washin and medicine wash-out (e.g., or other neural states of patient 112) may cause slight changes in the underlying resonance, such that the processing circuitry of IMD 106 may adjust one or more parameters of the therapeutic electrical stimulation signals to better maintain a desired resonance state based on detecting the changes. Additionally or alternatively, certain activities or movements may cause a change in the underlying resonance, and processing circuitry of IMD 106 may adjust one or more parameters of the therapeutic electrical stimulation signals to better maintain a desired resonance state based on detecting the change.

[0077] In some embodiments, the processing circuitry of IMD 106 may be configured to perform closed-loop adjustments to adjust stimulation parameters (e.g., stimulation frequency, amplitude, pulse width, etc.) based on a change in neural state for patient 112 or based on a presence of side effect(s). As an example, when patient 112 is awake, the processing circuitry of IMD 106 may use a first set of stimulation parameters programmed or assigned to an awake neural state, and when patient 112 is asleep, the processing circuitry of IMD 106 may switch to using a second set of stimulation parameters programmed or assigned to a sleep neural state. Additionally or alternatively, if the processing circuitry of IMD 106 senses a presence of side effect(s) (e.g., a change in the ERNA signal, an LFP signal side effect, etc.), the processing circuitry of IMD 106 may adjust one or more parameters of the therapeutic electrical stimulation signals.

[0078] The following describes one example way in which to determine parameters for the therapeutic electrical stimulation signal based on ERNA signals. However, the example techniques are not so limited. For instance, for initial parameters, a clinician may manually titrate parameters until the right parameters are identified for the initial therapeutic electrical stimulation signal.

[0079] For determining parameters based on ERNA signals, the processing circuitry of IMD 106 may cause the stimulation generation circuitry of IMD 106 to deliver a plurality of electrical stimulation signals via the one or more electrodes 116. In one or more examples, the plurality of electrical stimulation signals each include at least one different therapy parameter. For each of the plurality of electrical stimulation signals, the processing circuitry of IMD 106 may determine respective ERNA signals, where the respective ERNA signals are evoked by delivery of the respective plurality of electrical stimulation signals. The processing circuitry may determine parameters for the therapeutic electrical stimulation signal based on the respective ERNA signals.

[0080] In this disclosure, the phrase “therapeutic electrical stimulation signal” is used to refer to electrical stimulation signal that is delivered for providing therapy. Delivery of the therapeutic electrical stimulation signal may evoke an ERNA signal, but the techniques do not require the therapeutic electrical stimulation signal to evoke an ERNA signal. The phrase “electrical stimulation signal” is used to refer to electrical stimulation signal that is delivered for evoking an ERNA signal. Delivery of an electrical stimulation signal for evoking an ERNA signal may provide therapeutic effect, but the techniques do not require the electrical stimulation signal used for evoking an ERNA signal to provide therapeutic effect.

[0081] As described above, the processing circuitry may cause stimulation generation circuitry to deliver a plurality of electrical stimulation signals via the determined one or more electrodes, where the plurality of electrical stimulation signals each include at least one different therapy parameter. For instance, the processing circuitry may cause the stimulation generation circuitry to sweep across a range of frequencies such that frequency of each of the electrical stimulation signals is different. That is, the processing circuitry may be configured to cause the stimulation generation circuitry to deliver the plurality of electrical stimulation signals via the determined one or more electrodes, where a frequency for each of the plurality of electrical stimulation signals is within a range of frequencies (e.g., 5 Hz to 220 Hz). As another example, the processing circuitry may cause the stimulation generation circuitry to sweep across a range of amplitudes and/or pulse widths such that the amplitude and/or pulse width of each of the electrical stimulation signals is different. That is, the processing circuitry may be configured to cause the stimulation generation circuitry to deliver the plurality of electrical stimulation signals via the determined one or more electrodes, where an amplitude and/or pulse width for each of the plurality of electrical stimulation signals is within a range of amplitudes and/or pulse widths.

[0082] The processing circuitry may evaluate the respective ERNA signals for determining the parameters for the therapeutic electrical stimulation signal. For instance, the processing circuitry may determine characteristics of the respective ERNA signals such as resonant activity. Examples of resonant activity include one or more of peak-to- trough amplitude, time between peak-to-peak, decay time constant, change in peak amplitudes (e.g., damping), amount of oscillations (e.g., number of peaks), rise or fall times, and frequency shift from early resonance to late resonance of the respective ERNA signals.

[0083] Based on the determined resonant activity, the processing circuitry may select one of the ERNA signals. As an example, the processing circuitry may select the ERNA signal of the respective ERNA signals having the highest peak-to-trough amplitude (e.g., constructive resonant state). As another example, the processing circuitry may select the ERNA signal of the respective ERNA signals having the most of amount of oscillations (e.g., the most number of peaks before the ERNA signals dampens to noise level). As another example, the processing circuitry may select the ERNA signal of the respective ERNA signals having the fastest reduction in peak amplitudes (e.g., fastest damping). The above provide a few non-limiting examples resonant activity that the processing circuitry may evaluate to select an ERNA signal, and other examples of resonant activity are possible. Also, the processing circuitry may select an ERNA signal based on a combination of the resonant activity (e.g., a weighting of two or more examples the resonant activity).

[0084] The processing circuitry may determine the respective electrical stimulation signal of the selected ERNA signal, and may determine the parameters of the determined respective electrical stimulation signal. The processing circuitry may determine the parameters for the therapeutic electrical stimulation signal based on the determined parameters. In this way, the processing circuitry may determine parameters for the therapeutic electrical stimulation signal based on the respective ERNA signals.

[0085] IMD 106 may be implanted within a subcutaneous pocket above the clavicle, or, alternatively, on or within cranium 122 or at any other suitable site within patient 112. Generally, IMD 106 is constructed of a biocompatible material that resists corrosion and degradation from bodily fluids. IMD 106 may comprise a hermetic housing to substantially enclose components, such as a processor, therapy module, and memory. [0086] As shown in FIG. 1, implanted lead extension 110 is coupled to IMD 106 via connector 108 (also referred to as a connector block or a header of IMD 106). In the example of FIG. 1, lead extension 110 traverses from the implant site of IMD 106 and along the neck of patient 112 to cranium 122 of patient 112 to access brain 120. In the example shown in FIG. 1, leads 114A and 114B (collectively “leads 114”) are implanted within the right and left hemispheres (or in just one hemisphere in some examples), respectively, of patient 112 in order to deliver electrical stimulation to one or more regions of brain 120, which may be selected based on the patient condition or disorder controlled by therapy system 100. The specific target tissue site and the stimulation electrodes used to deliver stimulation to the target tissue site, however, may be selected, e.g., according to the identified patient behaviors and/or other sensed patient parameters. Other lead 114 and IMD 106 implant sites are contemplated. For example, IMD 106 may be implanted on or within cranium 122, in some examples. Leads 114A and 114B may be implanted within the same hemisphere or IMD 106 may be coupled to a single lead implanted in a single hemisphere, in some examples.

[0087] Existing lead sets include axial leads carrying ring electrodes disposed at different axial positions and so-called "paddle" leads carrying planar arrays of electrodes. In some examples, more complex lead array geometries may be used.

[0088] Although leads 114 are shown in FIG. 1 as being coupled to a common lead extension 110, in other examples, leads 114 may be coupled to IMD 106 via separate lead extensions or directly to connector 108. Leads 114 may be positioned to deliver electrical stimulation to one or more target tissue sites within brain 120 to manage patient symptoms associated with a movement disorder of patient 112. Leads 114 may be implanted to position electrodes 116, 118 at desired locations of brain 120 through respective holes in cranium 122. Leads 114 may be placed at any location within brain 120 such that electrodes 116, 118 are capable of providing electrical stimulation to target tissue sites within brain 120 during treatment. For example, electrodes 116, 118 may be surgically implanted under the dura mater of brain 120 or within the cerebral cortex of brain 120 via a burr hole in cranium 122 of patient 112, and electrically coupled to IMD 106 via one or more leads 114.

[0089] In the example shown in FIG. 1, electrodes 116, 118 of leads 114 are shown as ring electrodes. Ring electrodes may be used in DBS applications because ring electrodes are relatively simple to program and are capable of delivering an electrical field to any tissue adjacent to electrodes 116, 118. In other examples, electrodes 116, 118 may have different configurations. For example, at least some of the electrodes 116, 118 of leads 114 may have a complex electrode array geometry that is capable of producing shaped electrical fields. The complex electrode array geometry may include multiple electrodes (e.g., partial ring or segmented electrodes) around the outer perimeter of each lead 114, rather than one ring electrode. In this manner, electrical stimulation may be directed in a specific direction from leads 114 to enhance therapy efficacy and reduce possible adverse side effects from stimulating a large volume of tissue. For example, one or more electrodes 116, 118 may be circumferentially-segmented DBS arrays of electrodes, and one or more electrodes 116, 118 may be non-segmented electrodes such as ring electrodes, as described above. In some examples, electrodes 116, 118 may only be circumferentially- segmented DBS arrays of electrodes, and in some examples, electrodes 116, 118 may only be non-segmented electrodes, such as ring electrodes.

[0090] In some examples, a housing of IMD 106 may include one or more stimulation and/or sensing electrodes. In some examples, leads 114 may have shapes other than elongated cylinders as shown in FIG. 1. For example, leads 114 may be paddle leads, spherical leads, bendable leads, or any other type of shape effective in treating patient 112 and/or minimizing invasiveness of leads 114.

[0091] IMD 106 includes a memory to store a plurality of therapy programs that each define a set of therapy parameter values. In some examples, IMD 106 may select a therapy program from the memory based on various parameters, such as sensed patient parameters and the identified patient behaviors. For example, as described above, the processing circuitry of IMD 106 may determine updates to parameters for the therapeutic electrical stimulation signal based on the respective LFP measurements and ERNA signals. In some examples, IMD 106 may output information indicative of the determined updated parameters for clinician approval. After approval, the processing circuitry of IMD 106 may store in a therapy program the determined parameter and may be configured to cause stimulation generation circuitry of IMD 106 to deliver the therapeutic electrical stimulation signal based on the determined parameters (e.g., by the processing circuitry selecting the therapy program that includes the determined parameters).

[0092] That is, the stimulation generation circuitry of IMD 106 may deliver a first set of one or more therapeutic electrical stimulation signals according to a first set of one or more parameters. Then, the processing circuitry may determine a second set of one or more parameters for a second set of one or more therapeutic electrical stimulation signals based on the one or more ERNA signals and constructive and destructive resonance states, and cause the stimulation generation circuitry to deliver the second set of the one or more therapeutic electrical stimulation signals. The second set of one or more parameters may be updates to the first set of one or more parameters.

[0093] The delivery of the first set of one or more therapeutic electrical stimulation signals may not be necessary in all cases. For instance, memory of IMD 106 or some other memory may store the first set of one or more parameters for the first set of one or more therapeutic electrical stimulations signals. The processing circuitry may periodically update the first set of one or more parameters to the second set of one or more parameters based on ERNA signals and constructive and destructive resonance states, as described in this disclosure.

[0094] In some examples, clinician approval may not be necessary, such as in examples where the determined parameters for the therapeutic electrical stimulation signal are within a “safe-range” as assigned by the surgeon/clinician. In such examples, the processing circuitry of IMD 106 may output information indicative of the determined parameters for storage as a therapy program, and the stimulation generation circuitry may deliver the therapeutic electrical stimulation signal based on the determined parameters (e.g., by processing circuitry selecting the therapy program that includes the determined parameters). In this way, IMD 106 may generate therapeutic electrical stimulation based on the parameters of the selected therapy program to manage the patient symptoms associated with the patient disorder.

[0095] Rather than or in addition to using therapy programs, in some examples, it may be possible for the processing circuitry to directly output the information indicative of the determined parameters to the stimulation generation circuitry. Accordingly, there may be various way in which the processing circuitry may output information indicative of the determined parameters, such as to an external device like external programmer 104, described, below, to a therapy program, or to the stimulation generation circuitry. [0096] External programmer 104 wirelessly communicates with IMD 106 as needed to provide or retrieve therapy information. Programmer 104 is an external computing device that the user, e.g., a clinician and/or patient 112, may use to communicate with IMD 106. For example, programmer 104 may be a clinician programmer that the clinician uses to communicate with IMD 106 and program one or more therapy programs for IMD 106. Alternatively, programmer 104 may be a patient programmer that allows patient 112 to select programs and/or view and modify therapy parameters. The clinician programmer may include more programming features than the patient programmer. In other words, more complex or sensitive tasks may only be allowed by the clinician programmer to prevent an untrained patient from making undesirable changes to IMD 106.

[0097] When programmer 104 is configured for use by the clinician, programmer 104 may be used to transmit initial programming information to IMD 106. This initial information may include hardware information, such as the type of leads 114 and the electrode arrangement, the position of leads 114 within brain 120, the configuration of electrode array 116, 118, initial programs defining therapy parameter values, and any other information the clinician desires to program into IMD 106. Programmer 104 may also be capable of completing functional tests (e.g., measuring the impedance of electrodes 116, 118 of leads 114).

[0098] The clinician may also store therapy programs within IMD 106 with the aid of programmer 104. During a programming session, the clinician may determine one or more therapy programs that may provide efficacious therapy to patient 112 to address symptoms associated with the patient condition, and, in some cases, specific to one or more different patient states, such as a sleep state, movement state or rest state. For example, the clinician may select one or more stimulation electrode combinations with which stimulation is delivered to brain 120. During the programming session, the clinician may evaluate the efficacy of the specific program being evaluated based on feedback provided by patient 112 or based on one or more physiological parameters of patient 112 (e.g., muscle activity, muscle tone, rigidity, tremor, etc.). In some examples, ERNA signals may be used to evaluate the efficacy of the specific program being evaluated (e.g., certain resonant activity in the ERNA signal may be indicative of efficacious therapy). Alternatively, identified patient behavior from video information may be used as feedback during the initial and subsequent programming sessions. Programmer 104 may assist the clinician in the creation/identification of therapy programs by providing a methodical system for identifying potentially beneficial therapy parameter values. [0099] Programmer 104 may also be configured for use by patient 112. When configured as a patient programmer, programmer 104 may have limited functionality (compared to a clinician programmer) in order to prevent patient 112 from altering critical functions of IMD 106 or applications that may be detrimental to patient 112. In this manner, programmer 104 may only allow patient 112 to adjust values for certain therapy parameters or set an available range of values for a particular therapy parameter.

[0100] Programmer 104 may also provide an indication to patient 112 when therapy is being delivered, when patient input has triggered a change in therapy or when the power source within programmer 104 or IMD 106 needs to be replaced or recharged. For example, programmer 104 may include an alert LED, may flash a message to patient 112 via a programmer display, generate an audible sound or somatosensory cue to confirm patient input was received, e.g., to indicate a patient state or to manually modify a therapy parameter.

[0101] Moreover, in some examples, the example techniques may be performed in the “cloud.” For example, IMD 106 and/or programmer 104 may upload the ERNA signals to one or more servers that form a cloud computing environment. Processing circuitry of the cloud computing environment may perform the example techniques described in this disclosure. Accordingly, in this disclosure, the processing circuitry that is configured to perform the example techniques may be any one or combination of the processing circuitry of IMD 106, the processing circuitry of programmer 104, and/or processing circuitry of a cloud computing environment.

[0102] Therapy system 100 may be implemented to provide chronic stimulation therapy to patient 112 over the course of several months or years. However, system 100 may also be employed on a trial basis to evaluate therapy before committing to full implantation. If implemented temporarily, some components of system 100 may not be implanted within patient 112. For example, patient 112 may be fitted with an external medical device, such as a trial stimulator, rather than IMD 106. The external medical device may be coupled to percutaneous leads or to implanted leads via a percutaneous extension. If the trial stimulator indicates DBS system 100 provides effective treatment to patient 112, the clinician may implant a chronic stimulator within patient 112 for relatively long-term treatment.

[0103] Although IMD 106 is described as delivering electrical stimulation therapy to brain 120, IMD 106 may be configured to direct electrical stimulation to other anatomical regions of patient 112. Further, an IMD may provide other electrical stimulation such as spinal cord stimulation to treat a movement disorder.

[0104] Fig. 2 is a block diagram of the example IMD 106 of Fig. 1 for delivering DBS therapy. In the example shown in Fig. 2, IMD 106 includes processing circuitry 210, memory 212, stimulation generation circuitry 202, sensing circuitry 204, telemetry circuitry 208, and power source 220. Each of these circuits may be or include electrical circuitry configured to perform the functions attributed to each respective circuit. Memory 212 may include any volatile or non-volatile media, such as a random-access memory (RAM), read only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, and the like. Memory 212 may store computer-readable instructions that, when executed by processing circuitry 210, cause IMD 106 to perform various functions. Memory 212 may be a storage device or other non- transitory medium. In some examples, IMD 106 may include or may be referred to as a signal generator.

[0105] In the example shown in Fig. 2, memory 212 stores data for performing a sensed signal monitoring 214, a neural state determination 216, a neural state change determination 218, and/or a notification transmission 220. In one or more examples, processing circuitry 210 may perform sensed signal monitoring 214 to monitor for a sensed signal after applying a generated electrical stimulation signal (e.g., therapeutic electrical stimulation signal). For example, the sensed signal may include an ERNA signal, an LFP signal, an HFO signal, or a combination thereof. Subsequently, processing circuitry 210 may perform neural state determination 216 to determine a neural state is present for the patient based on the sensed signal. In some embodiments, as part of the neural state determination, processing circuitry 210 may calculate a steady state behavior for the sensed signal (e.g., a steady state ERNA behavior), and the neural state may be determined to present for the patient based on detecting a change in the sensed signal from the steady state behavior.

[0106] Additionally, processing circuitry 210 may perform neural state determination 216 to determine a respective plurality of stimulation parameters for each of a plurality of neural states. As described herein, the plurality of neural states may include but is not limited to: asleep/awake, depth of anesthesia, medication wash in/out, disease progression, a movement state (e.g., whether the patient is moving or not, such as indicated by an accelerometer), and a posture of the patient (e.g., upright, laying down, etc.). For example, each of the respective plurality of stimulation parameters may be configured for applying the generated electrical stimulation signal to the anatomical element when a corresponding neural state is determined to be present for the patient. In some examples, each of the respective plurality of stimulation parameters may comprise a frequency, an amplitude, a pulse width, a choice of stimulation electrode, additional parameters, or a combination thereof for applying the electrical stimulation signal when the corresponding neural state is determined to be present for the patient. Accordingly, as part of neural state determination 216, processing circuitry 210 may select a plurality of stimulation parameters from the respective plurality of stimulation parameters based on determining the neural state is present for the patient, where the plurality of stimulation parameters correspond to the determined neural state. Subsequently, processing circuitry 210 may indicate for stimulation generation circuitry 202 to apply a generated electrical stimulation signal (e.g., therapeutic electrical stimulation signals) to the anatomical element using the selected plurality of stimulation parameters for the detected neural state.

[0107] In some embodiments, sensed signal monitoring 214 may include monitoring for an additional instance of the sensed signal after the generated electrical stimulation signal is applied to the anatomical element using the selected plurality of stimulation parameters for the detected neural state. Subsequently, in some examples, processing circuitry 210 may perform neural state change determination 218 by determining a neural state change from the detected neural state to an additional neural state of the plurality of neural states based on the additional instance of the sensed signal. For example, the neural state change may be determined to occur based on a detected shift in resonant frequency from the additional instance of the sensed signal, a peak-to-trough amplitude of the additional instance of the sensed signal, a damping of the additional instance of the sensed signal, a number of resonant peaks of the additional instance of the sensed signal, or a combination thereof. Accordingly, processing circuitry 210 may indicate for stimulation generation circuitry 202 to apply the generated electrical stimulation signal to the anatomical element using an additional plurality of stimulation parameters of the respective plurality of stimulation parameters based on the determined neural state change, the additional plurality of stimulation parameters corresponding to the additional neural state.

Additionally, processing circuitry 210 may perform notification transmission 220 to transmit a notification to a user interface accessible by the patient based on the determined neural state change. In some embodiments, the notification may indicate for the patient to perform a patient action (e.g., take medication, adjust stimulation parameters, etc.). [0108] In some embodiments, sensed signal monitoring 214 may include applying the electrical stimulation signal to the anatomical element using a burst of a plurality of pulses, pausing application of the generated electrical stimulation signal after the burst of the plurality of pulses for a time duration, and capturing a neural response of the patient during the time duration, where the sensed signal comprises the neural response. For example, the neural response may include an ERNA response as described herein.

[0109] Stimulation generation circuitry 202, under the control of processing circuitry 210, generates stimulation signals (e.g., electrical stimulation signals for evoking ERNA signals and/or therapeutic electrical stimulation signals for delivering therapy) for delivery to patient 112 via electrodes 116, 118. An example range of electrical parameters believed to be effective in DBS to manage a movement disorder of patient include: a. Pulse Rate, i.e., Frequency: between approximately 5 Hertz (Hz) and approximately 500Hz, such as between approximately 5 to 220Hz or such as approximately 130Hz. b. In the case of a voltage controlled system, Voltage Amplitude: between approximately 0.1 volts (V) and approximately 50V, such as between approximately 2V and approximately 3 V. c. In the case of a current controlled system, Current Amplitude: between approximately 0.1 milliamps (mA) to approximately 3.5mA, such as between approximately 1.0mA and approximately 1.75mA. d. Pulse Width: between approximately 20 microseconds (ps) and approximately 500ps, such as between approximately 50ps and approximately 200ps.

[0110] Accordingly, in some examples, stimulation generation circuitry 202 generates therapeutic electrical stimulation signals in accordance with the electrical parameters noted above. For example, processing circuitry 210 may utilize the example techniques described in this disclosure to determine the parameters for the therapeutic electrical stimulation signals (e.g., based on the respective plurality of stimulation parameters determined and/or assigned for each of a plurality of neural states from neural state determination 216), and stimulation generation circuitry 202 may deliver the therapeutic electrical stimulation signals. Other ranges of therapy parameter values may also be useful, and may depend on the target stimulation site within patient 112. While stimulation pulses are described, stimulation signals may be of any form, such as continuous-time signals (e.g., sine waves) or the like. [0111] In addition to delivering therapeutic electrical stimulation signals, stimulation generation circuitry 202 may be configured to deliver electrical stimulation signals for evoking ERNA signals. Example parameters of the electrical stimulation signals for evoking ERNA signals include amplitude within range of 0 to 7.5 mA, such as 0 to 5 mA, frequency within range of 5 Hz to 250 Hz, such as 80 to 220 Hz, and pulse width in range of 20 to 450 microseconds, such as 60 to 120 microseconds.

[0112] Processing circuitry 210 may include fixed function processing circuitry and/or programmable processing circuitry, and may comprise, for example, any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), discrete logic circuitry, or any other processing circuitry configured to provide the functions attributed to processing circuitry 210 herein may be embodied as firmware, hardware, software or any combination thereof. Processing circuitry 210 may control stimulation generation circuitry 202 according to therapy programs stored in memory 212 to apply particular parameter values specified by one or more of programs, such as voltage amplitude or current amplitude, pulse width, and/or pulse rate.

[0113] Sensing circuitry 204 is configured to monitor signals from any combination of electrodes 116, 118. Although sensing circuitry 204 is incorporated into a common housing with stimulation generation circuitry 202 and processing circuitry 210 in Fig. 2, in other examples, sensing circuitry 204 may be in a separate housing from IMD 106 and may communicate with processing circuitry 210 via wired or wireless communication techniques.

[0114] In some examples, sensing circuitry 204 includes one or more amplifiers, filters, and analog-to-digital converters. Sensing circuitry 204 may be used to sense physiological signals, such as EP measurements and ERNA signals. In some examples, sensing circuitry 204 measures EP and ERNA signals from a particular combination of electrodes 116, 118. In some cases, the particular combination of electrodes for sensing includes different electrodes than a set of electrodes 116, 118 used to deliver electrical stimulation signals (e.g., therapeutic electrical stimulation signals or electrical stimulation signals for evoking ERNA signals). Alternatively, in other cases, the particular combination of electrodes used for sensing includes at least one of the same electrodes as a set of electrodes used to deliver stimulation signals to patient 120. Sensing circuitry 204 may provide signals to an analog-to-digital converter, for conversion into a digital signal for processing, analysis, storage, or output by processing circuitry 210. [0115] Electrodes 116, 118 on respective leads 114 may be constructed of a variety of different designs. For example, one or both of leads 114 may include two or more electrodes at each longitudinal location along the length of the lead, such as multiple electrodes, e.g., arranged as segments, at different perimeter locations around the perimeter of the lead at each of the locations.

[0116] As an example, one or both of leads 114 may include circumferentially- segmented DBS arrays of electrodes and non-segmented electrodes (e.g., ring electrodes). As one example, there may be a first ring electrode of electrodes 116 around the perimeter of lead 114A at a first longitudinal location on lead 114A (e.g., location A). Below the first ring electrode, there may be three segmented electrodes of electrodes 116 around the perimeter of lead 114A at a second longitudinal location on lead 114A (e.g., location B). Below the three segmented electrodes, there may be another set of three segmented electrodes of electrodes 116 around the perimeter of lead 114A at a third longitudinal location of lead 114A (e.g., location C). Below the three segmented electrodes, there may be a second ring electrode of electrodes 116 around the perimeter of lead 114A (e.g., location D). Electrodes 118 may be similarly positioned along lead 114B.

[0117] The above is one example of the array of electrodes, and the example techniques should not be considered limited to such an example. There may be other configurations of electrodes for DBS. Moreover, the example techniques are not limited to DBS, and other electrode configurations are possible.

[0118] In one example, the electrodes 116, 118 may be electrically coupled to stimulation generation circuitry 202 and sensing circuitry 204 via respective wires that are straight or coiled within the housing of the lead and run to a connector at the proximal end of the lead. In another example, each of the electrodes 116, 118 of the leads 114 may be electrodes deposited on a thin film. The thin film may include an electrically conductive trace for each electrode that runs the length of the thin film to a proximal end connector. The thin film may then be wrapped (e.g., a helical wrap) around an internal member to form the leads 114. These and other constructions may be used to create a lead with a complex electrode geometry.

[0119] Telemetry circuitry 208 supports wireless communication between IMD 106 and an external programmer 104 or another computing device under the control of processing circuitry 210. Processing circuitry 210 of IMD 106 may receive, as updates to programs, values for various parameters such as magnitude and electrode combination, from programmer 104 via telemetry circuitry 208. The updates to the therapy programs may be stored within therapy programs 214 portion of memory 212. Telemetry circuitry 208 in IMD 106, as well as telemetry modules in other devices and systems described herein, such as programmer 104, may accomplish communication by radiofrequency (RF) communication techniques. In addition, telemetry circuitry 208 may communicate with external medical device programmer 104 via proximal inductive interaction of IMD 106 with programmer 104. Accordingly, telemetry circuitry 208 may send information to external programmer 104 on a continuous basis, at periodic intervals, or upon request from IMD 106 or programmer 104.

[0120] Power source 220 delivers operating power to various components of IMD 106. Power source 220 may include a small rechargeable or non-rechargeable battery and a power generation circuit to produce the operating power. Recharging may be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within IMD 104. In some examples, power requirements may be small enough to allow IMD 104 to utilize patient motion and implement a kinetic energyscavenging device to trickle charge a rechargeable battery. In other examples, traditional batteries may be used for a limited period of time.

[0121] The DBS therapy is defined by one or more therapy programs 214 having one or more parameters stored within memory 212. For example, the one or more parameters include a current amplitude (for a current-controlled system) or a voltage amplitude (for a voltage-controlled system), a pulse rate or frequency, and a pulse width, or a number of pulses per cycle. In examples where the electrical stimulation is delivered according to a “burst” of pulses, or a series of electrical pulses defined by an “on-time” and an “off- time,” the one or more parameters may further define one or more of a number of pulses per burst, an on-time, and an off-time. Processing circuitry 210, via electrodes 116, 118, delivers DBS to patient 120 and may adjust one or more parameters defining the electrical stimulation based on corresponding parameters of the sensed one or more signals of brain 120.

[0122] Fig. 3 is a block diagram of the external programmer 104 of Fig. 1. Although programmer 104 may generally be described as a hand-held device, programmer 104 may be a larger portable device or a more stationary device. In addition, in other examples, programmer 104 may be included as part of an external charging device or include the functionality of an external charging device. As illustrated in Fig. 3, programmer 104 may include processing circuitry 310, memory 312, user interface 302, telemetry circuitry 308, power source 320, neural state parameter assignment 306, feedback reception 304, and parameter adjustment 314. Memory 312 may store instructions that, when executed by processing circuitry 310, cause processing circuitry 310 and external programmer 104 to provide the functionality ascribed to external programmer 104 throughout this disclosure. Each of these components, or modules, may include electrical circuitry that is configured to perform some or all of the functionality described herein. For example, processing circuitry 310 may include processing circuitry configured to perform the processes discussed with respect to processing circuitry 210 of the IMD 106 as described with reference to Fig. 2. In some examples, programmer 104 may include or may be referred to as a signal generator (e.g., in combination with or separate from IMD 106).

[0123] In general, programmer 104 comprises any suitable arrangement of hardware, alone or in combination with software and/or firmware, to perform the techniques attributed to programmer 104, and processing circuitry 310, user interface 302, and telemetry circuitry 308 of programmer 104. In various examples, programmer 104 may include one or more processors, which may include fixed function processing circuitry and/or programmable processing circuitry, as formed by, for example, one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. Programmer 104 also, in various examples, may include a memory 312, such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, a hard disk, a CD-ROM, comprising executable instructions for causing the one or more processors to perform the actions attributed to them. Moreover, although processing circuitry 310 and telemetry circuitry 308 are described as separate modules, in some examples, processing circuitry 310 and telemetry circuitry 308 may be functionally integrated with one another. In some examples, processing circuitry 310 and telemetry circuitry 308 correspond to individual hardware units, such as ASICs, DSPs, FPGAs, or other hardware units.

[0124] Memory 312 (e.g., a storage device) may store instructions or data that, when executed by processing circuitry 310, cause processing circuitry 310 and programmer 104 to provide the functionality ascribed to programmer 104 throughout this disclosure. For example, memory 312 may include instructions that cause processing circuitry 310 to obtain a parameter set from memory or receive a user input and send a corresponding command to IMD 106, or instructions for any other functionality. In addition, memory 312 may include a plurality of programs, where each program includes a parameter set that defines stimulation therapy. For example, memory 312 may include data for [0125] User interface 302 may include a button or keypad, lights, a speaker for voice commands, a display, such as a liquid crystal (LCD), light-emitting diode (LED), or organic light-emitting diode (OLED). In some examples the display may be a touch screen. User interface 302 may be configured to display any information related to the delivery of stimulation therapy, identified patient behaviors, sensed patient parameter values, patient behavior criteria, or any other such information. User interface 302 may also receive user input via user interface 302. The input may be, for example, in the form of pressing a button on a keypad or selecting an icon from a touch screen.

[0126] Telemetry circuitry 308 may support wireless communication between IMD 106 and programmer 104 under the control of processing circuitry 310. Telemetry circuitry 308 may also be configured to communicate with another computing device via wireless communication techniques, or direct communication through a wired connection. In some examples, telemetry circuitry 308 provides wireless communication via an RF or proximal inductive medium. In some examples, telemetry circuitry 308 includes an antenna, which may take on a variety of forms, such as an internal or external antenna.

[0127] Examples of local wireless communication techniques that may be employed to facilitate communication between programmer 104 and IMD 106 include RF communication according to the 802.11 or Bluetooth specification sets or other standard or proprietary telemetry protocols. In this manner, other external devices may be capable of communicating with programmer 104 without needing to establish a secure wireless connection.

[0128] In some examples, processing circuitry 310 of external programmer 104 defines the parameters of electrical stimulation therapy, stored in memory 312, for delivering DBS to patient 120. In one example, processing circuitry 310 of external programmer 104, via telemetry circuitry 308, issues commands to IMD 106 causing IMD 106 to deliver electrical stimulation therapy via electrodes 116, 118 via leads 114.

[0129] In one or more examples, programmer 104 may be configured to perform one or more of the example techniques described in this disclosure. For instance, processing circuitry 310 may be configured to perform one or more of the example operations described above with respect to processing circuitry 210.

[0130] For example, processing circuitry 310 may be configured to cause stimulation generation circuitry 202 to deliver a first set of one or more therapeutic electrical stimulation signals according to a first set of one or more parameters. For instance, processing circuitry 310 may output the first set of one or more parameters to IMD 106 for storage, which stimulation generation circuitry 202 uses for delivery of the first set of one or more therapeutic electrical stimulation signals.

[0131] Additionally, processing circuitry 310 may be configured to perform neural state parameter assignment 306. Neural state parameter assignment 306 may include processing circuitry 310 assigning a respective plurality of stimulation parameters to each of a plurality of neural states, each of the respective plurality of stimulation parameters being configured for applying the generated electrical stimulation signal to the anatomical element when a corresponding neural state is determined to be present for the patient. In some examples, neural state parameter assignment 306 may be indicated or executed based on inputs from a clinician assigning the respective plurality of stimulation parameters to each neural state of the plurality of neural states. Accordingly, when a neural state is detected, a plurality of parameters for the therapeutic electrical stimulation signals may be determined by processing circuitry 310 according to the respective plurality of stimulation parameters assigned to the detected neural state.

[0132] In some embodiments, processing circuitry 310 may also be configured to perform feedback reception 304. Feedback reception 304 may include processing circuitry 310 receiving feedback after the electrical stimulation signal is applied using a plurality of stimulation parameters that correspond or are assigned to a determined neural state. For example, the feedback may include an input received from the patient (e.g., via user interface 302) indicating a level of satisfaction the patient experiences when the electrical stimulation signal is applied to the anatomical element using the plurality of stimulation parameters for the determined neural state, an input received from a clinician to adjust one or more parameters, information received from an accelerometer (e.g., indicating a movement state and/or posture of the patient, such as whether the patient is moving, not moving, standing, laying down, etc.), a snapshot of a sensed signal (e.g., LFP, HFO, ERNA, etc.), indications of symptom biomarkers, or a different type of feedback not explicitly listed herein.

[0133] In some embodiments, after receiving the feedback, processing circuitry 310 may be configured to perform parameter adjustment 314, which may include processing circuitry 310 adjusting one or more stimulation parameters of the plurality of stimulation parameters assigned to the determined neural state based on the received feedback. For example, the one or more stimulation parameters may be adjusted autonomously by processing circuitry 310, processing circuitry 210, IMD 106, programmer 104, or a combination thereof, based in part on a deep learning model (e.g., an artificial intelligence (Al)-type algorithm) and/or a pre-determined algorithm (e.g., not Al related). Additionally or alternatively, the one or more stimulation parameters may be adjusted manually by a clinician and/or the patient.

[0134] Fig. 4 is an example stimulation response 400 according to at least one embodiment of the present disclosure. The example stimulation response 400 may implement aspects of or may be implemented by aspects of Figs. 1-3. For example, the example stimulation response 400 may represent a neural response of applying an electrical stimulation signal (e.g., therapeutic electrical stimulation signal) to an anatomical element (e.g., brain, STN, other area of the brain, the spine, etc.) of a patient as part of a DBS therapy (e.g., or other type of therapy) as described with reference to Figs. 1-3, such as by using IMD 106, leads 114A and 114B, electrodes 116 and 118, etc.

[0135] The example stimulation response 400 may represent applying the electrical stimulation signal using a plurality of stimulation pulses 402A-402J (e.g., a burst comprising the plurality of stimulation pulses 402). Each single stimulation pulse 402 may elicit an EP response 404 due to activation of local neural circuitry when the electrical stimulation signal is applied to the anatomical element of the patient. Stimulation of the anatomical element may activate the local neural circuitry such that sensing EPs in the anatomical element (e.g., via the electrodes 116, 118) will show the response to a given stimulation pulse 402 in addition to any additional feedback or underlying activity from connected structures near the anatomical element that are also activated. When multiple stimulation pulses 402 are delivered, the EP response 404 elicited from each stimulation pulse 402 can add to the underlying activity from the feedback from the complex neural network near the anatomical element.

[0136] With consecutive stimulation pulses 402, a sensed signal from the DBS therapy (e.g., which equals the EP response 404 from each stimulation pulse 402 plus underlying ongoing activity from previous pulses) may show a resonant behavior, referred to as ERNA 406. For example, the ERNA 406 (e.g., ERNA signal) is not an intrinsic signal within the anatomical element of the patient, but is evoked due to the electrical stimulation signal being delivered to the anatomical element. The stimulation signal delivered to the brain that evokes the ERNA 406 need not necessarily provide any therapeutic benefit, although it is possible for the stimulation signal that evokes the ERNA 406 to provide therapeutic benefit.

[0137] In some embodiments, the ERNA 406 may be generated based on applying the electrical stimulation signal to the anatomical element using a burst of the plurality of stimulation pulses 402 and then pausing application of the electrical stimulation signal after the burst of the plurality of stimulation pulses for a time duration (e.g., 30 ms or a different time duration). Subsequently, a neural response captured during the time duration may represent the ERNA 406. As shown in the example stimulation response 400 of Fig. 4, a time instance 408 may represent a time when a next occurring stimulation pulse 402 would have occurred after the stimulation pulse 402J, but did not occur based on the pause of the application of the electrical stimulation signal (e.g., time gap) to enable capturing of the ERNA 406. If a stimulation pulse were to be delivered at the time instance 408, the evoked response (e.g., the EP response 404) would add to any underlying activity (e.g., the ERNA 406) that is ongoing from the previous stimulation pulses 402. While 10 stimulation pulses 402 are shown in the example stimulation response 400, a different number of stimulation pulses 402 may be used to generate the ERNA 406.

[0138] As described herein, the ERNA 406 may be used to detect a change in neural state and then enable a switch of stimulation parameters (e.g., simulation group) based on stimulation parameters that are assigned to respective neural states. For example, a first set of stimulation parameters may be assigned to a first neural state, a second set of stimulation parameters may be assigned to a second neural state, etc. Accordingly, when a change to a neural state is detected, a corresponding set of stimulation parameters assigned to the detected neural state may be used to apply the electrical stimulation signal to the anatomical element of the patient. In some embodiments, the neural states for a patient may include, but are not limited to: asleep/awake, depth of anesthesia, medication wash in/out, disease progression, a movement state (e.g., whether the patient is moving or not, such as indicated by an accelerometer), and a posture of the patient (e.g., upright, laying down, etc.).

[0139] Fig. 5 is an example stimulation response recording 500 according to at least one embodiment of the present disclosure. In some examples, the example stimulation response recording 500 may represent a stimulation response for a patient during a neural state of the patient, such as a medication wash-in state. The example stimulation response recording 500 may implement aspects of or may be implemented by aspects of Figs. 1-4. For example, the example stimulation response recording 500 may represent a neural responses from applying an electrical stimulation signal (e.g., therapeutic electrical stimulation signal) to an anatomical element (e.g., brain, STN, other area of the brain, the spine, etc.) of a patient as part of a DBS therapy (e.g., or other type of therapy) as described with reference to Figs. 1-4, such as by using IMD 106, leads 114A and 114B, electrodes 116 and 118, etc.

[0140] The example stimulation response recording 500 may represent a recording during wash-in of a medication (e.g., propofol) to anesthetize a patient. A stimulation may be delivered as a burst of 10 pulses using a set of stimulation parameters (e.g., a stimulation frequency of 130Hz, a stimulation current of 0.7mA, etc.) with a gap (e.g., 30ms gap) between bursts of stimulation pulses to record an ERNA signal (e.g., underlying resonant activity). The example stimulation response recording 500 shows the 30ms gap between bursts along the x-axis through a duration of time along the y-axis. The color indicates the ERNA amplitude in microvolts (uV). Overall, a change of neural state due to anesthesia (e.g., medication wash-in) may cause a shift in resonant frequency of the ERNA response and, as such, can be used to indicate a depth of anesthesia for the patient. Similar concepts might hold for other changes in neural state, such as detection of sleep, medication, or disease progression.

[0141] As illustrated in the example stimulation response recording 500, as the medication was administered, a resonant frequency of the ERNA response shifts to the right (lower resonant frequency). For example, the example stimulation response recording 500 may include a first time instance 502 where a first dose of the medication is started to be administered to the patient, a second time instance 504 where administration of the first dose of the medication is stopped, a third time instance 506 where a second dose of the medication is started to be administered to the patient, a fourth time instance 508 where administration of the second dose of the medication is stopped, a fifth time instance 510 where a third dose of the medication is started to be administered to the patient, and a sixth time instance 512 where administration of the third dose of the medication is stopped. Accordingly, as more doses of the medication are administered to the patient (e.g., medication wash-in), a resonant frequency of the ERNA response starts to shift to the right as can be seen by the lighter shaded portions of the example stimulation response recording 500 begin moving to the right. As such, the shift in resonant frequency of the ERNA response may indicate a neural state change for the patient (e.g., depth of anesthesia state).

[0142] Fig. 6 is an example stimulation response recording 600 according to at least one embodiment of the present disclosure. In some examples, the example stimulation response recording 600 may represent a stimulation response for a patient during a neural state of the patient, such as a medication application. The example stimulation response recording 600 may implement aspects of or may be implemented by aspects of Figs. 1-5. For example, the example stimulation response recording 600 may represent a neural responses from applying an electrical stimulation signal (e.g., therapeutic electrical stimulation signal) to an anatomical element (e.g., brain, STN, other area of the brain, the spine, etc.) of a patient as part of a DBS therapy (e.g., or other type of therapy) as described with reference to Figs. 1-5, such as by using IMD 106, leads 114A and 114B, electrodes 116 and 118, etc.

[0143] The example stimulation response recording 600 may represent a stimulation that was held at a constant level after administering a medication (e.g., propofol) to the patient. As illustrated in the example stimulation response recording 600, a resonant frequency of an ERNA response begins to slowly shift left (e.g., an increase in resonant frequency) as can be seen by the lightly shaded portions moving to the left back to a normal awake state. At a time instance 602, the patient became alert (e.g., at ~4.7 minutes) as indicated with the horizontal black line. Subsequently, a small dose of the medication was given to the patient to keep the patient anesthetized, and the resonant frequency shifts back to the right, indicating a depth of anesthesia state for the patient.

[0144] Fig. 7 is an example stimulation response recording 700 according to at least one embodiment of the present disclosure. In some examples, the example stimulation response recording 700 may represent a stimulation response for a patient during a neural state of the patient, such as a medication wash-out. The example stimulation response recording 700 may implement aspects of or may be implemented by aspects of Figs. 1-6. For example, the example stimulation response recording 700 may represent a neural responses from applying an electrical stimulation signal (e.g., therapeutic electrical stimulation signal) to an anatomical element (e.g., brain, STN, other area of the brain, the spine, etc.) of a patient as part of a DBS therapy (e.g., or other type of therapy) as described with reference to Figs. 1-6, such as by using IMD 106, leads 114A and 114B, electrodes 116 and 118, etc.

[0145] The example stimulation response recording 700 may represent a stimulation response following a final dose of medication being applied to a patient at an initial time instance 702, and the patient awakening as the medication washes-out of the patient. Accordingly, the example stimulation response recording 700 may illustrate an ERNA response that was monitored as the medication is washed-out. At a time instance 704, reflexes of the patient begin to return. As the reflexes of the patient begin to return fully (e.g., after the time instance 704), a resonant frequency of the ERNA response shifts left (e.g., higher frequency), indicating a wash-out of the medication and a return to a baseline/alert neural state for the patient. At a time instance 706, the patient may be fully awake and alert. Accordingly, as illustrated and described in reference to Figs. 5, 6, and 7, shifts in resonant frequency of the ERNA response may indicate a neural state change for a patient (e.g., depth of anesthesia state). Similar concepts might hold for other changes in neural states, such as detection of sleep, medication, or disease progression (e.g., shifts in resonant frequency or other changes in the ERNA response may indicate changes in neural states). Additionally or alternatively, other changes in the ERNA response, such as changes in a peak-to-trough amplitude, a damping, and/or a change in a number of resonant peaks, may indicate a neural state change for the patient.

[0146] Fig. 8 depicts a flowchart of a method 800 that may be used, for example, to determine a neural state of a patient and apply an electrical stimulation signal using a plurality of parameters corresponding to the determined neural state.

[0147] 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) of a device as described herein. The at least one processor may be part of a programmer 104 and/or IMD 106 as described with reference to Figs. 1-3 (e.g., the processing circuitry 210 and/or the processing circuitry 310) and/or may be part of a control unit (e.g., computing device) in communication with the programmer 104 and/or IMD 106. 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 a memory in the programmer 104 and/or IMD 106 as described herein or a control unit, computing device, etc.). The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 800. One or more portions of a method 800 may be performed by the processor executing any of the contents of memory, such as monitor for a sensed signal, determine a neural state, determine stimulation parameters corresponding to a respective neural state, and/or any associated operations as described herein.

[0148] The method 800 comprises programming desired stimulation parameters for each neural state of a patient (step 802). For example, a first set of stimulation parameters may be programmed for an awake state of the patient, a second set of stimulation parameters may be programmed for an asleep state of the patient, a third set of stimulation parameters may be programmed for an on medication state, a fourth set of stimulation parameters may be programmed for an off medication state, etc. That is, a respective plurality of stimulation parameters may be determined for each of a plurality of neural states, each of the respective plurality of stimulation parameters being configured for applying the generated electrical stimulation signal to the anatomical element when a corresponding neural state is determined to be present for the patient.

[0149] The method 800 also comprises monitoring a sensed signal for detecting a neural state of the patient (step 804). For example, the sensed signal may include an ERNA signal, an LFP signal, an HFO signal, or a combination thereof.

[0150] The method 800 also comprises determining a neural state is present for the patient based on the sensed signal (step 806). In some embodiments, a steady state behavior for the sensed signal may be calculated, and the neural state may be determined to be present for the patient based on detecting a change in the sensed signal from the steady state behavior.

[0151] The method 800 also comprises applying a generated electrical stimulation signal to the anatomical element using a plurality of stimulation parameters, the plurality of stimulation parameters corresponding to the determined neural state (step 808). For example, the generated electrical stimulation signal may be applied to the anatomical element via a signal generator, such as the programmer 104, the IMD 106, the stimulation generation circuitry 202, the processing circuitry 210, and/or the processing circuitry 310, as described herein.

[0152] 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.

[0153] Fig. 9 depicts a flowchart of a method 900 that may be used, for example, to determine a neural state change.

[0154] The method 900 (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) of a device as described herein. The at least one processor may be part of a programmer 104 and/or IMD 106 as described with reference to Figs. 1-3 (e.g., the processing circuitry 210 and/or the processing circuitry 310) and/or may be part of a control unit (e.g., computing device) in communication with the programmer 104 and/or IMD 106. A processor other than any processor described herein may also be used to execute the method 900. The at least one processor may perform the method 900 by executing elements stored in a memory (such as a memory in the programmer 104 and/or IMD 106 as described herein or a control unit, computing device, etc.). The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 900. One or more portions of a method 900 may be performed by the processor executing any of the contents of memory, such as monitor for a sensed signal, determine a neural state change, determine stimulation parameters corresponding to a respective neural state, transmit a notification, and/or any associated operations as described herein.

[0155] The method 900 comprises programming desired stimulation parameters for each neural state of a patient (step 902). Step 902 may correspond to step 802 as described with reference to Fig. 8.

[0156] The method 900 also comprises monitoring a sensed signal (e.g., an ERNA signal, an LFP signal, an HFO signal, or a combination thereof) for detecting a change in neural state for the patient (step 904). For example, the neural state change may be determined based on a detected shift in resonant frequency of the sensed signal, a peak-to- trough amplitude of the additional instance of the sensed signal, a damping of the additional instance of the sensed signal, a number of resonant peaks of the additional instance of the sensed signal, or a combination thereof.

[0157] The method 900 also comprises switching stimulation groups to a new group programmed for the detected neural state change (step 906). For example, when programming the desired stimulation parameters for each neural state, each set of stimulation parameters may be assigned to a separate group corresponding to a respective neural state. Accordingly, an electrical stimulation signal may be applied to the anatomical element using a plurality of stimulation parameters assigned to the new group corresponding to the neural state change.

[0158] The method 900 also comprises transmitting a notification to a user interface accessible by the patient based on the determined neural state change (step 908). For example, if a medication- related neural state change is detected, the patient may be notified of a need to take more medication. Additionally or alternatively, the notification may indicate for the patient and/or a clinician to perform another action.

[0159] For example, a change in the sensed signal (e.g., ERNA change, such as a change in a resonant frequency of the ERNA response) may indicate that medications for the patient are washing out. Accordingly, the change in the sensed signal can be used as a way to then notify the patient to take more medication (e.g., such as via an application on a patient phone). For example, the patient’s device may talk to a programmer configured for DBS therapy (e.g., the programmer 104 as described with reference to Fig. 1), where the programmer may indicate that the medications of the patient are washing out based on the change in the sensed signal. Subsequently, the patient can decide to retake the medications based on the notification.

[0160] The present disclosure encompasses embodiments of the method 900 that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

[0161] Fig. 10 depicts a flowchart of a method 1000 that may be used, for example, to adjust stimulation parameters based on received feedback.

[0162] The method 1000 (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) of a device as described herein. The at least one processor may be part of a programmer 104 and/or IMD 106 as described with reference to Figs. 1-3 (e.g., the processing circuitry 210 and/or the processing circuitry 310) and/or may be part of a control unit (e.g., computing device) in communication with the programmer 104 and/or IMD 106. A processor other than any processor described herein may also be used to execute the method 1000. The at least one processor may perform the method 1000 by executing elements stored in a memory (such as a memory in the programmer 104 and/or IMD 106 as described herein or a control unit, computing device, etc.). The elements stored in the memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 1000. One or more portions of a method 1000 may be performed by the processor executing any of the contents of memory, such as monitor for a sensed signal, determine a neural state, determine a neural state change, determine stimulation parameters corresponding to a respective neural state, receive feedback, adjust stimulation parameters, and/or any associated operations as described herein.

[0163] The method 1000 comprises programming desired stimulation parameters for each neural state of a patient (step 1002). The method 1000 also comprises monitoring a sensed signal (e.g., an ERNA signal, an LFP signal, an HFO signal, or a combination thereof) for detecting a change in neural state for the patient (step 1004). The method 1000 also comprises switching stimulation groups to a new group programmed for the detected neural state change (step 1006). Steps 1002, 1004, and 1006 may correspond to steps 902, 904, and 906 as described with reference to Fig. 9 and may be performed similarly. [0164] The method 1000 also comprises receiving feedback for the new group programmed for the detected neural state change (step 1008). For example, an electrical stimulation signal may be applied to the anatomical element using a plurality of stimulation parameters assigned to the new group corresponding to the neural state change, and the feedback may indicate a level of satisfaction the patient experiences for the plurality of stimulation parameters assigned to the new group, information received from an accelerometer (e.g., indicating a movement state and/or posture of the patient, such as whether the patient is moving, not moving, standing, laying down, etc.), a snapshot of a sensed signal (e.g., LFP, HFO, ERNA, etc.), indications of symptom biomarkers, or a combination thereof.

[0165] The method 1000 also comprises adjusting one or more stimulation parameters of the plurality of stimulation parameters assigned to the new group based on the feedback (step 1010). For example, the one or more stimulation parameters may be adjusted autonomously by components configured for DBS therapy (e.g., IMD 106, programmer 104, processing circuitry 210, processing circuitry 310, etc.) based on a deep learning model and/or a pre-determined algorithm, adjusted manually by a clinician and/or the patient, or a combination thereof.

[0166] The present disclosure encompasses embodiments of the method 1000 that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

[0167] As noted above, the present disclosure encompasses methods with fewer than all of the steps identified in Figs. 8, 9, and 10 (and the corresponding descriptions of the methods 800, 900, and 1000), as well as methods that include additional steps beyond those identified in Figs. 8, 9, and 10 (and the corresponding descriptions of the methods 800, 900, and 1000). 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.

[0168] 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.

[0169] 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.