Brain stimulation and sensing

Abstract

The present invention discloses devices, systems, and techniques for managing electrical stimulation therapy and / or sensing physiological signals, such as brain signals. For example, the system can assist a clinician in identifying one or more electrode combinations for sensing brain signals. In another example, a user interface can display brain signal information and values ​​of stimulation parameters that at least partially define the electrical stimulation delivered to a patient when the brain signal information is sensed. A method is described herein, comprising: obtaining, by a processing circuit, brain signal information for at least one electrode combination from a plurality of electrode combinations of one or more electrical leads; determining, by the processing circuit, a corresponding frequency for the at least one electrode combination based on the brain signal information; outputting for display a plurality of selectable lead icons, wherein each of the plurality of selectable lead icons represents a different electrode combination from the plurality of electrode combinations; outputting for display the corresponding frequency determined for the at least one electrode combination in association with the corresponding selectable lead icon associated with the at least one electrode combination; receiving user input selecting one of the plurality of selectable lead icons; and, in response to receiving the user input, selecting, by the processing circuit, the sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing. An external programmer configured to perform the method is also described.

Description

[0001] This application claims priority to U.S. Provisional Patent Application No. 62 / 955,861, filed on December 31, 2019, and entitled “BRAIN STIMULATION AND SENSING,” which is incorporated herein by reference in its entirety. Technical Field

[0002] The present disclosure generally relates to electrical stimulation therapy. Background Art

[0003] The medical device 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, tremors, Parkinson's disease, other movement disorders, epilepsy, urinary or fecal incontinence, sexual dysfunction, obesity, or gastroparesis. The medical device may deliver the electrical stimulation therapy via one or more leads comprising electrodes positioned near a target location associated with the patient's brain, spinal cord, pelvic nerves, peripheral nerves, or gastrointestinal tract. Thus, electrical stimulation may be used for different therapeutic applications, such as deep brain stimulation (DBS), spinal cord stimulation (SCS), pelvic stimulation, gastric stimulation, or peripheral nerve field stimulation (PNFS).

[0004] A clinician can select values ​​for a plurality of programmable parameters to define the electrical stimulation therapy to be delivered to a patient by an implantable stimulator. For example, a clinician can select one or more electrodes to be used to deliver the stimulation, the polarity of each selected electrode, the voltage or current amplitude, the pulse width, and the pulse frequency as stimulation parameters. A set of parameters (such as a set of parameters including electrode combinations, electrode polarity, voltage or current amplitude, pulse width, and pulse frequency) can be referred to as a program because the set of parameters defines the electrical stimulation therapy to be delivered to the patient. Summary of the Invention

[0005] In general, the present disclosure describes devices, systems, and techniques for managing DBS therapy, which may include monitoring brain signals, stimulation parameter values, patient events, or other aspects related to the patient and DBS therapy. For example, a programming device may be configured to present a user interface configured to present information related to DBS therapy and / or brain signal monitoring. The system may include a medical device (e.g., an implantable medical device) configured to sense physiological signals, such as electrical signals originating from the patient's brain. The system may employ various aspects of these signals to present information to a user and / or guide the user in selecting various parameters for sensing and / or delivering stimulation.

[0006] For example, an external device (e.g., an external programmer) may include a user interface configured to receive user input selecting one or more electrode configurations for delivering stimulation and / or sensing brain signals. The system may suggest and / or receive user input defining one or more threshold values ​​that determine treatment parameter values ​​or request patient data. In some examples, the user interface may be configured to present stored and / or real-time brain signal data alone or together with one or more stimulation parameter values ​​defining the stimulation delivered when the brain signal data is sensed. In some examples, the external programming device may control the medical device to perform one or more signal tests on one or more electrode combinations (e.g., one or more signal pathways) of the implanted leads. Thus, the programming devices, user interfaces, and techniques described herein may enable a user (e.g., a clinician or patient) to manage one or more aspects of DBS therapy.

[0007] In one example, a method includes obtaining, by a processing circuit, brain signal information of at least one electrode combination among a plurality of electrode combinations of one or more electrical leads; determining, by the processing circuit, a corresponding frequency for the at least one electrode combination based on the brain signal information; outputting a plurality of selectable lead icons for display, wherein each of the plurality of selectable lead icons represents a different electrode combination among the plurality of electrode combinations; outputting the corresponding frequency determined for the at least one electrode combination in association with the corresponding selectable lead icon associated with the at least one electrode combination for display; receiving user input selecting one of the plurality of selectable lead icons; and in response to receiving the user input, selecting, by the processing circuit, a sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing.

[0008] In another example, a method includes obtaining, by a processing circuit, a brain signal representing electrical activity of a patient's brain; controlling, by the processing circuit, a medical device to deliver electrical stimulation defined by at least a first value of a stimulation parameter; adjusting, by the processing circuit, the first value of the stimulation parameter to a second value of the stimulation parameter at which a patient condition is identified; and determining, by the processing circuit, a threshold value of the brain signal associated with the patient condition, wherein the medical device is configured to limit automatic adjustment of the stimulation parameter to the second value associated with the threshold value.

[0009] In another example, a method includes obtaining, by a processing circuit, a brain signal representing electrical activity of a patient's brain; obtaining, by the processing circuit, one or more values ​​of a stimulation parameter that at least partially defines electrical stimulation that can be delivered to a portion of the patient's brain; and outputting a coordinate graph for display in a user interface, the coordinate graph comprising a first trace of the brain signal over a time period and a second trace of the one or more values ​​of the stimulation parameter over the time period.

[0010] In another example, a method includes obtaining, by a processing circuit, brain signal information representing electrical activity of a patient's brain over a time period from a first memory; obtaining, by the processing circuit, stimulation parameter information, the stimulation parameter information including one or more values ​​of stimulation parameters that at least partially define electrical stimulation delivered to a portion of the patient's brain during the time period; and outputting a coordinate graph for display on a user interface, the coordinate graph including a first trace of the brain signal information over the time period and a second trace of the one or more values ​​of the stimulation parameter over the time period.

[0011] In another example, a method includes obtaining, by a processing circuit, brain signal information representing electrical activity of a patient's brain over a time period; determining, by the processing circuit, a first amount of time during the time period when the amplitude of the brain signal information is greater than an upper threshold; determining, by the processing circuit, a second amount of time during the time period when the amplitude of the brain signal information is less than a lower threshold; determining, by the processing circuit, a third amount of time during the time period when the amplitude of the brain signal information is between the upper threshold and the lower threshold; and outputting representations of the first amount of time, the second amount of time, and the third amount of time for display via a user interface.

[0012] In another example, a method includes receiving, by a processing circuit, an indication of an event at a time; storing, in response to receiving the indication of the event, spectral information of a brain signal recorded at the time; and outputting a coordinate graph for display on a user interface, the coordinate graph indicating the spectral information of the brain signal recorded at the time.

[0013] The details of one or more examples of the technology of this disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of these technologies will be apparent from the description and drawings, and from the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a conceptual diagram illustrating an exemplary system including an implantable medical device (IMD) configured to deliver DBS to a patient according to examples of the presently disclosed technology.

[0015] Figure 2 is an example of a device for delivering DBS therapy according to the presently disclosed technology. Figure 1 Block diagram of an exemplary IMD.

[0016] Figure 3 is a method for controlling the delivery of DBS therapy according to an example of the technology disclosed herein Figure 1 Block diagram of an external programmer.

[0017] Figure 4is a conceptual diagram illustrating an exemplary home screen for navigating within a user interface.

[0018] Figure 5 and Figure 6 is a conceptual diagram illustrating an exemplary setting screen for managing electrode configuration.

[0019] Figure 7 is a flow chart illustrating an exemplary technique for running a signal test that evaluates one or more aspects of an electrode configuration.

[0020] Figure 8 and Figure 9 is a conceptual diagram illustrating exemplary screens showing information associated with stimulation effects on a patient.

[0021] Figure 10 is a conceptual diagram illustrating an exemplary screen for adjusting a frequency band for an electrode configuration.

[0022] Figure 11 is a conceptual diagram illustrating an exemplary screen for setting various sensing parameters for an electrode configuration.

[0023] Figure 12 is a conceptual diagram illustrating an exemplary screen for selecting the type of adaptive DBS mode.

[0024] Figures 13 to 20 is a conceptual diagram illustrating an exemplary screen for capturing one or more thresholds associated with adaptive DBS therapy.

[0025] Figure 21 is a flow chart illustrating an exemplary technique for setting one or more thresholds associated with adaptive DBS therapy.

[0026] Figure 22 is a conceptual diagram illustrating an exemplary screen summarizing parameters selected for adaptive DBS therapy.

[0027] Figure 23 and Figure 24 is a conceptual diagram illustrating an exemplary screen for manually adjusting one or more thresholds associated with adaptive DBS therapy.

[0028] Figures 25 to 30 is a conceptual diagram illustrating an exemplary screen for displaying sensed brain signals along with one or more stimulation parameters defining the delivered DBS therapy.

[0029] Figure 31 is a flow chart illustrating an exemplary technique for displaying sensed brain signals along with one or more stimulation parameters that define the delivered DBS therapy.

[0030] Figure 32 and Figure 33 is a conceptual diagram illustrating an exemplary screen for adjusting a transition between a stimulation parameter upper limit and a stimulation parameter lower limit.

[0031] Figure 34 is a conceptual diagram illustrating an exemplary home screen for navigating to view stored patient event data.

[0032] Figures 35 to 42 is a conceptual diagram illustrating an exemplary screen for displaying patient event data arranged by user-selectable time.

[0033] Figures 43 to 47 is a conceptual diagram illustrating an exemplary screen for displaying a brain signal coordinate graph corresponding to a patient event.

[0034] Figure 48 is a flow chart illustrating an exemplary technique for generating and displaying brain signal coordinate maps corresponding to patient events.

[0035] Figure 49 is a conceptual diagram illustrating an exemplary screen for displaying the amount of time that a brain signal characteristic is within a corresponding brain signal value range.

[0036] Figures 50 to 55 is a conceptual diagram illustrating an exemplary screen for displaying a graph of brain signal characteristics and stimulation parameter values ​​from DBS treatment over time.

[0037] Figure 56 is a flow chart illustrating an exemplary technique for generating and displaying graphs of brain signal characteristics and stimulation parameter values ​​from DBS therapy over time.

[0038] Figure 57 is a conceptual diagram illustrating an exemplary screen for displaying the amount of time for delivering different types of DBS treatments for corresponding days.

[0039] Figure 58 and Figure 59 is a conceptual diagram illustrating an exemplary screen for displaying a graph of brain signal power for corresponding electrode combinations of leads.

[0040] Figures 60 to 69 is a conceptual diagram illustrating exemplary screens of a user interface associated with entering an MRI mode of a medical device.

[0041] Figures 70 to 74 is a conceptual diagram illustrating exemplary screens of a user interface associated with entering an MRI mode of a medical device.

[0042] Figure 75 is a flow chart illustrating an exemplary technique for managing sensing of brain signals.

[0043] Figure 76 is a flow chart illustrating an exemplary technique for setting up and managing adaptive stimulation using brain signals. DETAILED DESCRIPTION

[0044] A patient may suffer from one or more symptoms that can be treated by electrical stimulation therapy. For example, a patient may suffer from a brain dysfunction (such as Parkinson's disease, Alzheimer's disease) or another type of movement disorder. Deep brain stimulation (DBS) can be an effective treatment for reducing the symptoms associated with such disorders. However, manually determining the appropriate stimulation parameters that define an effective electrical stimulation treatment can be very time-consuming for clinicians. In addition, DBS is typically delivered continuously to patients in an open-loop manner. Not only does this open-loop delivery consume more battery power by delivering stimulation when the patient does not need it, but the system is not able to adjust the stimulation parameters to provide more targeted treatment when the patient's condition changes over time or under certain conditions. In addition, it can be challenging for clinicians to identify patient events and conditions and what types of adjustments can be made over time to improve treatment.

[0045] As described herein, various devices, systems, and techniques are capable of managing DBS therapy and / or brain sensing for patients. For example, the systems described herein can be configured to sense and record brain signals associated with brain disorders (e.g., electroencephalogram (EEG) signals, local field potentials (LFP signals), or other brain signals). The system can identify appropriate frequencies for different electrode combinations and / or recommend electrode combinations for sensing. The system can also display the recorded brain signals or aspects thereof for review by a user (such as a clinician). In some examples, the system can operate in an adaptive DBS mode in which the system adjusts the values ​​of one or more stimulation parameters to keep the brain signals above or below one or more corresponding thresholds. The system can receive user input that specifies or adjusts any of these thresholds. In addition, the system can employ a setup mode in which a clinician can capture brain signal thresholds corresponding to corresponding stimulation parameter values. In some examples, the system can be configured to record and store brain signal information in response to user-identified events and / or system-identified events, wherein the system can subsequently present information related to the brain signals to enable a clinician to view brain signals associated with the events that occurred.

[0046] These various features can provide advantages over other systems and improve system functionality and patient outcomes. For example, the system can capture brain signals from multiple different electrode combinations and recommend electrode combinations for brain signal sensing, which reduces the trial and error of clinicians during patient setup. The system can also guide clinicians in the setting process of one or more thresholds for providing adaptive DBS therapy and enable fine-tuning of these thresholds. This guidance can reduce clinician time and improve patient treatment outcomes by increasing the efficacy of therapeutic stimulation and reducing side effects. The system can also correlate patient conditions and events with sensed brain signals and display such information for clinician review. Clinicians can then identify brain signals sensed during specific patient events and the stimulation state during such events to monitor stimulation efficacy and adjust stimulation over time to alleviate patient symptoms.

[0047] Figure 1 is a conceptual diagram illustrating an exemplary system 100 that includes an implantable medical device (IMD) 106 configured to deliver adaptive deep brain stimulation to a patient 112. DBS may be adaptive in the sense that IMD 106 may adjust, increase, or decrease the magnitude of one or more stimulation parameters of DBS in response to changes in patient activity or movement, the severity of one or more symptoms of the patient's disease, the presence of one or more side effects due to DBS, or one or more sensed signals from the patient. For example, the one or more sensed signals from the patient may be used as control signals such that IMD 106 correlates the magnitude of the one or more parameters of electrical stimulation with the magnitude of the one or more sensed signals. In accordance with the techniques of the present disclosure, system 100 delivers electrical stimulation therapy via IMD 106 having one or more parameters, such as voltage or current amplitude, that are adjusted in response to a signal's deviation from a range defined by a steady-state window (e.g., a window defined by one or more thresholds, such as a lower threshold and an upper threshold, of a brain signal).

[0048] In other examples, the system delivers an electrical stimulation therapy having the one or more parameters, such as voltage or current amplitude, adjusted in response to multiple signals, each of which deviates from a range defined by a corresponding steady-state window. For example, the system may sense a first neural signal (such as a signal within a beta band of the brain 120 of the patient 112 within a first corresponding steady-state window) and a second neural signal (such as a signal within a gamma band of the brain 120 of the patient 112 within a second corresponding steady-state window). In one exemplary system, the IMD 16 dynamically selects one of the first signal or the second signal to control the adjustment of the one or more parameters based on determining which of the first signal or the second signal most accurately corresponds to the severity of one or more symptoms of the patient. In another exemplary system, the IMD 106 adjusts the one or more parameters based on a ratio of the first signal to the second signal. In some examples, the amplitude of one or more frequencies in the gamma band increases as the stimulation intensity increases, such that higher gamma frequency amplitudes may be associated with side effects. Conversely, the amplitude of one or more frequencies in the beta band decreases as stimulation intensity increases, such that lower gamma frequency amplitudes may be associated with side effects (eg, dyskinesias).

[0049] In some examples, the medications taken by patient 112 are medications used to control one or more symptoms of Parkinson's disease (such as tremors or stiffness caused by Parkinson's disease). Such medications include extended-release dopamine agonists; conventional dopamine agonists; controlled-release carbidopa / levodopa (CD / LD); conventional CD / LD, entacapone, rasagiline, selegiline, and amantadine. Typically, to set the upper and lower thresholds of the steady-state window, the patient is off medication, that is, the upper and lower thresholds are set when the patient is not taking the medication selected to alleviate these symptoms. A patient may be considered to be off-drug if: for extended-release dopamine agonists, the patient has not taken the drug for at least approximately 72 hours prior to the time at which the upper limit is set; for conventional dopamine agonists and controlled-release CD / LD, the patient has not taken the drug for at least approximately 24 hours; and for conventional CD / LD, entacapone, rasagiline, selegiline, and amantadine, the patient has not taken the drug for at least approximately 12 hours. If stimulation only suppresses brain signals (e.g., LFP signals), the system can measure these brain signals for various values ​​of the stimulation parameters without external input. Once the upper and lower thresholds are established, the system can identify when the drug has lost its effect because the brain signal will cross the lower or upper thresholds. In response to identifying that the brain signal has crossed the threshold, the system can initiate electrical stimulation to restore the brain signal amplitude back to between the lower and upper thresholds. The programmer 104 can enable the user to set the lower and upper thresholds initially and adjust them over time. Programmer 104 may also determine and display information regarding the amount of time the stimulation amplitude is above, below, or between these thresholds.

[0050] As used herein, "alleviating" or "suppressing" a patient's symptoms refers to completely or partially alleviating the severity of one or more symptoms of the patient. In one example, a clinician determines the severity of one or more symptoms of Parkinson's disease in patient 112 by referring to the Unified Parkinson's Disease Rating Scale (UPDRS) or the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). A discussion of the use of the MDS-UPDRS is provided in Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): Scale Presentation and Clinimetric Testing Results, C. Goetz et al., Movement Disorders, Vol. 23, No. 15, pp. 2129-2170 (2008), the contents of which are incorporated herein in their entirety.

[0051] As described herein, a clinician may determine an upper threshold value for a steady-state window when the patient is not taking medication and when electrical stimulation therapy is being delivered to brain 120 of patient 112 via IMD 106. In one example, the clinician determines a point in time at which increasing the magnitude of one or more parameters defining the electrical stimulation therapy (such as voltage amplitude or current amplitude) begins to cause one or more side effects in patient 112. For example, the clinician may gradually increase the magnitude of one or more parameters defining the electrical stimulation therapy and determine a point in time at which further increases in the magnitude of the one or more parameters defining the electrical stimulation therapy cause perceptible side effects in patient 112. As described herein, IMD 106 may sense LFP during this process and display an LFP signal and / or LFP signal magnitude that may correspond to a corresponding threshold value.

[0052] As also described above, the clinician determines the lower threshold value when the patient is discontinuing medication and when the electrical stimulation therapy is delivered to the brain 120 of the patient 112 via the IMD 106. In one example, the clinician determines the point in time at which reducing the magnitude of one or more parameters defining the electrical stimulation therapy causes a break-through of one or more symptoms of the patient 112. The symptom break-through may refer to the recurrence of at least some symptoms that were substantially suppressed until the recurrence time point due to the reduction in the magnitude of the one or more electrical stimulation therapy parameters. For example, the clinician may gradually reduce the magnitude of one or more parameters defining the electrical stimulation therapy and determine the point in time at which symptoms of Parkinson's disease in the patient 112 appear, as measured by a sudden increase in the patient's 112 score in tremor or rigidity as defined by the UPDRS or MDS-UPDRS. In another example, the clinician measures a physiological parameter of patient 112 associated with one or more symptoms of the disease of patient 112 (e.g., wrist flexion of patient 112) and determines a point in time at which a further decrease in the magnitude of one or more parameters defining the electrical stimulation therapy causes a sudden worsening of one or more symptoms of the disease of patient 112 (e.g., patient 112 begins to experience an inability to flex his wrist).

[0053] At the magnitude of the one or more parameters defining the electrical stimulation therapy (at which point a further decrease in the magnitude of the one or more parameters defining the electrical stimulation therapy causes a sudden worsening of the one or more symptoms of the disease in patient 112), the clinician measures the magnitude of the signal from patient 112 and sets the magnitude as the lower threshold of the steady-state window. In some examples, the clinician may select the lower threshold of the steady-state window to be a predetermined amount higher than the magnitude at which the symptoms of patient 112 first appeared during the decrease in the magnitude of the one or more electrical stimulation parameters, such as 5% or 10% higher, to prevent the symptoms of patient 112 from appearing during subsequent use.

[0054] In another example, the clinician sets the lower threshold by first ensuring that the patient is off medication treating the one or more symptoms. In this example, the clinician delivers electrical stimulation with the value of the one or more parameters of the electrical stimulation approximately equal to the upper threshold of the therapeutic window. In some examples, the clinician delivers electrical stimulation with the value of the one or more parameters of the electrical stimulation slightly below the magnitude that induces side effects in patient 112. Typically, this results in a greater reduction in the one or more symptoms of the disease in patient 112 and, therefore, a greater reduction in the signal. At this magnitude of the one or more parameters, the clinician measures the magnitude of the signal of patient 112 and sets this magnitude as the lower threshold of the steady-state window via external programmer 104. In some examples, the clinician may select the value of the lower threshold of the steady-state window to be a predetermined amount higher than the magnitude at which the patient 112's symptoms occurred, such as 5% or 10% higher, to prevent the symptoms of patient 112 from occurring during subsequent use.

[0055] In addition, in one example of the technology disclosed herein, the system monitors a signal from the patient. In one example, the signal is a neural signal from the patient, such as a signal within the beta band or gamma band of the patient's brain. In yet another example, the signal is a signal indicative of a physiological parameter of the patient, such as the severity of the patient's symptoms, the patient's body position, the patient's respiratory function, or the patient's activity level. For example, the monitored signal may be the power of the corresponding beta band and / or gamma band.

[0056] The system delivers electrical stimulation to the patient via IMD 106, where one or more parameters defining the electrical stimulation are proportional to the magnitude of the monitored signal.

[0057] System 100 can be configured to treat patient conditions, such as movement disorders, neurodegenerative damage, mood disorders or epilepsy of patient 112. Patient 112 is typically a human patient. However, in some cases, treatment system 100 can be applied to other mammals or non-mammals, non-human patients. Although this article mainly mentions movement disorders and neurodegenerative damage, in other examples, treatment system 100 can provide treatment to manage the symptoms of other patient conditions, such as but not limited to epilepsy (e.g., epilepsy) or mood (or psychological) disorders (e.g., major depressive disorder (MDD), bipolar disorder, anxiety disorder, post-traumatic stress disorder, dysthymic disorder and obsessive-compulsive disorder (OCD)). At least some of these obstacles can be manifested as one or more patient motor behaviors. As described herein, movement disorders or other neurodegenerative damages can include symptoms, such as muscle control damage, motor damage or other movement problems, such as stiffness, spasticity, bradykinesia, rhythmic hyperkinesia, non-rhythmic hyperkinesia and akinesia. In some cases, movement disorders can be the symptoms of Parkinson's disease. However, movement disorders may be attributable to other patient conditions.

[0058] The exemplary treatment system 100 includes a medical device programmer 104, an implantable medical device (IMD) 106, a lead extension 110, and leads 114A and 114B with corresponding electrode sets 116, 118. Figure 1 In the example shown, the electrodes 116, 118 of the leads 114A, 114B are positioned to deliver electrical stimulation to a tissue site within the brain 120, such as a deep brain site beneath the dura mater of the brain 120 of the patient 112. In some examples, delivering stimulation to one or more regions of the brain 120, such as the subthalamic nucleus, globus pallidus, or thalamus, can be an effective treatment for managing movement disorders such as Parkinson's disease. Some or all of the electrodes 116, 118 can also be positioned to sense neural brain signals within the brain 120 of the patient 112. In some examples, some of the electrodes 116, 118 can be configured to sense neural brain signals, and other electrodes 116, 118 can be configured to deliver adaptive electrical stimulation to the brain 120. In other examples, all of the electrodes 116, 118 are configured to sense neural brain signals and deliver adaptive electrical stimulation to the brain 120.

[0059] IMD 106 includes a therapy module (e.g., which may include processing circuitry, signal generation circuitry, or other circuitry configured to perform the functions attributed to IMD 106) that includes a stimulation generator 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 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, a stimulation electrode combination may be selected for a particular patient 112 and target tissue site (e.g., based on the patient's condition). Electrode sets 116, 118 include at least one electrode and may include a plurality of electrodes. In some examples, multiple electrodes 116 and / or 118 may have complex electrode geometries, such that two or more electrodes are located at different locations around the perimeter of the respective leads.

[0060] In some examples, neural signals sensed within brain 120 may reflect changes in electrical current resulting from the summation of electrical potential differences throughout brain tissue. Examples of neural brain signals include, but are not limited to, electrical signals generated by local field potentials (LFPs) sensed within one or more regions of brain 120, such as electroencephalogram (EEG) signals or electrocorticogram (ECoG) signals. However, local field potentials may include a wider variety of electrical signals within brain 120 of patient 112.

[0061] In some examples, the neural brain signals used to select the stimulation electrode combination can be sensed in the same area of ​​the brain 120 as the target tissue site for electrical stimulation. As previously noted, these tissue sites can include tissue sites within anatomical structures (such as the thalamus, subthalamic nucleus, or globus pallidus of the brain 120), as well as other target tissue sites. Specific target tissue sites and / or regions within the brain 120 can be selected based on the patient's condition. Therefore, in some examples, the electrodes used to deliver electrical stimulation may be different from the electrodes used to sense neural brain signals. In other examples, the same electrodes can be used to deliver electrical stimulation as well as to sense brain signals. However, this configuration will require the system to switch between stimulation generation and sensing circuits, and can reduce the time the system can sense brain signals.

[0062] The electrical stimulation generated by IMD 106 can be configured to manage a variety of disorders and conditions. In some examples, the stimulation generator of IMD 106 is configured to generate electrical stimulation pulses via electrodes of a selected stimulation electrode combination and deliver the electrical stimulation pulses to patient 112. However, in other examples, the stimulation generator of IMD 106 can be configured to generate and deliver a continuous wave signal, such as a sine wave or a triangle wave. In either case, the stimulation generator within IMD 106 can generate electrical stimulation therapy for DBS according to a treatment program selected at a given time of treatment. In examples where IMD 106 delivers electrical stimulation in the form of stimulation pulses, the treatment program can include a set of treatment parameter values ​​(e.g., stimulation parameters), such as the stimulation electrode combination used to deliver the stimulation to patient 112, the pulse frequency, the pulse width, and the current or voltage amplitude of the pulses. As previously noted, the electrode combination can indicate the specific electrodes 116, 118 selected for delivering the stimulation signal to the tissue of patient 112, as well as the corresponding polarity of the selected electrodes.

[0063] IMD 106 can be implanted in a subcutaneous pocket above the clavicle, or alternatively, on or in skull 122, or at any other suitable site within patient 112. Generally, IMD 106 is constructed of biocompatible materials that resist corrosion and degradation by body fluids. IMD 106 can include an airtight housing to substantially enclose components such as a processor, therapy module, and memory.

[0064] like Figure 1 As shown, implant lead extension 110 is coupled to IMD 106 via connector 108 (also referred to as a connector block or connector of IMD 106). Figure 1 In the example of FIG, lead extension 110 is passed from the implant site of IMD 106 and along the neck of patient 112 to skull 122 of patient 112 to enter brain 120. Figure 1 In the example shown, leads 114A and 114B (collectively, "leads 114") are implanted in the right and left hemispheres, respectively, of patient 112 to deliver electrical stimulation to one or more regions of brain 120, which may be selected based on a patient condition or disorder controlled by treatment system 100. However, a particular target tissue site and stimulation electrode for delivering stimulation thereto may be selected based on, for example, identified patient behavior and / or other sensed patient parameters. Other lead 114 and IMD 106 implantation sites are contemplated. For example, in some examples, IMD 106 may be implanted on or in skull 122. Alternatively, leads 114 may be implanted in the same hemisphere, or IMD 106 may be coupled to a single lead implanted in a single hemisphere.

[0065] Existing lead sets include axial leads carrying ring electrodes at various axial locations and so-called "paddle" leads carrying planar array electrodes. Choosing the right electrode combination within an axial lead, within a paddle lead, or between two or more different leads presents challenges for clinicians. In some cases, more complex lead array geometries can be used.

[0066] Although lead 114 is Figure 1 106 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 within brain 120 through corresponding holes in skull 122. Leads 114 may be placed at any location within brain 120 so that electrodes 116, 118 can provide electrical stimulation to target tissue sites within brain 120 during treatment. For example, electrodes 116, 118 may be surgically implanted beneath the dura mater of brain 120 or within the cerebral cortex of brain 120 via a burr hole in skull 122 of patient 112 and electrically coupled to IMD 106 via one or more leads 114.

[0067] exist Figure 1 In the example shown, electrodes 116, 118 of lead 114 are shown as ring electrodes. Ring electrodes can be used in DBS applications because ring electrodes are relatively easy to program and can deliver electric fields to any tissue adjacent to electrodes 116, 118. In other examples, electrodes 116, 118 may have different configurations. For example, in some examples, at least some of electrodes 116, 118 of lead 114 may have a complex electrode array geometry that can produce a shaped electric field. The complex electrode array geometry may include multiple electrodes (e.g., partial rings or segmented electrodes) around the outer periphery of each lead 114, rather than one ring electrode. In this way, electrical stimulation can be directed from lead 114 in a specific direction to enhance the efficacy of the treatment and reduce possible adverse side effects caused by stimulating a large amount of tissue. In some examples, the housing of IMD 106 may include one or more stimulation and / or sensing electrodes. In an alternative example, lead 114 may have electrodes other than the following: Figure 1 For example, lead 114 may be a paddle lead, a ball lead, a bendable lead, or any other type of shape effective in treating patient 112 and / or minimizing the invasiveness of lead 114.

[0068] exist Figure 1In the example shown, IMD 106 includes memory for storing a plurality of therapy programs, each therapy program defining 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 identified patient behavior. IMD 106 may generate electrical stimulation based on the selected therapy program to manage patient symptoms associated with a movement disorder.

[0069] External programmer 104 wirelessly communicates with IMD 106 to provide or retrieve therapy information as needed. Programmer 104 is an external computing device that a user (e.g., a clinician and / or patient 112) can use to communicate with IMD 106. For example, programmer 104 can be a clinician programmer, which a clinician uses to communicate with IMD 106 and program one or more therapy programs for IMD 106. Alternatively, programmer 104 can be a patient programmer that allows patient 112 to select programs and / or view and modify therapy parameters. A clinician programmer may include more programming features than a patient programmer. In other words, more complex or sensitive tasks may be allowed only with a clinician programmer to prevent untrained patients from making undesirable changes to IMD 106.

[0070] When programmer 104 is configured for use by a clinician, programmer 104 can be used to transmit initial programming information to IMD 106. This initial information may include hardware information, such as the type and electrode arrangement of lead 114, the location of lead 114 within brain 120, the configuration of electrode arrays 116, 118, an initial program defining treatment parameter values, and any other information that the clinician wishes to program into IMD 106. Programmer 104 can also perform functional testing (e.g., measuring the impedance of electrodes 116, 118 of lead 114). In addition to or in lieu of programmer 104, a different external computing device can perform any of the functions of programmer 104. The external computing device can be a networked device and communicate with IMD 106 directly or via programmer 104.

[0071] The clinician can also store therapy programs within IMD 106 with the aid of programmer 104. During a programming session, the clinician can determine one or more therapy programs that can provide effective therapy to patient 112 to address symptoms associated with the patient's condition, and in some cases, symptoms specific to one or more different patient states (such as a sleeping state, a mobile state, or a resting state). For example, the clinician can select one or more stimulation electrode combinations with which to deliver stimulation to brain 120. During a programming session, the clinician can evaluate the efficacy of a particular program based on feedback provided by patient 112 or based on an assessment of one or more physiological parameters of patient 112 (e.g., muscle activity, muscle tone, stiffness, tremor, etc.). Alternatively, identified patient behavior based on video information can be used as feedback during the initial and subsequent programming sessions. Programmer 104 can assist the clinician in creating / identifying therapy programs by providing a structured system for identifying potentially beneficial therapy parameter values.

[0072] 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 changing critical functions of IMD 106 or the application that could be harmful to patient 112. Thus, programmer 104 may only allow patient 112 to adjust the values ​​of certain therapy parameters or set the available range of values ​​for a particular therapy parameter.

[0073] Programmer 104 may also provide indications to patient 112 when therapy is being delivered, when patient input has triggered a change in therapy, or when a power source within programmer 104 or IMD 106 needs to be replaced or recharged. For example, programmer 112 may include an alert LED, may send messages to patient 112 via a programmer display, generate audible sounds, or physical cues to confirm receipt of patient input, such as to indicate patient status or to manually modify therapy parameters.

[0074] Therapy system 100 may be implemented to provide chronic stimulation therapy to patient 112 over the course of months or years. System 100 may then also be employed on a trial basis to evaluate the therapy before committing to full implantation. If implemented temporarily, some components of system 100 may not be implanted in patient 112. For example, patient 112 may be fitted with an external medical device, such as a trial stimulator, instead of IMD 106. The external medical device may be coupled to the percutaneous leads or implanted leads via a percutaneous extension. If the trial stimulator indicates that DBS system 100 is providing effective therapy to patient 112, the clinician may implant a chronic stimulator in patient 112 for relatively long-term therapy.

[0075] Although IMD 104 is described as delivering electrical stimulation therapy to brain 120, in other examples, IMD 106 can be configured to direct electrical stimulation to other anatomical regions of patient 112. In other examples, system 100 can include an implantable drug pump in addition to or in place of IMD 106. Furthermore, an IMD can provide other electrical stimulation, such as spinal cord stimulation, to treat movement disorders.

[0076] According to the techniques of the present disclosure, system 100 defines a steady-state window and a therapeutic window for delivering adaptive DBS to patient 112. System 100 can adaptively deliver electrical stimulation and adjust one or more parameters defining the electrical stimulation within a parameter range defined by upper and lower limits of the therapeutic window based on the activity of a sensed signal (e.g., an LFP signal) within the steady-state window. For example, system 100 can adjust the one or more parameters defining the electrical stimulation in response to the sensed signal falling below a lower threshold of the steady-state window or exceeding an upper threshold of the steady-state window, but may not adjust the one or more parameters defining the electrical stimulation such that they fall below a lower limit of the therapeutic window or exceed an upper limit of the therapeutic window.

[0077] In one example, external programmer 104 issues a command to IMD 106 causing IMD 106 to deliver electrical stimulation therapy via electrodes 116, 118 via lead 114. As described above, the treatment window defines upper and lower limits for one or more parameters that define the delivery of the electrical stimulation therapy to patient 112. For example, the one or more parameters include current amplitude (for a current-controlled system) or voltage amplitude (for a voltage-controlled system), pulse frequency or frequency, and pulse width. In examples where electrical stimulation is delivered according to "bursts" of pulses or a series of electrical pulses defined by an "on time" and an "off time," the one or more parameters may also define one or more of the number of pulses per burst, the on time, and the off time. In one example, the treatment window defines upper and lower limits for one or more parameters, such as upper and lower thresholds for the current amplitude of the electrical stimulation therapy (in a current-controlled system) or upper and lower thresholds for the voltage amplitude of the electrical stimulation therapy (in a voltage-controlled system). While the examples herein are generally given with respect to adjusting voltage amplitude or current amplitude, the techniques herein are equally applicable to steady-state windows and therapeutic windows using other parameters such as, for example, pulse frequency or pulse width. Example embodiments of therapeutic windows are provided in further detail below.

[0078] Typically, patient programmer 104 may not have the ability to adjust any thresholds or limits for sensing or stimulation associated with adaptive DBS. For example, patient programmer 104 may only enable the patient to adjust stimulation parameter values ​​within limits set by the clinician programmer. However, in other examples, system 100 may provide adaptive DBS by allowing patient 112 to indirectly adjust activation, deactivation, and magnitude of electrical stimulation, for example, via patient programmer 104, by adjusting lower and upper thresholds of a steady-state window. In one example, patient programmer 104 may only be enabled to adjust the upper or lower thresholds by a small amount or percentage of a clinician-set value. In another example, by adjusting one or both thresholds of the steady-state window, patient 112 may adjust the point at which a sensed signal deviates from the steady-state window, thereby triggering system 100 to adjust one or more parameters of electrical stimulation within the parameter range defined by the lower and upper thresholds of the therapy window.

[0079] In some examples, the patient may provide feedback, for example, via programmer 104, to adjust one or both thresholds of the steady-state window. In another example, programmer 104 and / or IMD 106 may automatically adjust one or both thresholds of the steady-state window, as well as adjust one or more parameters of electrical stimulation within a parameter range defined by a lower threshold and an upper threshold of the therapy window. For example, IMD 106 may automatically adjust one or more thresholds of the steady-state window (e.g., in some examples, an upper threshold and a lower threshold) in response to, for example, a physiological parameter sensed by one or more sensors 109 of system 100, thereby adjusting the delivery of adaptive DBS. As another example, programmer 104 and / or IMD 106 may automatically adjust one or more thresholds of the steady-state window based on one or more physiological or neural signals of patient 112 sensed by IMD 106. For example, in response to a deviation of a patient's signal outside of a steady-state window, system 100 (e.g., IMD 106 or programmer 104) can automatically adjust one or more parameters defining the electrical stimulation therapy delivered to the patient in a manner proportional to the magnitude of the sensed signal and within a therapy window defining lower and upper thresholds for the one or more parameters. Adjustments to the one or more stimulation therapy parameters based on the deviation of the sensed signal can be proportional or inversely proportional to the magnitude of the signal.

[0080] Thus, in some examples, system 100 can adjust one or more parameters of electrical stimulation, such as voltage or current amplitude, within the therapeutic window based on patient input to adjust the steady-state window or based on one or more signals (such as sensed physiological parameters or sensed neural signals), or a combination of two or more thereof, via programmer 104 or IMD 106. Specifically, system 100 can automatically and / or in response to patient input to adjust the steady-state window adjust the parameters of electrical stimulation, provided that the values ​​of the electrical stimulation parameters are constrained to remain within a range specified by the upper and lower thresholds of the therapeutic window. This range can be considered to include the upper and lower thresholds themselves.

[0081] In some examples where the system 100 adjusts multiple parameters of electrical stimulation, the system 100 may adjust at least one of the voltage amplitude or current amplitude, stimulation frequency, pulse width, or electrode selection, among others. In such examples, the clinician may set an order or sequence for adjusting these parameters (e.g., adjusting the voltage amplitude or current amplitude, then adjusting the stimulation frequency, and then adjusting the electrode selection). In other examples, the system 100 may randomly select an adjustment sequence for the multiple parameters. In either example, the system 100 may adjust the value of a first parameter of the parameters of electrical stimulation. If the signal does not respond to the adjustment of the first parameter, the system 100 may adjust the value of a second parameter of the parameters of electrical stimulation, and so on, until the signal returns to within the steady-state window.

[0082] In order to adaptively adjust DBS based on the neural signal, for example, two or more electrodes 116, 118 of IMD 106 may be configured to monitor a neural signal (e.g., an LFP signal) of patient 112. In some examples, at least one of electrodes 116, 118 may be disposed on a housing of IMD 106, thereby providing a monopolar stimulation and / or sensing configuration. In one example, the neural signal is a signal within the beta frequency band of brain 120 of patient 112. For example, the neural signal within the beta frequency band of patient 112 may be associated with one or more symptoms of Parkinson's disease of patient 112. In general, the neural signal within the beta frequency of patient 112 may be approximately proportional to the severity of the symptoms of patient 112. For example, as tremors induced by Parkinson's disease increase, the neural signal within the beta frequency of patient 112 also increases (e.g., the magnitude of the signal and / or spectral power). Furthermore, the neural signal within the beta frequency is considered proportional because the system 100 can be configured such that an increase in the magnitude of the signal can trigger the system 100 to increase the magnitude of the delivered stimulation therapy according to the disclosed techniques. Similarly, as the tremor induced by Parkinson's disease decreases, the neural signal within the beta frequency of the patient 112 also decreases (e.g., the magnitude of the signal and / or spectral power), and this decrease can trigger the system 100 to decrease the magnitude of the delivered stimulation.

[0083] In some examples, each sensor within IMD 106 is an accelerometer, a bonded piezoelectric crystal, a mercury switch, or a gyroscope. In some examples, these sensors can provide a signal indicative of a patient's physiological parameter, which in turn varies based on the patient's activity. For example, the device can monitor a signal indicative of the patient's heart rate, electrocardiogram (ECG) morphology, electroencephalogram (EEG) morphology, respiratory rate, respiratory volume, core body temperature, subcutaneous temperature, or muscle activity.

[0084] In some examples, sensors generate signals based on both patient activity and patient position. For example, an accelerometer, gyroscope, or magnetometer can generate signals indicating both the activity and position of patient 112. External programmer 104 can use this information regarding position to determine whether external programmer 104 should perform adjustments to the therapy window.

[0085] For example, to identify body position, sensors such as accelerometers can be oriented substantially orthogonally relative to one another. In addition to being oriented orthogonally relative to one another, each sensor used to detect the body position of patient 112 can also be substantially aligned with an axis of the body of patient 112. When the accelerometers are aligned in this manner, for example, the magnitude and polarity of the DC component of the signal generated by the accelerometer indicate the orientation of the patient relative to the Earth's gravity, e.g., the body position of patient 112. More information regarding determining patient position using orthogonally aligned accelerometers can be found in commonly assigned U.S. Patent No. 5,593,431 to Todd J. Sheldon, the entire contents of which are incorporated herein by reference.

[0086] Other sensors that can generate signals indicative of the position of patient 112 include electrodes that generate signals, such as electromyography (EMG) signals, based on electrical activity within the muscles of patient 112, or bonded piezoelectric crystals that generate signals based on muscle contraction. The electrodes or bonded piezoelectric crystals can be implanted in the legs, buttocks, chest, abdomen, or back of patient 112 and connected wirelessly or via one or more leads to one or more of external programmer 104 and IMD 106. Alternatively, when IMD 106 is implanted in the buttocks, chest, abdomen, or back of patient 112, the electrodes can be integrated into the housing of IMD 106, or the piezoelectric crystals can be bonded to the housing. The signals generated by such sensors when implanted in these locations can vary based on the position of patient 112, for example, whether the patient is standing, sitting, or lying down.

[0087] Furthermore, the body position of patient 112 can affect the patient's thoracic impedance. Therefore, the sensor may include an electrode pair comprising an electrode integrated with the housing of IMD 106 and one of electrodes 116, 118 that generates a signal based on the thoracic impedance of patient 112. Based on this signal, IMD 106 may detect the body position or positional changes of patient 112. In one example (not depicted), the electrodes of the pair may be located on opposite sides of the patient's thorax. For example, the electrode pair may include an electrode located proximal to the patient's spine and used to deliver SCS therapy, and IMD 106, with the electrodes integrated into its housing, may be implanted in the abdomen or chest of patient 112. As another example, in addition to leads 114 implanted in the brain of patient 112, IMD 106 may also include electrodes implanted for detecting thoracic impedance. Body position or positional changes may affect the delivery of DBS or SCS therapy to patient 112 for treating any type of neurological disorder and may also be used to detect patient sleep, as described herein.

[0088] Additionally, changes in the position of patient 112 may cause changes in the pressure of the patient's cerebrospinal fluid (CSF). Accordingly, the sensor may include a pressure sensor coupled to one or more intrathecal or intraventricular catheters, or a pressure sensor coupled to IMD 106 wirelessly or via one of leads 114. Changes in CSF pressure associated with changes in position may be particularly evident within the patient's brain, e.g., in an intracranial pressure (ICP) waveform.

[0089] Thus, in some examples, the system 100 does not monitor the patient's neural signals, but rather monitors one or more signals from the sensors that are indicative of the magnitude of a physiological parameter of the patient 112. Upon detecting that the one or more signals from the sensors exceed an upper limit of a steady-state window, the system 100 increases stimulation at a maximum ramp rate determined by the clinician until the one or more signals from the sensors return to within the steady-state window, or until the magnitude of the electrical stimulation reaches an upper limit of a therapeutic window determined by the clinician. Similarly, upon detecting that the one or more signals from the sensors fall below a lower limit of the steady-state window, the system decreases stimulation at a maximum ramp rate determined by the clinician until the one or more signals from the sensors return to within the steady-state window, or until the magnitude of the electrical stimulation reaches a lower limit of a therapeutic window determined by the clinician. Upon detecting that the one or more signals from the sensors are within a threshold of the steady-state window, the system maintains the magnitude of the electrical stimulation constant.

[0090] Such a system 100 for delivering adaptive DBS to a patient by monitoring physiological parameters may offer advantages over other techniques that use neural signals as thresholds because the disclosed techniques allow an IMD to use hysteresis to control the delivery of therapy. In other words, such a system 100 uses the patient's physiological parameters to form a control loop for controlling not only the delivery of therapy but also the magnitude of the therapy delivered. Such a system may be less intrusive to the patient's activities because the system 100 adapts the stimulation to the patient's current needs and, therefore, may reduce the side effects experienced by the patient.

[0091] Furthermore, such a system 100 can use external sensors (such as accelerometers) instead of internal sensors (such as electrodes) to detect symptoms of a patient's disease and control the adjustment of the magnitude of one or more parameters of the treatment. For example, the system 100 can use a wrist sensor to detect wrist flexion or tremor in a patient with Parkinson's disease. Thus, such an IMD for monitoring physiological parameters can be less invasive than other IMD systems because the system of the present disclosure may not require sensing electrodes to be implanted in the brain of the patient 112.

[0092] In some cases, as described herein, system 100 may deliver a lower magnitude of electrical stimulation than is required for patient 112 to prevent his or her symptoms from flaring up, based on the upper and lower thresholds of the steady-state window. For example, a patient receiving treatment from IMD 106 (which uses the steady-state window to control the delivery of electrical stimulation therapy) may, in some cases, experience less than optimal results compared to when the patient receives continuous electrical stimulation therapy at a maximum therapeutic magnitude. To prevent this from occurring, system 100 may determine a value for the at least one electrical stimulation parameter defined by the steady-state window as described above. Additionally, IMD 106 of system 100 may increase the value of the at least one electrical stimulation parameter by an offset amount greater than the determined magnitude defined by the steady-state window in order to further prevent symptom flaring up for patient 112. Thus, system 100 may avoid delivering electrical stimulation therapy having a magnitude that may be insufficient to prevent symptom flaring up.

[0093] Figure 1 The architecture of the system 100 shown in FIG is shown as an example. The technology described in this disclosure can be used in Figure 1 The present invention may be implemented in the exemplary system 100 of the present invention, as well as in other types of systems not specifically described herein. For example, a clinician may determine an upper threshold and a lower threshold for a steady-state window. In other examples, one of the external programmer 104 and the IMD 106 determines the upper threshold and the lower threshold for a steady-state window. In addition, the external programmer 104 or the IMD 106 may receive a signal representing a signal from the patient 112 and determine adjustments to one or more parameters that define the electrical stimulation therapy delivered by the IMD 106 to the patient 112. Nothing in this disclosure should be construed to limit the technology of this disclosure to Figure 1An example architecture is shown.

[0094] Figure 2 is used to deliver adaptive deep brain stimulation therapy Figure 1 A block diagram of an exemplary IMD 106 is shown. Figure 2 In the example shown, IMD 106 includes processor 210, memory 211, stimulation generator 202, sensing module 204, switch module 206, telemetry module 208, sensor 212, and power supply 220. Each of these modules may be or include circuitry configured to perform the functions attributed to each respective module. For example, processor 210 may include processing circuitry, switch module 206 may include switching circuitry, sensing module 204 may include sensing circuitry, and telemetry module 208 may include telemetry circuitry. Switch module 204 may not be required for multiple current source and sink configurations. Memory 211 may include any volatile or non-volatile medium, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, etc. Memory 211 may store computer-readable instructions that, when executed by processor 210, cause IMD 106 to perform various functions. Memory 211 may be a storage device or other non-transitory medium.

[0095] exist Figure 2 In the example shown, the memory 211 stores the treatment programs 214 and the sensing electrode combinations and the associated stimulation electrode combinations 218 in a separate memory within the memory 211 or in a separate area within the memory 211. Each stored treatment program 214 defines a specific set of electrical stimulation parameters (e.g., a treatment parameter set), such as stimulation electrode combinations, electrode polarity, current or voltage amplitude, pulse width, and pulse frequency. In some examples, the individual treatment programs can be stored as a treatment group that defines a group of treatment programs that can be used to generate stimulation. The stimulation signals defined by the treatment programs of the treatment group can be delivered together on an overlapping or non-overlapping (e.g., time-interleaved) basis.

[0096] Sensing and stimulation electrode combinations 218 store sensing electrode combinations and associated stimulation electrode combinations. As described above, in some examples, the sensing and stimulation electrode combinations may include the same subset of electrodes 116, 118, the housing of IMD 106 serving as electrodes, or may include different subsets or combinations of such electrodes. Thus, memory 211 may store multiple sensing electrode combinations and, for each sensing electrode combination, information identifying the stimulation electrode combination associated with the corresponding sensing electrode combination. The association between the sensing electrode combination and the stimulation electrode combination may be determined, for example, by a clinician or automatically by processor 210. In some examples, corresponding sensing electrode combinations and stimulation electrode combinations may include some or all of the same electrodes. However, in other examples, some or all of the electrodes in the corresponding sensing electrode combination and stimulation electrode combination may be different. For example, a stimulation electrode combination may include more electrodes than the corresponding sensing electrode combination in order to increase the efficacy of the stimulation therapy. In some examples, as discussed above, stimulation may be delivered via a stimulation electrode combination to a tissue site that is different from a tissue site that is proximate to the corresponding sensing electrode combination but within the same region of the brain 120 (e.g., the thalamus) in order to mitigate any irregular oscillations or other irregular brain activity within the tissue site associated with the sensing electrode combination.

[0097] Under the control of processor 210, stimulation generator 202 generates stimulation signals for delivery to patient 112 via the selected combination of electrodes 116, 118. Example ranges of electrical stimulation parameters believed to be effective in managing movement disorders in patients during DBS include:

[0098] 1. Pulse frequency, ie, frequency: between about 40 Hz and about 500 Hz, such as between about 40 Hz and 185 Hz or such as about 140 Hz.

[0099] 2. For a voltage controlled system, voltage amplitude: between about 0.1 volts and about 50 volts, such as between about 2 volts and about 3 volts.

[0100] 3. In the alternative case of a current control system, current amplitude: between about 0.2 mA and about 100 mA, such as between about 1.3 mA and about 2.0 mA.

[0101] 4. Pulse width: between about 10 microseconds and about 5000 microseconds, such as between about 100 microseconds and about 1000 microseconds, or between about 180 microseconds and about 450 microseconds.

[0102] Thus, in some examples, stimulation generator 202 generates an electrical stimulation signal based on the above-described electrical stimulation parameters and applies an upper threshold and a lower threshold of a therapeutic window to one or more of these parameters, such that the applicable parameter is within the range specified by the window. Other ranges of therapeutic parameter values ​​may also be useful and may depend on the target stimulation site in patient 112. Although stimulation pulses are described, the stimulation signal may be in any form, such as a continuous time signal (e.g., a sine wave).

[0103] The processor 210 may include fixed-function processing circuitry and / or programmable processing circuitry and may include, for example, one or more of the following: 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 functionality attributed to the processor 210, which may be firmware, hardware, software, or any combination thereof. The processor 210 may control the stimulation generator 202 according to a therapy program 214 stored in the memory 211 to apply specific stimulation parameter values ​​specified by one or more programs, such as voltage or current amplitude, pulse width, or pulse frequency.

[0104] exist Figure 2 In the example shown, the set of electrodes 116 includes electrodes 116A, 116B, 116C, and 116D, and the set of electrodes 118 includes electrodes 118A, 118B, 118C, and 118D. The processor 210 also controls the switch module 206 to apply the stimulation signal generated by the stimulation generator 202 to the selected combination of electrodes 116, 118. Specifically, the switch module 204 can couple the stimulation signal to selected conductors within the lead 114, which in turn deliver the stimulation signal across the selected electrodes 116, 118. The switch module 206 can be a switch array, a switch matrix, a multiplexer, or any other type of switch module configured to selectively couple stimulation energy to the selected electrodes 116, 118 and selectively sense neural brain signals using the selected electrodes 116, 118. Thus, the stimulation generator 202 is coupled to the electrodes 116, 118 via the switch module 206 and the conductors within the lead 114. However, in some examples, IMD 106 does not include switch module 206 .

[0105] The stimulation generator 202 may be a single-channel or multi-channel stimulation generator. Specifically, the stimulation generator 202 may be capable of delivering a single stimulation pulse, multiple stimulation pulses, or a continuous signal at a given time via a single electrode combination, or delivering multiple stimulation pulses at a given time via multiple electrode combinations. However, in some examples, the stimulation generator 202 and the switch module 206 may be configured to deliver multiple channels on a time-interleaved basis. For example, the switch module 206 may be used to time-divide the output of the stimulation generator 202 across different electrode combinations at different times to deliver stimulation energy for multiple programs or channels to the patient 112. Alternatively, the stimulation generator 202 may include multiple voltage or current sources and sinks that are coupled to corresponding electrodes to drive the electrodes as cathodes or anodes. In this example, the IMD 106 may not require the time-interleaved multiplexing functionality of the switch module 206 for stimulation via different electrodes.

[0106] The electrodes 116, 118 on the corresponding leads 114 can be constructed from a variety of different designs. For example, one or both of the leads 114 may include two or more electrodes at each longitudinal position along the length of the lead, such as multiple electrodes at different peripheral positions around the periphery of the lead at each position in positions A, B, C, and D. In one example, the electrodes can be electrically coupled to the switch module 206 via corresponding wires that are straight or coiled within the housing of the lead and extend to a connector at the proximal end of the lead. In another example, each of the electrodes of the lead can be an electrode deposited on a film. The film may include a conductive trace for each electrode that extends to a proximal end connector along the length of the film. The film can then be wrapped (e.g., spirally wrapped) around an internal member to form the lead 114. These and other configurations can be used to form leads with complex electrode geometries.

[0107] Although the sensing module 204 and Figure 2 In one embodiment, stimulation generator 202 and processor 210 are incorporated into a common housing, but in other examples, sensing module 204 may be located in a separate housing from IMD 106 and may communicate with processor 210 via wired or wireless communication techniques. Exemplary neural brain signals include, but are not limited to, signals generated by local field potentials (LFPs) within one or more regions of brain 28. EEG and ECoG signals are other examples of electrical signals that may be measured within brain 120 or by electrodes placed in other locations relative to brain 120.

[0108] Sensor 212 may include one or more sensing elements that sense corresponding patient parameter values. For example, sensor 212 may include one or more accelerometers, optical sensors, chemical sensors, temperature sensors, pressure sensors, or any other type of sensor. Sensor 212 may output patient parameter values ​​that may be used as feedback to control therapy delivery. IMD 106 may include additional sensors within the housing of IMD 106 and / or coupled via one or other of leads 114. In addition, IMD 106 may receive sensor signals wirelessly from remote sensors, for example, via telemetry module 208. In some examples, one or more of these remote sensors may be located external to the patient's body (e.g., carried on an external surface of the skin, attached to clothing, or otherwise positioned external to the patient's body).

[0109] Under the control of processor 210, telemetry module 208 supports wireless communication between IMD 106 and external programmer 104 or another computing device. As updates to the program, processor 210 of IMD 106 can receive values ​​for various stimulation parameters (such as magnitude and electrode combinations) from programmer 104 via telemetry module 208. Updates to the therapy program can be stored in therapy program 214 portion of memory 211. Telemetry module 208 in IMD 106, as well as telemetry modules in other devices and systems described herein (such as programmer 104), can communicate via radio frequency (RF) communication techniques. In addition, telemetry module 208 can communicate with external medical device programmer 104 via proximal sensing interaction between IMD 106 and programmer 104. Thus, telemetry module 208 can send information to external programmer 104 continuously, at periodic intervals, or upon request from IMD 106 or programmer 104.

[0110] Power supply 220 delivers operating power to the various components of IMD 106. Power supply 220 may include a small rechargeable or non-rechargeable battery and power generation circuitry to generate operating power. Recharging may be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within IMD 220. In some examples, the power requirements may be small enough to allow IMD 220 to utilize patient motion and implement a kinetic energy harvesting device to trickle charge the rechargeable battery. In other examples, conventional batteries may be usable for a limited period of time.

[0111] In accordance with the techniques of the present disclosure, the processor 210 of the IMD 106 delivers electrical stimulation therapy to the patient 112 via electrodes 116, 118 (and optionally the switch module 206) inserted along the leads 114. The adaptive DBS therapy is defined by one or more therapy programs 214 having one or more parameters stored in the memory 211. For example, the one or more parameters include current amplitude (for current-controlled systems) or voltage amplitude (for voltage-controlled systems), pulse frequency or frequency, and pulse width or the number of pulses per cycle. In examples where electrical stimulation is delivered according to "bursts" of pulses or a series of electrical pulses defined by an "on time" and an "off time," the one or more parameters may also define one or more of the number of pulses per burst, the on time, and the off time. In one example, a therapy window defines upper and lower limits on the voltage amplitude used for the electrical stimulation therapy. In another example, a therapy window defines upper and lower limits on the current amplitude used for the electrical stimulation therapy. Specifically, parameters of the electrical stimulation therapy, such as voltage or current amplitude, are constrained to a treatment window having an upper and lower limit, such that the voltage or current amplitude can be adjusted as long as the amplitude remains greater than or equal to the lower limit and less than or equal to the upper limit. Note that in some examples, a single limit may be used.

[0112] In one example, processor 210 monitors behavior of signals from patient 112 within a steady-state window, via electrodes 116, 118 of IMD 106, that correlate with one or more symptoms of a disease of patient 112. Processor 210 delivers adaptive DBS to patient 112 via electrodes 116, 118 and may adjust one or more parameters defining electrical stimulation within a parameter range defined by a lower threshold and an upper threshold of a therapy window based on the activity of the sensed signals within the steady-state window.

[0113] In one example, the signal is a neural signal (e.g., an LFP signal) in the beta band of the brain 120 of the patient 112. The signal in the beta band of the patient 112 may be correlated with one or more symptoms of Parkinson's disease of the patient 112. Generally speaking, the neural signal in the beta band of the patient 112 may be roughly proportional to the severity of the symptoms of the patient 112. For example, as the tremor induced by Parkinson's disease increases, the magnitude of the neural signal in the beta band of the patient 112 detected by one or more of the electrodes 116, 118 also increases.

[0114] Similarly, as the tremor induced by Parkinson's disease decreases, the magnitude of the neural signal detected by processor 210 in the beta band of patient 112 via one or more of electrodes 116 and 118 also decreases. In another example, the signal is a neural signal in the gamma band of patient 112's brain 120. The signal in the gamma band of patient 112 may also be correlated with one or more side effects of the electrical stimulation therapy. However, in contrast to the neural signal in the beta band, the neural signal in the gamma band of patient 112 may generally be inversely proportional to the severity of the side effects of the electrical stimulation therapy. For example, as the side effects caused by the electrical stimulation therapy increase, the magnitude of the signal detected by processor 210 in the gamma band of patient 112 via one or more of electrodes 116 and 118 decreases. Similarly, as the side effects caused by the electrical stimulation therapy decrease, the magnitude of the signal detected by processor 210 in the gamma band of patient 112 via one or more of electrodes 116 and 118 increases.

[0115] In response to detecting that a patient's signal, such as a sensed physiological parameter signal or a sensed neural signal, has deviated from the steady-state window, the processor 210 dynamically adjusts the magnitude of one or more parameters of the electrical stimulation therapy, such as the pulse current amplitude or the pulse voltage amplitude, to drive the patient's signal back into the steady-state window. For example, where the signal is a neural signal in the beta frequency band of the brain 120 of the patient 112, the processor 210 monitors the beta magnitude of the patient 112 via one or more of the electrodes 116, 118. Upon detecting that the beta magnitude of the patient 112 exceeds an upper limit of the steady-state window, the processor 210 increases the magnitude of the electrical stimulation delivered via the electrodes 116, 118 at a maximum ramp rate, such as automatically or determined by a clinician, until the magnitude of the neural signal in the beta frequency band falls back into the steady-state window, or until the magnitude of the electrical stimulation reaches the upper limit of the therapeutic window determined by the clinician. Similarly, upon detecting that the beta magnitude of patient 112 has fallen below the lower limit of the steady-state window, processor 210 reduces the stimulation magnitude at a maximum ramp rate determined by the clinician until the beta magnitude rises back within the steady-state window, or until the magnitude of the electrical stimulation reaches the lower limit of the therapeutic window determined by the clinician. Upon detecting that the beta magnitude is now within the threshold of the steady-state window or has returned to within the threshold of the steady-state window, processor 210 maintains the magnitude of the electrical stimulation constant. In other examples, process 210 may automatically determine the ramp rate at which to adjust stimulation parameters to bring brain signals back into the target range. The ramp rate may be selected based on prior data indicating general patient comfort or the comfort or preferences of a particular patient.

[0116] In some examples, processor 210 measures the signals continuously in real time. In other examples, processor 210 periodically samples one or more bioelectric signals according to a predetermined frequency or after a predetermined amount of time. In some examples, processor 210 periodically samples the signals at a frequency of approximately 150 Hz.

[0117] In addition, the processor 210 delivers the electrical stimulation therapy constrained by the upper and lower limits of the treatment window. In some examples, the values ​​defining the treatment window are stored in the memory 211 of the IMD 106. For example, in response to detecting that the brain signal has deviated from the steady-state window, the processor 210 of the IMD 106 may adjust one or more parameters of the electrical stimulation therapy to provide responsive treatment to the patient 112. For example, in response to detecting that the signal has exceeded the upper threshold of the steady-state window and before delivering the electrical stimulation therapy, the processor 210 increases the amplitude of the stimulation (e.g., but not above the upper limit) in order to reduce the signal back below the upper threshold. For example, in a voltage-controlled system where the clinician has set the upper limit of the treatment window to 3 volts, the processor 210 may increase the voltage amplitude to a value no greater than 3 volts in an attempt to reduce the brain signal to below the upper threshold.

[0118] In another example, in response to detecting that the signal has fallen below the lower threshold of the steady-state window and before delivering electrical stimulation therapy, processor 210 reduces, for example, the voltage amplitude, but not below the magnitude of the lower threshold. For example, in the voltage control system described above where the clinician has set the lower limit of the treatment window to 1.2 volts, processor 210 may reduce the voltage amplitude to no less than 1.2 volts in an attempt to raise the brain signal back above the lower threshold and into the steady-state window. Thus, processor 210 of IMD 106 may deliver adaptive DBS to patient 112, wherein the one or more parameters defining the adaptive DBS are within the treatment window defined by the lower and upper limits of the parameters.

[0119] In the aforementioned examples, the limits of the therapeutic window are inclusive (i.e., the upper and lower limits are valid values ​​for the one or more parameters). However, in other examples, the limits of the therapeutic window are non-inclusive (i.e., the upper and lower limits are not valid values ​​for the one or more parameters). In such examples of non-inclusive therapeutic windows, the processor 210 instead sets the adjustment to the one or more parameters to the second highest valid value (if the adjustment potentially exceeds the upper limit) or the second lowest valid value (if the adjustment potentially exceeds the lower limit).

[0120] In another example, the values ​​defining the therapy window are stored in memory 311 of external programmer 104. In this example, in response to detecting that the signal has deviated from the steady-state window, processor 210 of IMD 106 transmits data representing a measurement of the signal to external programmer 104 via telemetry module 208. In one example, in response to detecting that the signal has exceeded an upper threshold of the steady-state window, processor 210 of IMD 106 transmits data representing a measurement of the signal to external programmer 104 via telemetry module 208. External programmer 104 may determine to adjust the parameter value to reduce the signal below the upper threshold, as long as the parameter value remains within the one or more limits for the parameter.

[0121] In another example, processor 210 receives instructions from external programmer 104 via telemetry module 208 to adjust one or more limits of the treatment window. For example, such instructions may be in response to patient feedback regarding the efficacy of the electrical stimulation treatment, or in response to one or more sensors that have detected signals from the patient. Such signals from the sensors may include neural signals (such as signals within the beta band or the gamma band of the patient's brain 120) or physiological parameters and measurements (such as signals indicating one or more of the patient's activity level, body position, and respiratory function). In addition, such signals from the sensors may indicate that one or more symptoms of patient 112 (such as tremor or stiffness) have not been alleviated or that there are side effects (such as paresthesia) caused by the electrical stimulation treatment. In response to these instructions, processor 210 may adjust one or more thresholds of the steady-state window. For example, processor 210 may adjust the magnitude of the upper threshold, the lower threshold, or move the overall position of the steady-state window so that the thresholds for adjusting the one or more parameters of the electrical stimulation defined by the steady-state window adjust themselves. Processor 210 then delivers the adjusted electrical stimulation to patient 112 via electrodes 116 and 118 .

[0122] Figure 3 yes Figure 1 1 is a block diagram of an external programmer 104. Although programmer 104 may generally be described as a handheld device, programmer 104 may be a larger portable device or a more stationary device. In some examples, programmer 104 may be referred to as a tablet computing device. Furthermore, in other examples, programmer 104 may be included as part of an external charging device or include the functionality of an external charging device. Figure 3As shown, programmer 104 may include a processor 310, a memory 311, a user interface 302, a telemetry module 308, and a power supply 320. Memory 311 may store instructions that, when executed by processor 310, cause processor 310 and external programmer 104 to provide the functionality attributed to external programmer 104 throughout this disclosure. Each of these components or modules may include circuitry configured to perform some or all of the functions described herein. For example, processor 310 may include processing circuitry configured to perform the processes discussed with respect to processor 310.

[0123] In general, programmer 104 includes any suitable hardware arrangement, alone or in combination with software and / or firmware, to perform the techniques attributed to programmer 104 and its processor 310, user interface 302, and telemetry module 308. In various examples, programmer 104 may include one or more processors, which may include fixed-function processing circuitry and / or programmable processing circuitry, such 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 combination of such components. In various examples, programmer 104 may also include memory 311 (such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, hard disk, CD-ROM) containing executable instructions for causing the one or more processors to perform the actions attributed to them. Furthermore, while processor 310 and telemetry module 308 are described as separate modules, in some examples, processor 310 and telemetry module 308 may be functionally integrated with each other. In some examples, processor 310 and telemetry module 308 correspond to respective hardware units, such as an ASIC, DSP, FPGA, or other hardware units.

[0124] Memory 311 (e.g., a storage device) may store instructions that, when executed by processor 310, cause processor 310 and programmer 104 to provide the functionality attributed to programmer 104 throughout this disclosure. For example, memory 311 may include instructions that cause processor 310 to obtain a parameter set from memory, select a spatial electrode motion pattern, or receive user input and send a corresponding command to IMD 104, or instructions for any other functionality. Furthermore, memory 311 may include multiple programs, each of which includes a parameter set that defines a stimulation therapy.

[0125] The user interface 302 may include buttons or a keypad, lights, a speaker for voice commands, a display, such as a liquid crystal (LCD) display, a light emitting diode (LED) display, or an organic light emitting diode (OLED) display. In some examples, the display may be a touch screen. The user interface 302 may be configured to display any information related to the delivery of stimulation therapy, identified patient behavior, sensed patient parameter values, patient behavior standards, or any other such information. The user interface 302 may also receive user input via the user interface 302. The input may be in the form of, for example, pressing a button on a keypad or selecting an icon from a touch screen. The user interface 302 may refer to hardware configured to present information to a user and / or receive input from a user. In some examples, the processor 310 directly controls the hardware. In other examples, the processor 310 may communicate with driver hardware that controls the hardware of the user interface 302. In a certain example, the user interface 302 may include a display configuration and / or interactive display configuration as described herein.

[0126] Under the control of processor 310, telemetry module 308 can support wireless communication between IMD 106 and programmer 104. Telemetry module 308 can also be configured to communicate with another computing device via wireless communication techniques or directly with another computing device via a wired connection. In some examples, telemetry module 308 provides wireless communication via RF or proximal inductive media. In some examples, telemetry module 308 includes an antenna, which can take various forms, such as an internal antenna or an external antenna.

[0127] Examples of local wireless communication technologies that can be used 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 way, other external devices may be able to communicate with programmer 104 without establishing a secure wireless connection. As described herein, telemetry module 308 may be configured to transmit spatial electrode motion patterns or other stimulation parameter values ​​to IMD 106 to deliver stimulation therapy.

[0128] In accordance with the techniques of this disclosure, in some examples, processor 310 of external programmer 104 defines parameters of a steady-state therapy window stored in memory 311 for delivering adaptive DBS to patient 112. In one example, processor 311 of external programmer 104 issues commands to IMD 106 via telemetry module 308, causing IMD 106 to deliver electrical stimulation therapy via electrodes 116, 118 and via leads 114.

[0129] The following examples illustrate various user interfaces and techniques for managing the sensing of physiological signals, such as brain signals, and managing electrical stimulation as described above. Programmer 104 or another external computing device may output the user interfaces and screens described herein. Figure 4 4 is a conceptual diagram illustrating an exemplary home screen 402 for navigating within the exemplary user interface 400. The user interface 400 may include several different screens as the user may navigate to different functions to view sensed information, view stored data, or adjust various stimulation parameter values. Figure 4 As shown in the example of FIG, home screen 402 includes information associated with patient 122, such as patient-specific information 406, such as name, patient ID, date of birth, and patient diagnosis. Other information may include device-specific information, such as model number, implant date, battery charge level, and estimated remaining battery life. Information such as the impedance status of the system and an event summary may also be provided in home screen 402. Screen 402 may also include a stimulation toggle switch 404, which, when selected, switches stimulation on or off. Stimulation toggle switch 404 may be provided in some, most, or all of the different screens within user interface 400 to enable the user to turn stimulation on or off at any time. Alert button 410 displays "No Alerts" because there are no alerts to be displayed. However, if there are alerts for the user, alert button 410 may indicate the presence of an alert or the number of alerts, and alert button 410 may be selectable to cause user interface 400 to display a list of alerts for the user.

[0130] Figure 4 Home screen 402 in FIG4 may also include a menu 408 that includes several selectable buttons that enable the user to navigate to other screens and functions supported by user interface 400. These selectable buttons include "Setup," "Stimulation," "Impedance," "MRI Qualification," "Replace," "Events," and "End Session." Programmer 104 may switch to the appropriate screen in response to user selection of the corresponding selectable button.

[0131] The Settings button takes the user to a screen associated with selecting an electrode configuration for sensing and / or stimulation. The Settings portion of user interface 400 may also provide a screen for receiving user input for capturing upper and / or lower thresholds for a steady-state window and / or upper and / or lower limits for a therapy window. The Stimulation button takes the user to a screen associated with managing electrical stimulation therapy for the patient. The Impedance button takes the user to a screen associated with viewing the impedance of one or more electrode combinations and / or leads and running impedance tests for any electrical pathways.

[0132] The MRI Qualification button takes the user to screens associated with checking the MRI qualification of any implanted device (e.g., IMD 106) and / or placing the implanted device into an MRI-qualified mode. The Replace button causes the user interface 400 to replace screens associated with when the IMD 106 should be replaced (e.g., the remaining operating life of the primary battery non-rechargeable power source). The Events button enables the user to navigate to various screens displaying events and data associated with sensing and delivering electrical stimulation. The End Session button enables the user to terminate the management session via the user interface 400. In addition to this menu, the user interface 400 may also include a stimulation toggle switch that enables the user to request stimulation to be turned on or off.

[0133] The user interface 400 can be configured for a clinician programmer that enables a clinician to manage all aspects of stimulation therapy and / or sensing. In some examples, the user interface 400 can enable a clinician programmer to have a different language than a patient programmer that is configured to enable a patient to control a subset of features associated with the IMD 106. For example, the user interface 400 can enable a clinician to set a patient programmer language in a settings button, where the patient programmer language is different from the language of the user interface 400 presented by the clinician programmer. For example, the user interface 400 can enable a clinician to set therapy group names, device names, and patient events to be presented in the patient's local language, regardless of the primary or supported clinician language of the user interface 400. In this way, the user interface 400 can enable a clinician (or an interpreter assisting the clinician) to program group names and patient events in the patient's desired language, even if that language is not the clinician's primary language.

[0134] Figure 5 and Figure 6 4 is a conceptual diagram illustrating an exemplary setup screen for managing electrode configurations. Programmer 104 may be configured to control the display of user interface 400, which includes a screen for reviewing and selecting an electrode configuration for sensing brain signals. In some examples, programmer 104 may control IMD 106 to check signal quality across all electrodes and leads (e.g., in different hemispheres) for this purpose or guide the user to select an appropriate sensing electrode configuration. This appropriate sensing configuration may also be appropriate for stimulation, as the sensing electrode configuration may be compatible with an effective stimulation electrode configuration for treatment.

[0135] In some examples, programmer 104 may evaluate all constraints and known information about stimulation outcomes, such as electrode impedance, signal power in one or more frequency bands, electrode combinations selected for treatment, or other such factors. For example, for each lead or hemisphere, programmer 104 may recommend a sensing electrode configuration based on one, some, or all of the following factors: electrodes available for sensing due to the use of parallel stimulation electrodes, the sensed signals of interest (e.g., one or more of a predetermined signal range or peak power in a particular frequency band, such as the beta or gamma bands), previously collected information regarding the effects and / or side effects of various electrodes at certain stimulation parameter values ​​(e.g., Figure 8 and Figure 9 as shown) or identified artifact sources due to other signals such as electrocardiogram (ECG) artifacts.

[0136] The user interface 400 may include configuration options that enable a user to configure or adjust one or more aspects of the sensing electrode configuration setup process. For example, the programmer 104 may provide a frequency selection input (e.g., Figure 10 ), the frequency selection input adjusts the frequency of the signal used for feedback in response to the user selecting a different frequency. Programmer 104 may provide this frequency selection input for one or more frequency bands, such as a beta band and a gamma band. In addition, user interface 400 may provide selectable inputs that enable the user to adjust the frequency of the high-pass filter or the type of filter, the sensing blanking duration, the averaging duration of the signal, or whether an electrode (or combination of electrodes) that captures artifacts (e.g., ECG or EMG artifacts) is selectable for sensing brain signals (e.g., Figure 11 ). In other examples, the user interface 400 may enable an artifact contrast input that may allow a user to specify an artifact amount (or several selectable artifact levels) that is acceptable for a sensing electrode configuration.

[0137] In some examples, user interface 400 may provide additional features. For example, programmer 104 may include different default settings for sensing electrode configuration settings based on an indication of a patient's treatment. For example, a user may input a specific type of condition or desired treatment (e.g., Parkinson's disease, tremor, epilepsy, depression, etc.), and programmer 104 may control user interface 400 to set default settings for sensing electrode configuration (e.g., target frequency band, electrode configuration, filter, blanking interval, averaging duration, etc.), which may reduce the need for user adjustments. Programmer 104 may also include automatic selection of frequency band power when multiple peaks exist in a frequency band. For example, programmer 104 may be configured to select one of the multiple peaks for sensing based on the magnitude of each peak relative to adjacent frequencies, the location of the frequency relative to common frequencies, the proximity of the peaks to each other, or any other such factors. In some examples, programmer 104 may set or suggest (for user confirmation) a specific bandwidth for sensing the power of the sensed signal. This specific bandwidth may be set, for example, to a predetermined and fixed range, such as 5 Hz. However, programmer 104 may select a different fixed range based on the frequency width of the power peak in the power spectrum, the presence of adjacent peaks, the absence of adjacent peaks, or an indication by the patient. In some examples, programmer 104 may enable a bandwidth selection input configured to receive user input selecting a different frequency range desired by the user (e.g., less than or greater than the suggested bandwidth). Such a bandwidth input may be provided as, for example, a slider or Figure 10 The user interface 400 can illustrate the changing bandwidth on the graph by expanding or shrinking different colored columns around the shown target frequency.

[0138] In another example, programmer 104 may suggest different default settings for signal quality based on the type of lead selected (or indicated as implanted in the patient). For example, programmer 104 may use a different electrode combination to sense from a lead having all annular electrodes compared to a lead having some electrodes at different circumferential locations around the lead. Additionally, programmer 104 may change filter settings, blanking duration, averaging duration, frequency bands, etc. based on the type of lead indicated as implanted in the patient.

[0139] exist Figure 5 In the example of FIG, the brain sensing setup screen 502 has been entered to select an electrode configuration for sensing brain signals (such as LFP signals). Menu 504 indicates the current stage of setup, which is in Figure 5106. The program 106 is shown as "Brain Sensing Setup" in FIG. 10. As the user progresses through the different stages of setup, the corresponding stages are underlined to show the current status. "Refresh Signal Test" button 506, when selected by the user, causes programmer 104 to control IMD 106 to run a signal test on one or more pathways (e.g., different electrode combinations). Each pathway is a different possible electrode combination for electrodes implanted in the patient. For each pathway, IMD 106 collects brain signals for a certain period of time (such as 30 seconds). Each pathway can be a pathway between two or more different electrodes of a lead (e.g., a sensing electrode combination).

[0140] Figure 5 The screen may display all electrode combinations for a particular lead. Lead selector 508 indicates which lead or hemisphere of the brain the lead is located in has been selected (e.g., Figure 5 Left STN in the example). Although Figure 5 A four-electrode lead is shown in the example of FIG, but other leads with fewer or greater numbers of electrodes may be used in other examples. In some examples, the lead may have multiple electrodes located at different circumferential positions around the perimeter of the lead alone or in combination with ring electrodes or other electrode patterns. Figure 5 A screen showing all pathways (or all sensing electrode combinations) on corresponding selectable cards 510 is shown. Each card 510 may provide the frequency of the brain signal that provides the maximum amplitude. For example, Figure 5 The selected card 510A in the β band indicates a frequency of 22.46 Hz. No signals have been selected for the respective different paths of cards 510B and 510C. Figure 5 When too many pathways are shown on the screen, user interface 400 can be controlled to show only the cards for pathways that provide a better signal. In other examples, user interface 400 can group combinations based on their type (e.g., where the electrodes are located in the lead) or other factors. Advanced settings 518 is a selectable icon that, when selected, causes programmer 104 to display additional settings for stimulation.

[0141] Thus, the processing circuitry 310 of the programmer 104 can be configured to obtain brain signal information for at least one electrode combination from a plurality of electrode combinations of one or more electrical leads, determine a corresponding frequency for the at least one electrode combination based on the brain signal information, and output a plurality of selectable lead icons (e.g., cards 510) for display, wherein each of the plurality of selectable lead icons represents a different electrode combination from the plurality of electrode combinations. Furthermore, the processing circuitry 310 can output the corresponding frequency determined for the at least one electrode combination in association with a corresponding selectable lead icon associated with the at least one electrode combination for display, receive user input selecting one of the plurality of selectable lead icons, and, in response to receiving the user input, select the sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing.

[0142] The processing circuit 310 may further output a selectable signal test icon for display, receive user input selecting the selectable signal test icon, and, in response to receiving the user input selecting the selectable signal test icon, control the medical device to obtain brain signal information for at least one electrode combination from the plurality of electrode combinations. The plurality of electrode combinations may include all possible electrode combinations for the one or more electrical leads implanted in the patient, although fewer than all combinations may be shown in other examples.

[0143] In some examples, the processing circuit 310 may analyze the brain signal information for the presence of artifacts associated with at least one of electrocardiographic sensing or movement of the one or more electrical leads, determine that the artifact is not present in the brain signal information, and in response to determining that the artifact is not present, approve the one or more electrode combinations for user selection for subsequent brain signal sensing. In this way, the processing circuit 310 can determine whether the electrode or electrode combination is suitable for sensing or is potentially problematic and cannot provide accurate and / or consistent sensed data. The processing circuit 310 may perform ECG artifact detection in several different ways, either individually or in combination. In some examples, the processing circuit 310 analyzes the presence of artifacts in the brain signal information by applying a logistic regression classifier to at least a portion of the brain signal information. The logistic regression classifier can be a machine learning method trained using LFP data collected from a previous patient group. Other types of machine learning algorithms, such as neural networks, support vector machines, extreme random trees, random forests, or other types of classifiers, may be used in other examples.

[0144] The logistic regression classifier may include spectral band power features and time domain threshold crossing statistical features. The processing circuit 310 may initially filter the sensed brain signal, such as removing the first portion (e.g., 10 seconds) and the last portion (e.g., 2.5 seconds) to avoid transient signals. The processing circuit 310 may determine the spectral features by calculating the band power within several frequency intervals. In one example, these bands may include 0 Hz to 3 Hz, 3 Hz to 5 Hz, 5 Hz to 10 Hz, 10 Hz to 20 Hz, 20 Hz to 30 Hz, 40 Hz to 50 Hz, 50 Hz to 60 Hz, 70 Hz to 80 Hz, and 80 Hz to 90 Hz. The processing circuit 310 may then normalize the power of each band by dividing it by the total power calculated in the band from 0 Hz to 90 Hz. The processing circuit 310 may then calculate the entropy of the normalized band power. In some examples, the entropy of the normalized band power is summed for use by the logistic regression classifier.

[0145] Temporal features can be determined by calculating threshold crossings from the rectified and normalized LFP signal. Processing circuit 310 can determine the threshold crossing rate for several different thresholds. Processing circuit 310 can then determine the inter-threshold crossing interface (e.g., the number of seconds between consecutive threshold crossings). Processing circuit 310 can then determine the entropy of each inter-threshold crossing interval. In other examples, a logistic regression classifier or other machine learning algorithm can use these temporal features as a supplement to the spectral features.

[0146] The input to the logistic regression classifier may include the amplitude or power of a selected frequency range from the brain signal, so that frequency domain and / or time domain input may be used. In one example, the processing circuit 310 may determine a plurality of signal features from the brain signal information, the plurality of signal features including entropy of a plurality of frequency bands within the brain signal information and a plurality of time domain threshold crossing features. The processing circuit 310 may then apply the logistic regression classifier to the portion of the brain signal information by applying the logistic regression classifier to the plurality of signal features. In some examples, the probability threshold of the logistic regression classifier may be set to 0.5, where any case greater than 0.5 is output as a brain signal including ECG artifacts and any case of 0.5 or less is output as a brain signal not including ECG artifacts.

[0147] As another way to identify ECG artifacts, the processing circuit 310 can analyze the fast Fourier transform (FFT) amplitude spacing of the brain signal information at approximately 8 Hz between a first brain signal detected during electrical stimulation delivery and a second brain signal detected during a period when electrical stimulation was not being delivered. In this way, an FFT amplitude spacing that is less than a spacing threshold indicates the absence of artifacts. In some examples, the IMD 106 may be more susceptible to ECG artifacts when stimulation is delivered at 0 mA, so this check helps identify those situations. In one example, the absolute value of the FFT amplitude difference at 8 Hz between cessation of stimulation and 0 mA stimulation is compared to a threshold value (e.g., 200 nV / rtHz). If the FFT amplitude difference is greater than the threshold value, the system determines that the spacing is too large and the electrode configuration is susceptible to ECG artifacts.

[0148] Thus, processing circuitry 310 may evaluate several aspects of the recorded brain signals from each electrode combination. Processing circuitry 310 may evaluate the brain signals to determine the absence of ECG artifacts. Furthermore, processing circuitry 310 may analyze the brain signals to determine the absence of motion artifacts. Furthermore, processing circuitry 310 may determine whether the brain signal amplitude is above a predetermined threshold. For the example of an LFP signal, the threshold may be 1.2 uVp (microvolt peak).

[0149] The processing circuit 310 can automatically select a frequency from the brain signal with the largest amplitude or power in the frequency domain. The electrode combination can then use this frequency to monitor changes in the brain signal. However, the user interface 400 can receive user selection of an edit button, thereby allowing the user to select a frequency different from the automatically selected frequency. For example, the user can select a frequency from a power versus frequency graph based on the test signal of the electrode combination.

[0150] The "Review" button 512 provides a summary of the effects, side effects, amplitudes, etc. that the clinician has established for that pathway and for a particular patient. For example, the clinician may have previously performed a monopolar review of all electrode pathways to identify any effects and side effects associated with stimulation of each electrode. In this way, the user may be able to access these notes about each electrode combination from the card for that particular electrode combination. The user may then be able to balance sensing with treatment. For example, the user may select a different electrode combination based on information other than the frequency of the sensed brain signal for that electrode combination.

[0151] Once the electrode configuration has been selected, the user may select the "Save and Exit" button 514, causing the processing circuitry 310 to proceed to a different screen where sensing and therapy may begin. Alternatively, the processing circuitry 310 may receive a user selection of the "Next Page" button 516 and responsively move to the next screen where thresholds may be established for adaptive DBS therapy. Figure 6In the example of , screen 602 is similar to screen 502 and shows a highlighted card 510A for a selected electrode combination indicating that therapy is being delivered using the electrode combination of the selected card 510A.

[0152] Figure 7 is a flow chart illustrating an exemplary technique for running a signal test that evaluates one or more aspects of an electrode configuration. The signal test is configured to evaluate the presence and / or prevalence of a specific brain signal across all electrode configurations available for a medical device. Such a process may utilize Figure 4 、 Figure 5 and Figure 6 Portion of user interface 400 is shown.

[0153] exist Figure 7 In the example of FIG, the processing circuit 310 obtains brain signal information of at least one electrode combination among a plurality of electrode combinations of one or more electrical leads (702), and then determines a corresponding frequency of the at least one electrode combination based on the brain signal information (704). An exemplary signal obtained during this process may be similar to Figure 58 and Figure 59 The processing circuit 310 then outputs a plurality of selectable lead icons for display (706), such as Figure 5 Selectable card 510. Each of the plurality of selectable lead icons represents a different electrode combination in the plurality of electrode combinations. The processing circuit 310 then outputs the corresponding frequency determined for the at least one electrode combination in association with the corresponding selectable lead icon associated with the at least one electrode combination for display (708). The processing circuit 310 receives user input (710) selecting one of the plurality of selectable lead icons, and in response to receiving the user input, selects the sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing (712). The user can repeat this process at any time during patient treatment or monitoring.

[0154] Figure 8 and Figure 9 is a conceptual diagram illustrating exemplary user interface screens 802 and 902 that display information associated with stimulation effects on a patient. Figure 8 and Figure 9The information may provide access to previously captured clinician evaluations of electrode feasibility for one or more electrode combinations. In some examples, a previously captured clinician evaluation may have been performed using a monopolar electrode combination (e.g., one electrode on the lead and another electrode remote from the lead, such as an electrode carried by the housing of the IMD). By providing this evaluation information for the electrodes in conjunction with the signal selection and evaluation process, the clinician and / or automated system may quickly access additional contextual information when making the most appropriate signal selection for sensing and / or stimulation. Figure 5 The "Review" button 512 visits Figure 8 and Figure 9 screen.

[0155] like Figure 8 As shown, screen 802 displays the severity of various side effects (such as bradykinesia, muscle contraction, and paresthesia) for corresponding stimulation parameter sets 806 in data fields 808. Each parameter set 810 shows the values ​​of amplitude, pulse width, and frequency. Each data point for various side effects may include a numerical indicator, a word indicator, and / or a graphical indicator. Menu 804 indicates that screen 802 shows a table of this information. Figure 9 As shown in the example of FIG, screen 902 shows an exemplary graph 904 showing the severity of side effects and the severity of symptoms for different current amplitudes of stimulation. Each graph is provided for a single day, but in other examples, multiple days can be combined. Parameter value 906 indicates the pulse width and frequency of the stimulation delivered. Menu 804 indicates that screen 802 shows a graph version of this information.

[0156] When generating suggested sensing electrode configurations, programmer 104 may utilize historical data for the patient or other patients with similar conditions. For example, programmer 104 may identify those electrode combinations that provide effective treatment (e.g., a therapeutic effect with no or limited side effects) and only recommend sensing configurations that are compatible with those electrode combinations used for treatment. Programmer 104 may identify those electrode combinations that would not be used for treatment. In some examples, programmer 104 may control user interface 400 to indicate which sensing electrodes can be used for stimulation electrode combinations that can provide effective treatment. Figure 8 and / or Figure 9 Screens 802 and 902 may also indicate a therapy window, threshold, or other stimulation parameter associated with the identified electrode combination. Programmer 104 may control the user interface to present a therapy window, e.g., for each electrode combination when it is useful to identify those electrode combinations that may provide a larger therapy window and potentially better stimulation therapy.

[0157] Figure 10is a conceptual diagram showing an exemplary screen 1000 for adjusting a frequency band for sensing brain signals using an electrode configuration. Figure 10 As shown, in the frequency domain Figure 5 Brain signal 1010 recorded for the electrode configuration during the signal inspection of FIG. The processing circuit 310 has automatically selected a frequency 1012 having a peak 1008 in the beta band 1002 as the frequency to monitor during brain signal sensing. The frequency indicator 1006 indicates that the frequency is 22.46 Hz. This peak 1008 may be selected because it provides the best sensing of changes in brain signal information. However, via Figure 10 In screen 1000, user interface 400 provides a user-movable slider 1016 that, when selected, enables the user to drag slider 1016 along the x-axis and select a different frequency. Frequency range 1014 indicates the frequency range over which the power of signal 1010 will be used to monitor brain activity. In some examples, frequency range 1014 may be a preset difference from frequency 1012, such as 5 Hz on either side of frequency 1012. In other examples, screen 1000 may include an adjustment input through which the user can change frequency range 1014. In other examples, programmer 104 may automatically select the width of frequency range 1014 based on the width of peak 1008 or some other characteristic of signal 1010. While both beta band 1002 and gamma band 10004 are shown, other examples may include only one band. In response to user selection of close button 1018, user interface 400 may close screen 1000 and return to a setup screen, such as screen 502.

[0158] Figure 11 1 is a conceptual diagram illustrating an exemplary screen 1100 for setting various sensing parameters for an electrode configuration. Figure 11 As shown in the example of FIG, the user interface 400 may provide a screen 100 that includes sensing parameters such as a high-pass filter frequency 1102, a sensing blanking duration 1104, and an average sensing duration 1106. Each of these parameters may be selected and changed by the user. In addition, the user may be able to determine whether an electrode combination including artifacts is selectable for sensing by selecting one of the allow artifact input boxes 1108.

[0159] Figure 12 1 is a conceptual diagram illustrating an exemplary screen 1200 for selecting the type of adaptive DBS mode. Figure 12As shown in the example of , user interface 400 may include screen 1200 that enables selection of dual threshold mode 1202, single threshold mode 1204, or single threshold inverse mode 1206. Dual threshold mode 1202 is shown as being selected. Dual threshold mode 1202 enables the system to adjust the stimulation amplitude based on an upper threshold and a lower threshold of the LFP signal. Single threshold mode 1204 enables the system to increase stimulation when the LFP signal is above the threshold, and single threshold inverse mode 1206 enables the system to decrease stimulation when the LFP signal is below the threshold.

[0160] This feature of adaptive DBS is intended to allow clinicians to configure treatment based on changes in brain state to automatically adjust within clinician-defined limits. Brain signals (such as LFP) recorded long-term from implanted electrodes will be used to measure the patient's brain state. The goal of automatic adjustment of treatment can be to keep the brain state (as defined by these signals) within a range specified by the clinician (e.g., in the dual threshold mode example, between an upper threshold and a lower threshold) due to the recognition that clinical symptoms and side effects can be well correlated with these detected brain states. In this way of managing brain state, users may be able to manage clinical symptoms and side effects. This feature is called closed-loop DBS or "aDBS" (adaptive DBS). "cDBS" refers to continuous DBS (i.e., manually controlled and open-loop, as in traditional DBS systems).

[0161] Thus, the user interface 400 enables the user to configure adaptive therapy by selecting algorithms, thresholds, and / or stimulation settings for an adaptive stimulation mode. In addition to selecting one of the threshold modes, the user interface 400 also enables the user to configure and adjust one or more thresholds (such as thresholds) that instruct the system to automatically adjust or change the value of a stimulation parameter. Figures 13 to 21 ). The user interface 400 also enables the user to configure other stimulation settings, changes, limits, transition times, and other Figure 22 and Figure 23 In some examples, user interface 400 enables a user to view, measure, and evaluate the performance of adaptive stimulation using set thresholds (e.g., Figures 25 to 32 ). User interface 400 may also include other tools for evaluating stimulation, such as tracking events, LFP signals, and stimulation parameters over time.

[0162] In other examples, programmer 104 may provide additional features. For example, programmer 104 may automatically propose a threshold mode (e.g., a dual threshold or a signal threshold) based on historical timeline data. In some examples, programmer 104 may detect poor or reduced performance based on one or more features, such as a signal quality check, oscillation of the stimulation amplitude of the LFP signal, the LFP signal being outside of threshold for more than a threshold time, the LFP value remaining at an upper threshold or lower threshold for longer than a predetermined amount of time, the patient disconnecting stimulation more than a predetermined number of times or frequency, or any other such event. In some examples, user interface 400 may enable a user to adjust one or more thresholds and / or stimulation parameter values ​​for stimulation while viewing LFP data and / or stimulation parameter values ​​in real time.

[0163] Figures 13 to 20 is a conceptual diagram illustrating an exemplary screen for capturing one or more thresholds associated with adaptive DBS therapy. Thus, user interface 400 enables a user to define thresholds to quantify changes in the signal over time. These thresholds can be used to aggregate large amounts of data to understand patterns that may reveal abnormalities worthy of further investigation. Figures 13 to 20 An example of a user interface 400 that enables a user to configure, view, and measure signals for one or more thresholds is shown. For example, a user can set upper and lower thresholds for the LFP signal and adjust the stimulation amplitude value to bring the brain into a state consistent with the desired thresholds. The user interface 400 allows the user to manually adjust the LFP thresholds and display the thresholds on stored data and / or real-time data. The user interface 400 can also display the amount of time the LFP signal is below, between, or above these thresholds.

[0164] In other examples, the user interface 400 may display one or more thresholds on the same display as the event data, or enable the user to set thresholds from a timeline, trend, or event data screen. In some examples, the user interface 400 may enable the user to adjust no-stimulation threshold settings, such as settings related to medication status or other patient conditions during stimulation. The user interface 400 may additionally or alternatively show information such as long-term averages of LFP values ​​or the time below, between, or above a threshold, identification of days or times when the LFP data is a statistical outlier with respect to other data, differences between night and day (or awake and asleep), or other averages or statistics for each stimulation parameter value.

[0165] like Figure 13As shown in the example of , a representation of the leads and the electrodes carried thereon is displayed in screen 1300. The cathode and anode electrodes are also indicated to show the selected electrode configuration as part of the lead view 1304. Menu 1302 indicates that the lead view 1304 is currently displayed, but annotations of the electrode configuration may alternatively be shown. To the right of the lead view 1304, an LFP coordinate graph 1306 and a stimulation parameter coordinate graph 1308 are displayed. A capture button 1310 enables the user to request capture of the LFP at the current amplitude. At the far right of screen 1300 is a parameter view 1314, which includes inputs selectable by the user to increase (button 1318) and decrease (button 1320) stimulation parameters, which are Figure 13 The current amplitude in the example of . Button 1316 jumps to the set upper amplitude limit. Button 1322 jumps to the lower amplitude limit (when set). Parameter button 1324 enables the user to select the desired parameter to be adjusted, such as amplitude, pulse width or frequency. Figure 13 On this screen, the user can set parameter value limits corresponding to respective thresholds for brain signals (such as LFP). Passive sensing button 1312 causes programmer 104 to save LFP values ​​for sensing only and not for adaptive stimulation. The user can move between different screens of user interface 400 via previous page button 1210 and next page button 1212.

[0166] Using these screens of user interface 400, the user can capture LFP thresholds corresponding to respective stimulation parameter values. In this way, the system can use stimulation as an actuator to determine LFP classification thresholds. In one example, each threshold can be set based on measuring LFP for 25 seconds at a specific amplitude level defined by the patient's tolerance and symptom relief. Other sensing durations can be used in other examples.

[0167] Typically, in order to set the upper and lower thresholds for brain signal monitoring, the patient has stopped taking the medication, that is, the upper and lower thresholds are set when the patient is not taking the medication selected to alleviate these symptoms. The patient can be considered not to have taken the medication in the following cases: for sustained-release dopamine agonists, the patient has not taken the medication for at least about 72 hours before the time when the upper limit is set; for conventional dopamine agonists and controlled-release CD / LD, the patient has not taken the medication for at least about 24 hours; and for conventional CD / LD, entacapone, rasagiline, selegiline and amantadine, the patient has not taken the medication for at least about 12 hours. If the stimulation only suppresses brain signals (e.g., LFP signals), the system can measure these brain signals for each value of the stimulation parameter without external input. Once the upper and lower thresholds are established, the system can identify when the drug effect disappears because the brain signal will cross the lower or upper threshold. In response to identifying that the brain signal crosses the threshold, the system can turn on electrical stimulation to restore the brain signal amplitude back to between the lower and upper thresholds. Thresholds can be set for certain brain signals (such as signals in the beta band) when the patient is off medication. In some examples, such as when evaluating signals in the gamma band, thresholds can be set when the patient is taking medication.

[0168] Since the patient is not taking any medication, there may be LFP activity above a threshold (such as greater than or equal to 1.2 uVp). In this process, the user will identify the lowest current amplitude at which the symptoms are controlled, which will be related to the upper threshold of the LFP signal. Figure 14 Increasing stimulation amplitudes are shown, with the resulting volume of activation (VOA) shown above the lead representation. Figure 14 In the example of FIG, screen 1400 shows that the increase in stimulation amplitude has caused stimulation to be delivered to the patient as indicated by stimulation field 1402. Slider 1404 can be selected and dragged by the user to increase or decrease the amplitude of the stimulation. This minimum amplitude will also be set as the lower limit of the stimulation parameters. Figure 15 Via screen 1500 it is shown that an upper threshold exists and can be captured as upper threshold 1504. Bubble 1502 informs the user to set the amplitude before capturing the lower LFP threshold. The beta signal will be high because there is little stimulation amplitude to suppress brain activity. Figure 16 Screen 1600 is shown including an exemplary pop-up window 1602 requesting patient confirmation of an upper threshold capture at current amplitude. The system will set the upper threshold here in response to the user selecting the confirm button.

[0169] Figure 17Screen 1700 is shown where the upper threshold 1504 has been captured and the lower limit of the current amplitude has been set. The user then increases the current amplitude to the highest amplitude that has no side effects (or in other examples has side effects that are acceptable to the patient). Figure 17 As shown, the current amplitude has been increased to 3.6 mA using slider 1404, while VOA or stimulation field 1402 is shown along with a representation of lead 1304. User selection of capture button 1310 captures the sensed LFP amplitude as the lower threshold and sets the current amplitude as the upper limit of the amplitude range. Figure 18 Screen 1800 is shown including an exemplary pop-up window 1802 requesting the patient to confirm a lower threshold capture at current amplitude in response to the user selecting the capture button 1310. The system will set the lower threshold here in response to the user selecting the confirm button. Figure 19 As shown, screen 1900 indicates that upper threshold 1504 has been set and is color-coordinated with the lower limit of current amplitude (e.g., shown as the same color). Lower threshold 1904 has been set and is color-coordinated with the upper limit of current amplitude (e.g., shown as the same color, but different from the upper / lower threshold colors). In addition to the color, upper threshold 1504 and the lower limit have similar directional arrows, while lower threshold 1904 and the upper limit have similar directional arrows. In this way, the system can automatically adjust the current amplitude between the lower and upper limits to maintain the LFP signal between the lower and upper thresholds.

[0170] As shown herein, increasing the current amplitude (or other stimulation parameters that increase the stimulation intensity) can reduce the amplitude of the LFP signal at the selected frequency. Conversely, reducing the current amplitude (or other stimulation parameters that reduce the stimulation intensity) can increase the amplitude of the LFP signal at the selected frequency. An LFP below a lower threshold may indicate that the patient is receiving too much stimulation and has movement disorders, while an LFP above an upper threshold may indicate that the patient's symptoms are not being effectively controlled. In some examples, the average power of the selected frequency over 30 seconds is captured as the upper and lower thresholds. In some examples, the processing circuit 310 may employ error checking for the upper and lower thresholds. For example, if the capture would cause the upper threshold to be lower than the lower threshold, the processing circuit 310 may refuse to capture the threshold. Additionally or alternatively, the processing circuit may perform statistical threshold checks to ensure that the thresholds are sufficiently separated from each other.

[0171] like Figure 19 As shown, the system can capture LFPs during stimulation delivery. This is possible because the stimulation electrodes are distinct from the sensing electrodes. One benefit of this ability to capture LFPs while delivering stimulation is that LFP data can be identified when the patient arrives home, allowing the system to monitor LFP thresholds.

[0172] As discussed herein, processing circuitry 310 may obtain brain signals representing electrical activity of a patient's brain; control a medical device (e.g., IMD 106) to deliver electrical stimulation defined by at least a first value of a stimulation parameter; adjust the first value of the stimulation parameter to a second value of the stimulation parameter at which a patient condition is identified; and determine a threshold value for the brain signals associated with the patient condition. IMD 106 may be configured to limit automatic adjustment of the stimulation parameter to a second value associated with the threshold value. The threshold value for the brain signals may be associated with one of an upper threshold value associated with a therapeutic benefit or a lower threshold value for the brain signals associated with a side effect.

[0173] In some examples, the processing circuit 310 may adjust the stimulation parameter to a third value at which a side effect is identified, the third value being different from the second value; and determine a second threshold value for the brain signal associated with the side effect, the second threshold value being associated with the lower threshold value. The medical device may be configured to limit automatic adjustment of the stimulation parameter to between the second value and the third value so that the brain signal remains between the upper threshold value and the lower threshold value. As discussed above, the processing circuit 310 may control the user interface to display the upper threshold value and the lower threshold value on the first coordinate graph and to display the second value and the third value on the second coordinate graph. In some examples, the upper threshold value and the second value are represented by a first color, and the lower threshold value and the third value are represented by a second color that is different from the first color. As Figure 19 As shown, processing circuitry 310 may control the user interface to display the threshold value of the brain signal on a first graph, display the second value of the stimulation parameter on a second graph, display a representation of the electrode through which the electrical stimulation is delivered, and display a stimulation field representing the electrical stimulation relative to the representation of the electrode. In some examples, user selection of clear LFP threshold button 1906 causes processing circuitry 310 to discard the captured upper and lower threshold values.

[0174] Figure 20 An exemplary screen 2000 is shown in which the user interface 400 indicates a prompt 2002 regarding the amplitude of the stimulation. Although the amplitude is within the upper and lower limits, if adaptive DBS is disconnected, the system may indicate that the stimulation may be too high. Upper limit 2006 is the upper limit of the amplitude, and lower limit 2004 is the lower limit of the amplitude.

[0175] Figure 21 is a flow chart illustrating an exemplary technique for setting dual thresholds associated with adaptive DBS therapy that may be performed using the various screens of the user interface 400 described herein. Figure 21In an example of FIG. 1 , processing circuit 310 receives user input requesting to set thresholds for adaptive DBS ( 2102 ). Processing circuit 310 captures an upper threshold for LFP brain signals at the lower limit of the stimulation amplitude that alleviates the patient's symptoms ( 2104 ). Processing circuit 310 then increases the stimulation amplitude based on the user input ( 2106 ). Processing circuit 310 captures a lower threshold for LFP brain signals at the upper limit of the stimulation amplitude that is slightly lower than the patient's side effects ( 2108 ). Processing circuit 310 then stores the thresholds and limits for adaptive DBS ( 2110 ). In some examples, the user can manually adjust these thresholds and limits.

[0176] Figure 22 is a conceptual diagram illustrating an exemplary screen 2200 summarizing parameters selected for adaptive DBS therapy. Figure 22 In the exemplary screen 2200 of FIGURE 2200, setting transitions for moving stimulation up and down and an indication of a captured threshold are provided. Electrode configuration 2202 shows the electrodes used to sense brain signals. Stimulation settings 2204 indicate the amplitude of the upper limit, lower limit, and pause for stimulation treatment. Field 2206 indicates the duration of the transition when moving between the upper and lower limits of the amplitude, and field 2208 indicates whether an LFP threshold has been captured. User selection of the threshold edit button for the corresponding fields 2206 and 2208 will cause the processing circuit 310 to display Figure 23 and Figure 24 The screen shown.

[0177] Figure 23 and Figure 24 is a conceptual diagram illustrating an exemplary screen for manually adjusting one or more thresholds associated with adaptive DBS therapy. Figure 23 In the exemplary screen 2300 of FIG. 4 , arrow buttons 2306, 2308, 2310, and 2312 are provided to receive user input requesting a manual adjustment of one or more of these thresholds, and then adjust the corresponding thresholds. Figure 24 An exemplary screen 2400 is included that instructs the user to decrease the upper threshold by 2 steps and increase the lower threshold by 2 steps. User selection of cancel button 2314 cancels the adjustment of the LFP threshold. User selection of update button 2316 causes programmer 104 to change the LFP threshold as indicated in screen 2400.

[0178] The system can increase or decrease any threshold. In some examples, the adjustment of the threshold is a relative adjustment of one or both thresholds. For example, the amplitude value separating the upper and lower thresholds can be divided into equal steps, so that each increase or decrease in the corresponding threshold causes a normalized change in the threshold. In one example, the magnitude between the thresholds is divided into 100 steps (or some other predetermined number of steps), and each press of the up or down button increases or decreases the threshold by one step. In other examples, each press of the button can change the threshold by a certain percentage or other relative value for the thresholds.

[0179] Figures 25 to 30 is a conceptual diagram illustrating an exemplary screen for displaying sensed brain signals along with one or more stimulation parameters defining the delivered DBS therapy. Figure 25 Screen 2500 is shown with a selectable "Start Streaming" button 2510 enabling the user to start streaming near real-time brain information (such as LFP power) and stimulation amplitude simultaneously. The processing circuit 310 can be configured to display the streamed LFP information and / or store the streamed LFP information to memory. Screen 2500 also includes a hemisphere selection 2502, an adaptive therapy toggle key 2504 for turning adaptive therapy on or off, and a menu 2504 indicating that the type of settings screen is current. The adaptive state 2506 indicates what type of stimulation is being delivered. The parameter field 2508 indicates the selected amplitude limit, but adaptive stimulation must be paused before manual parameter value adjustment can be made.

[0180] Once the start streaming button 2510 is selected, the processing circuit 310 begins streaming the LFP power information for display in the user interface 400. Figure 26 As shown, screen 2600 of user interface 400 includes two graphs 2602 and 2604. Each graph displays LFP power values ​​relative to current amplitude values, which are used to deliver stimulation while obtaining LFP power. The lower graph 2604 may include all data streamed since the start of streaming. The upper graph 2602 may include data streamed over a shorter time period. Box 2606 indicates from the lower graph 2604 the time period during which the upper graph 2602 displays LFP data. In this way, the lower graph 2604 may cover a larger time period than the upper graph 2602, wherein the lower graph 2604 includes the information presented in the upper graph 2602. In this way, each graph provides a different time range for the information displayed. Figure 27Screen 2700 is shown in which graphs 2602 and 2604 change over time as more data is captured, with upper graph 2602 remaining for a certain period of time and lower graph time periods increasing as more data is streamed in. As shown, as more time of LFP data is added to lower graph 2604, the size of box 2606 decreases.

[0181] Graphs 2602 and 2604 will display any observed changes to LFP power and current amplitude. In addition, each graph may include upper and lower thresholds associated with the LFP power data and upper and lower limits associated with the current amplitude. Thus, Figure 26 The streaming shown enables the user to see how changes to the current amplitude affect the LFP power at the frequency selected for the sensing electrode configuration. In some examples, the processing circuit 310 can automatically calculate the vertical height of the streamed data plot based on the threshold and limit values. In order to sense the LFP power while the stimulation is being delivered, the processing circuit 310 can blank the sensing channel during the time when the stimulation signal is being delivered to the patient. Although the user interface 400 can prevent the user from Figure 26 Screen 2600 of FIG2600 can be used to manually adjust stimulation parameters or thresholds, but other examples may provide such capabilities to manually change one or more thresholds or parameter limits while sensing data in real time. In this way, the clinician can monitor direct changes in LFP power (or another type of brain signal) caused by electrical stimulation as well as any changes to the electrical stimulation. For example, if Figure 28 As shown, screen 2800 provides input buttons (within stimulation field 2508) that enable the user to change the current amplitude while streaming LFP power data and stimulation parameter values. Figure 29 An exemplary screen 2900 is shown in which adaptive therapy has been paused, as indicated by the adaptive therapy toggle 2504, but a manual limit for current amplitude has been set (3.3 mA).

[0182] Figures 25 to 29 An exemplary screen for adaptive stimulation is shown. However, the user can switch to passive stimulation, such as Figure 30 The screen 3000 is shown. Figure 30 In screen 3000, LFP power and stimulation amplitude are still displayed. The user can also adjust the stimulation amplitude to see how those adjustments affect LFP power. Figure 30 As shown, selection of the patient limit button will cause the processing circuit 310 to present a screen from which the user can adjust the upper or lower limits for the current amplitude. The vertical height of each graph can be calculated based on these thresholds and limits.

[0183] like Figures 25 to 30As shown, user interface 400 provides real-time streaming of LFP data on programmer 104. Once the signal / configuration has been configured, the system can stream the signal in the clinic while programming is in progress in order to understand the real-time response of the signal to changes in stimulation (stim). In this way, short-term and long-term trends of the selected signal can be displayed, which can be included together with adjustments to the stimulation amplitude, one or more stimulation parameter values ​​(e.g., amplitude, frequency, and pulse rate). Programmer 104 can store the real-time data offline in memory for later analysis and / or review by the user.

[0184] In some examples, the user interface 400 may include an input mechanism for receiving user input indicating events or other annotations related to the streaming of data and the patient's stimulation time. In some examples, the user interface 400 may receive input to adjust the time scale of the presented data and / or compare data from different time periods. In other examples, the user interface 400 may present real-time power spectrum data, multiple signals of interest, or real-time analysis. The user interface 400 may present, for example, information related to the relative suppression of the LFP signal compared to a baseline.

[0185] Figures 25 to 30 Streaming of LFP data from one electrode combination used for sensing is shown. In other examples, the processing circuit 310 may store brain signal information (e.g., LFP power) from multiple different electrode combinations. The processing circuit 310 may then present the stored brain signal information from different electrode combinations together on the same screen to enable the user to identify which electrode combination provides the user's desired brain signal sensing.

[0186] Figure 31 is an illustration of an exemplary technique for displaying sensed brain signals along with one or more stimulation parameters defining the delivered DBS therapy (e.g., Figures 25 to 30 As shown in the flowchart. Figure 31 As shown in the example of FIG, processing circuit 310 can obtain brain signals representing electrical activity of a patient's brain (3102). Processing circuit 310 then obtains one or more values ​​of stimulation parameters that at least partially define electrical stimulation that can be delivered to a portion of the patient's brain (3104). The processing circuit then outputs a graph for display by user interface 400, the graph including a first trace of the brain signals over a period of time and a second trace of the one or more values ​​of the stimulation parameters over the period of time (3106). The presentation of this information can be in real time.

[0187] Figure 32 and Figure 33 : is a conceptual diagram showing an exemplary screen for adjusting the transition between the stimulation parameter upper limit and the stimulation parameter lower limit. Figure 32 and Figure 33 As shown, user interface 400 provides screens 3200 and 3300 that enable a user to test aDBS transitions and adjust how the transitions occur. Transition curve 3202 indicates the currently set transition time. Parameter field 3216 provides amplitude limits, current values, and adjustment inputs. Upward transition adjustment 3204 indicates the duration of the current rise, which can be adjusted by moving slider 3212. Downward transition adjustment 3208 indicates the duration of the current fall, which can be adjusted by moving slider 3214. Using this transition test, a user can assess whether there is an increased likelihood of side effects due to a rapid transition from stimulation on to off or from stimulation off to on. For example, up transition test button 3206 or down transition test button 3210 can be selected to initiate stimulation for an adaptive therapy transition in the corresponding direction for all or part of the therapy window. Processing circuitry 310 can send a complete command to IMD 106 to execute a full up or down transition to avoid communication delays at each step during the transition. In this way, IMD 106 will perform a test transition as this test transition will be done automatically by IMD 106 during adaptive DBS.

[0188] Each ramp-up and ramp-down on the top graph and / or sliders 3212 and 3214 on the lower timeline can be selected by the user to drag the ramp to a shorter or longer duration. In one example, processing circuitry 310 can initiate a ramp-up or ramp-down from any starting amplitude. However, in other examples, processing circuitry 310 may need to start at a lower amplitude and ramp up completely before ramping down completely. Selection of cancel button 3220 cancels any changes to the transition duration. Selection of update button 3222 confirms any changes to the transition duration.

[0189] Figure 34 is a conceptual diagram illustrating an exemplary home screen 3402 of a user interface 400 for navigating to view stored patient event data, which may be similar to screen 402. When a user selects an event button 3404 on menu screen 3402, user interface 400 expands the event button and displays a confirmation button 3406, which the user must select before processing circuitry 310 moves to Figures 35 to 42 The event set for the screen shown.

[0190] Figures 35 to 42 is a conceptual diagram illustrating an exemplary screen for displaying patient event data arranged by user-selectable time. Figures 35 to 39 Example screens are shown that show the number of events of each type that occurred during one or more time periods. Figure 35An exemplary screen 3500 is shown, in which four different events are displayed in table 3508 for two different time periods (e.g., corresponding weeks). Exemplary events include "medication taken," "fall," "dyskinesia," and "on time." These events can be patient events indicated by the patient at the time of their occurrence, such as medication taken, falls, dyskinesia events, and "on time." "On time" can be the number of times a patient feels well and has had symptoms reduced or eliminated. The timing and number of each event can help clinicians assess the efficacy of stimulation therapy for the patient. Menu 3502 indicates which type of information is being displayed, indicating the summary displayed in screen 3500. View selection 3504 indicates the time range of each column of data (e.g., day, week, month, hour, etc.). Range selector 3506 indicates which data will be used to populate table 3508. Event selector 3510 can be selected, allowing the user to select which type of event is displayed in table 3508. The user can read all events by selecting button 3512 or close screen 3500 by selecting close button 3514.

[0191] Figure 36 Screen 3600 is shown including a drop-down menu of view selector 3504 from which a user can select different time periods for parseable events. Figure 37 Screen 3700 is shown including a drop-down menu of range selectors 3506 from which a user can select which data to use in the chart. Figure 38 An exemplary screen 3800 is included in which events for each day are shown in table 3808 . Figure 39 An exemplary screen 3900 is included in which events since the last session with the clinician are shown in a table 3908 .

[0192] Figure 40 An exemplary screen 4000 is shown that displays the LFP classification determined by the processing circuit 310 in a chart 4008. The processing circuit 310 can classify brain states within user-selectable ranges and bins based on the measured thresholds. For example, Figure 40 Graph 4008 includes a breakdown of the amount of time the LFP amplitude was above an upper threshold, the amount of time the LFP amplitude was below a lower threshold, and the amount of time the LFP amplitude was between the upper and lower thresholds. This amount of time is shown as a percentage of time, but can also be displayed in minutes, hours, or other absolute measures of time. Using these indicators, the clinician can see how effective the stimulation was in keeping the LFP amplitude between the upper and lower thresholds. This can be an objective measure of the efficacy of adaptive DBS.

[0193] also, Figure 40Graph 4008 shows the average amplitude of stimulation parameters during stimulation and the adaptive amplitude reduction scale to illustrate how adaptive therapy affects the amount of stimulation received by the patient. While adaptive therapy is running, processing circuitry 310 may calculate and display the average amplitude reduction between the adaptive amplitude and the default amplitude value for continuous stimulation. A higher percentage indicates that adaptive DBS is reducing the amount of stimulation delivered and, therefore, reducing power consumption of the battery of IMD 106. Graph 4008 may also include the amount of time that adaptive DBS was running during the time period indicated in the graph.

[0194] In some examples, Figure 40 Graph 4008 may flag incomplete or otherwise poorly written data or indicate trends in treatment or sensing over different time periods. Figure 41 Screen 4100 is shown including two different weeks and corresponding LFP classifications in an exemplary graph 4108 .

[0195] Figure 42 Screen 4200 is presented, in which the user can specify which patient events can be indicated by the patient and whether LFP data should be captured in response to the user indicating that a patient event has occurred. For example, screen 4200 can be accessed by selecting Configure Event Selector 3510 from screen 4100. The user can select the appropriate box in boxes 4202 to select which one or more of events 4202 are included in the displayed data. For each of these events, LFP Capture 4206 indicates whether an LFP was captured for that event or whether a stimulation cycle 4208 was used for that event. Selecting Cancel button 4210 does not save any changes to the patient events, but selecting Update button 4212 causes programmer 104 to change the way patient events are displayed as selected. In some examples, the language of the patient programmer user interface may be different from the language of the physician programmer. A medical translator can enter events, group names, or other information for the patient programmer in the patient's language, while the clinician programmer can maintain the language used by the clinician.

[0196] User interface 400 can present information related to patient events in many different ways. As described herein, once the sensing circuit combination has been configured and used for sensing, the system allows the patient or other user to mark the event either concurrently or after the event occurs. Programmer 104 can control IMD 106 to capture the signature of the sensed brain signals after the event (and before the event by using a sensing buffer that temporarily stores brain signals). Programmer 104 can control user interface 400 to present one event along with other similar or different events. In this way, user interface 400 can help the user understand the real-world response of brain states to medications, stimulation, and other daily activities to inform future treatment management, which may include available stimulation parameter values ​​and / or improvements to stimulation closed-loop control. Figures 42 to 47 An exemplary screen of a user interface 400 that may provide this information is included in FIG.

[0197] The user interface 400 may provide various structures and functions for presenting patient events. For example, the user interface 400 may accept input for naming different event types, selection of one or more actions (e.g., recording data and / or stimulation adjustment) that should occur in response to detection of a particular patient event or event type, a request for a comparative view of multiple events or event types, an input requesting analysis of data such as event frequency, number of events, or event severity, or any other type of input. In addition, the user interface 400 may enable a user to filter (e.g., add or remove) events, event types, time periods, or other information to customize the view of the stored information.

[0198] In some examples, programmer 104 may perform statistical analysis on various data within or between events. For example, programmer 104 may determine the average peak frequency of different events or event types, the average peak magnitude of different events or event types, the correlation of events with different LFP data, etc. Programmer 104 may also cluster events together based on the similarity of one or more characteristics of the sensed brain signals sensed during the event. For example, programmer 104 may cluster events that have peaks at similar frequencies in the beta band and that occur at similar times of the day (e.g., on weekday mornings) or have other similarities such as similar accelerometer data. Programmer 104 may then control user interface 400 to present these statistical conclusions, clustered events, etc.

[0199] Figures 43 to 47is a conceptual diagram illustrating an exemplary screen for displaying a brain signal coordinate graph for corresponding patient events. In response to a user providing input indicating the occurrence of a patient event, the IMD 106 may obtain brain signal information (e.g., spectral information of the brain signals). The IMD 106 may capture beta and / or gamma band data for each event. A clinician may then determine which frequency bands or frequencies are good biomarkers for the type of event that occurred based on the captured brain signal information for the event. This functionality may also be beneficial to patients because medications can take a long time to wear off and may not occur during an office visit.

[0200] In response to a user pressing a button on the patient programmer or clinician programmer, the programmer may control the IMD 106 to capture LFP information within a certain time period (e.g., 25 seconds). The LFP information may be sensed after the event has been indicated. However, in other examples, the IMD 106 may maintain a rolling buffer and capture LFP information before, during, and after the event is indicated to occur. In other examples, when LFP data is stored for a longer period of time, the user may be able to go back and mark an event that occurred hours or days ago, and the system may capture LFP information recorded at the time of the indicated event. The captured LFP information may include time domain information and / or an FFT transform of the recorded LFP data. In some examples, the processing circuit 310 may select a certain number of power values ​​across the frequency domain, such as 100 power values. However, in other examples, more or less data may be stored for each sample of the LFP information. The LFP data may be stored on the patient programmer or IMD 106. In other examples, the LFP information may be transmitted to the cloud or other device for storage. In some examples, LFP information can be transmitted directly to a clinician.

[0201] Figure 43 Screen 4300 is shown showing patient events and corresponding LFP information displayed on a graph 4306 of LFP power versus frequency. Trace 4312 is the LFP power for each event shown in event list 4314. A hemisphere selector 4302 may be selected to switch between signals sensed from different leads, and a range selector 4304 may be selected to switch between different dates of sensed data. Although in this example (from Figure 42 ) are shown as selectable, but in other examples fewer or more types of events may be indicated by the user. Figure 43Screen 4300 provides a slider 4310 that the user can move to adjust the frequency bar 4308 and identify the frequency and / or power of any portion of each trace. On the right side of screen 4300, an event list 4314 is provided for each event. In response to the user deselecting an event (e.g., by unchecking the corresponding checkbox), user interface 400 removes the particular trace for that event from graph 4306. In this way, the user can choose to evaluate any event and compare any event. In other examples, other types of information for each event can be captured, such as medication status, accelerometer data, stimulation delivery status, etc. Each of these types of information can be presented on the same graph or different graphs for each type of information. Selection of close button 4318 closes screen 4300.

[0202] Figure 44 Shown is a pop-up window 4400 displayed in response to selection of the filter button 4316 in screen 4300. In pop-up window 4400, the user can select the event types to be displayed on the screen. Types of events 4404 are shown and can be selected or deselected via corresponding checkboxes 4402. Selection of the cancel button 4210 will cancel these changes and selection of the update button 4212 will change the event types shown in the next screen. Figure 45 Includes screen 4500 indicating that the user Figure 44 4400 and the corresponding LFP trace 4504 in the coordinate graph 4502. Figure 46 An exemplary screen 4600 is shown in which a dyskinesia event is identified and a corresponding trace 4604 is shown in a graph 4602. In some examples, programmer 104 may automatically place frequency bar 4308 at the frequency peak, but the user can always move slider 4310 to the peak on trace 4604. Figure 47 An exemplary screen 4700 is shown in which fall events (eg, all events within the fall event type) are identified and corresponding LFP data is shown as traces 4704 in a graph 4702 .

[0203] Figure 48 is an illustration of an exemplary technique for generating and displaying brain signal coordinate maps corresponding to patient events (such as Figures 42 to 47 Flowchart of the screen). Figure 48In the example of , processing circuit 310 receives an indication of an event at a certain time (4802), and in response to receiving the indication of the event, stores spectral information of brain signals recorded at the time (4804). In some examples, the stored spectral information may have been obtained only after the indication of the event was received. In other examples, processing circuit 310 may retrieve spectral information obtained before the event from a buffer in memory. Processing circuit 310 then outputs a coordinate graph for display in the user interface, the coordinate graph indicating the spectral information of the brain signals recorded at the time (4806). Processing circuit 310 may then control user interface 400 to adjust the displayed events and corresponding traces or other information in response to user requests.

[0204] Figure 49 4900 is a conceptual diagram illustrating an exemplary screen for displaying the amount of time a brain signal characteristic is within a corresponding brain signal value range. Figure 49 As shown, screen 4900 shows a bar graph 4904 of the amount of time that a brain signal (e.g., LFP power) is above an upper threshold, below a lower threshold, and between the upper and lower thresholds. This information can be viewed over different time periods (such as by day, week, or month). A time period selection can be made via a time selection 4908 (which can be a drop-down menu). A data selector 4902 enables the user to select the type of data, such as the type of stimulation delivered or the stored data set. Arrows 4906 can be selected to move to different days or view data for other time periods that do not fit within the graph.

[0205] Figures 50 to 55 is a conceptual diagram illustrating an exemplary screen for displaying a graph of brain signal characteristics and stimulation parameter values ​​from DBS treatment over time. This information can be stored over time and is similar to an electronic exercise diary. The stored information may include brain signal information (e.g., LFP power), stimulation parameter values, patient events, and / or system events. This type of information may allow a clinician to review brain signal information collected outside of a clinical setting and stored over time.

[0206] Once the sensing electrode combinations have been configured, the system can continuously record the sensed signals (e.g., recorded in the memory of IMD 106 and / or until unloaded to programmer 104 or another device). Programmer 104 then controls user interface 400 to display the data for review, for example, during a clinical visit or follow-up visit. The goal of presenting this data can be to help the user understand the real-world response of brain states to medications, stimulation, and other daily activities to inform future treatment management. In some examples, the display can show trends in the stored LFP signals, trends in stimulation parameter values ​​(such as amplitude), any events sensed or marked by the patient during that time, one or more stimulation parameter values ​​used to deliver stimulation during that time, one or more hemispheres (e.g., one or two leads), LFP thresholds, stimulation limits, or any other information related to the stored data.

[0207] In some examples, user interface 400 may enable a user to reduce or increase the time period of data displayed (e.g., changing from showing minutes, hours, days, weeks, or months). In some examples, programmer 104 may control user interface 400 to identify days with similar events or stored data, group days or other time periods together, or determine statistical metrics. Exemplary statistical metrics may include an average day, an average night, trends observed before and / or after an event, trends observed before and / or after a change in stimulation parameter values, or comparisons between different stimulation programs.

[0208] exist Figure 50 In the exemplary screen 5000 of FIGURE 5, LFP power over time is shown as a graph trace 5006, while a trace 5016 of current amplitude for one lead in one hemisphere of the patient is shown over the same time period. While the upper limit 5020 and lower limit 5018 for stimulation parameters are shown in the graph, in other examples, no limits or thresholds may be presented. An upper threshold and / or a lower threshold for the LFP data may also be shown. Figure 50 Screen 5000 in also indicates identified patient events 5012 (e.g., events marked by the patient) and system events 5014 (e.g., parameter value changes) and displays these events at the time they were identified. Patient events 5012 and system events 5014 can be identified using different colors. User selection of a patient event 5012 or system event 5014 can open a window that includes additional information related to the event, such as more specific LFP data or what parameter value changes were made. Using this timeline, the clinician can view historical brain signal information, stimulation information, and event information on the same coordinate graph. The timeline 5004 above the coordinate graph indicates the day of the month. Thus, Figure 50A graph of the time period 5002 can present an entire month's worth of data on one screen. In other examples, the timeline can be reduced to weeks or days or expanded to multiple months or years. A time selector 5002 can be selected to select a different time period for displaying the data. Each LFP and stimulation data point can be sampled at a certain rate (such as six times per hour). However, higher or lower sampling rates can be used, depending on the data storage capacity and the type of graph to be presented.

[0209] Figure 51 Included is a screen 5100 indicating that selection of a patient event causes the processing circuit 310 to present a snapshot 5102 of LFP spectrum information stored at the same time as the patient event. The clinician can then identify whether any abnormalities occurred during the event or identify certain frequencies of brain signals that can be used to prevent or encourage future patient events. The "on time" indicator for the patient event indicates that the patient felt well at that time.

[0210] Figure 52 Screen 5200 is shown with system events marked in the data, including changes to stimulation parameters. System events 5202 and 5204 show stopping and starting stimulation. Figure 52 As can be seen in FIG, stimulation is turned on in response to detecting that the LFP power exceeds the upper threshold. Patient event 5206 is also shown in the coordinate graph. Figure 53 As shown in screen 5300 of , the user can click on any of system events 5202 or 5204 to expand the event, thereby showing what event occurred. As shown in window 5302, the system event is the disconnection of stimulation at the time of the specific day listed. Figure 54 Screen 5400 is shown where a patient event 5404 is flagged when the LFP power falls below a lower threshold (possibly due to a side effect of stimulation). Flag identifiers 5402 indicate which days of the month have recorded events and which type of event (patient event or system event) is recorded via color coding. Figure 55 Screen 5500 is shown, showing the LFP power and stimulation parameter values ​​for both hemispheres of the brain. The stimulation parameters can be the same or different for each hemisphere. While brain signals generally move together, diverging signals from separate hemispheres can indicate another problem with the patient. Patient event 5506 is also shown.

[0211] like Figure 55As shown, the coordinate graph can present a full day's worth of objective LFP information and related stimulation parameter data on the same screen. In addition, the same screen can show stimulation changes and patient-reported events such as feeling well, feeling side effects, taking medication, etc. In some examples, all data is stored on the programmer, so no network connection is required to present this information. However, in other examples, the programmer can send the data to the clinician's digital health platform for viewing there. In some examples, Figures 50 to 55 The screen allows the user to filter events by event type, LFP power range, stimulus event, threshold crossing, etc.

[0212] Figure 56 is a flow chart illustrating an exemplary technique for generating and displaying graphs of brain signal characteristics and stimulation parameter values ​​from DBS therapy over time. Figure 56 The process can correspond to relative to and about Figures 50 to 55 User interface 400 is described. Figure 56 is a flow chart illustrating an exemplary technique for displaying sensed brain signals along with one or more stimulation parameters defining delivered DBS therapy based on historical data. Figure 56 As shown, processing circuitry 310 may obtain brain signals representing electrical activity of the patient's brain over a period of time (5602). Processing circuitry 310 may then obtain stimulation parameter information that at least partially defines electrical stimulation that may be delivered to a portion of the patient's brain over the period of time (5604). Processing circuitry 310 may then output a graph for display by user interface 400, the graph including a first trace of the brain signals over the period of time and a second trace of the one or more values ​​of the stimulation parameter information over the period of time (5606).

[0213] Figure 57 5700 is a conceptual diagram illustrating an exemplary screen for displaying the amount of time for delivering different types of DBS treatments for corresponding days. Figure 57 As shown, user interface 400 can display device usage for each type of stimulation program (such as adaptive stimulation or speech) in a bar graph 5702. This information can be viewed by different time periods (such as days, weeks, or months) that can be selected via time selector 5706. Legend symbol 5704 indicates the type of therapy used as shown in bar graph 5702.

[0214] Figure 58 and Figure 59 are conceptual diagrams illustrating exemplary screens 5800 and 5900 for displaying graphs of brain signal power for corresponding electrode combinations of leads. Figure 58The graph of screen 5800 may include LFP information 5808 (e.g., traces) recorded for each available electrode combination (channel). Typically, the best electrode combinations are those that have peaks at certain frequencies as shown in the LFP power versus frequency graph. This screen 5800 enables the user to select a different sensing channel 5802 to highlight the corresponding trace for that channel within the group of all traces for all channels. In screen 5800, the user has selected sensing channel 5804, and lead 5812 shows the electrodes for the leads for that particular sensing channel. LFP information 5808 shows all traces for sensing channel 5802. Traces 5810 may be highlighted (e.g., using a thicker line, a dashed line, a different color, etc.) and indicate the LFP data saved for the selected sensing channel 5804. The user may choose to refresh brain sensing survey 5804 so that programmer 104 initiates new sensing of LFP information for all sensing channels 5802. Figure 59 Included is screen 5900 showing that the user has selected sensing channel 5904 (e.g., electrodes "0 to 2"), which corresponds to trace 5910 having the highest peak in the beta band for all LFP information 5808. Leads 5812 provide a visual indication of the electrodes used for sensing channel 5904.

[0215] As discussed herein, programmer 104 may initiate an automatic scan of brain signals from all or most available sensing channels to enable programmer 104 or the user to identify where the signals may be located (which hemisphere of the brain, which area of ​​the leads, which specific combinations of contacts) for the purpose of understanding such signals, the integrity or quality of the recording system, and then guiding sensing configuration and / or stimulation parameter values. Figure 58 Screen 5800 of FIG. 58 shows a list of specific contacts to be scanned, and programmer 104 can use the limited sensing resources of IMD 106 to capture all signals "nearly" simultaneously so that they can be directly compared on a relative scale. Once LFP data is captured during a scan, programmer 104 can calculate the power spectrum of each sensing channel and control user interface 400 to create an interactive display of the LFP data.

[0216] In this way, user interface 400 can provide a view of all signals in the hemisphere simultaneously and enable selection of one signal to be compared with other signals. Programmer 104 can measure various aspects of the signal (e.g., the difference between the maximum and / or minimum values ​​at a particular frequency of interest). Programmer 104 can enable IMD 106 to continuously record a subset of the signals. In some examples, programmer 104 can perform statistical comparisons (e.g., the energy in a frequency region compared to the energy at a particular peak, the relative amplitude above 1 / frequency of the curve, the width of a peak, or simultaneous comparison or measurement of two or more peaks). In some examples, user interface 400 can provide additional views of leads (e.g., directional leads) having electrodes at different locations around the perimeter of the lead. User interface 400 can also provide visualization of anatomical structures or other references in combination with signal location (e.g., whether the signal is inside or outside the target, or whether the signal is inside or outside the anatomical structure).

[0217] Figures 60 to 69 is a conceptual diagram illustrating exemplary screens of a user interface of a patient programmer associated with entering an MRI mode of a medical device. Figure 60 Screen 6002 is shown including a navigation menu 6004 from which the user can enter "MRI Mode" by selecting MRI Mode button 6006. This mode is used to check the MRI eligibility of the IMD 106 implanted in the patient and enables the patient to enter MRI mode directly using the patient programmer if qualified. Figure 60 When the "MRI Mode" button 6006 is pressed, the user interface appears Figure 61 , where screen 6100 prompts the user to proceed into MRI mode using continue button 6102. Home button 6104 may be selected to exit the MRI mode process. Figure 62 Screen 6200 is included to prompt the user to select a device to be examined. Button 6202 indicates a device located in the body (such as the left chest), and button 6204 indicates a device located in the head. Back button 6206 takes the user back to the previous screen 6100, and Continue button 6208 moves to the next screen in the process. Figure 63 The screen 6300 of FIGURE 6301 enables the user to disconnect treatment from the MRI qualification check directly via the treatment disconnect button 6302 without having to navigate to different screens. If the user chooses to disconnect treatment, the user interface Figure 64 In screen 6400 of FIG. 6402 , the user is prompted to confirm that treatment should be disconnected. For example, pop-up window 6402 includes a treatment disconnect button 6404 that must be selected to disconnect treatment. Selection of cancel button 6406 returns to the previous screen and treatment remains on.

[0218] Figure 65Includes screen 6500 where the user is prompted to also put any other devices into MRI mode. When the Continue button 6502 is selected, the Figure 66 6600 and prompts the user to begin the MRI qualification check by selecting the Start Test button 6602. Selecting the Back button 6604 returns to the previous screen. In response to receiving the selection of the Start Test button 6602, the user interface moves to Figure 67 6700 in the MRI Qualification Test, which indicates the status of the MRI Qualification Test via a status bar 6702 (e.g., showing a percentage of the process). From this screen, the user can choose to stop the test if desired via a stop test button 6704. If the test is successful, then Figure 68 Indicates that the programmer has placed the one or more neurostimulators in MRI mode. In the pop-up window 6802 of screen 6800, the user can select the OK button 6904 to continue in MRI mode. Once in MRI mode, Figure 69 Screen 6900 of FIG. 6901 indicates that the user interface will present button 6904, which, when pressed, will cause the programmer to control the implanted device to leave MRI mode. Button 6902 can switch between different devices in different locations in the patient.

[0219] Figures 70 to 75 is a conceptual diagram illustrating an exemplary screen of a user interface associated with entering an MRI mode of a medical device. Figures 70 to 75 In an example, a clinician programmer can enter the MRI mode of the stimulation device. Figure 70 Screen 7002 is shown where the clinician can confirm the system components and any other eligibility factors for MRI eligibility. Stimulation toggle key 7004 enables the user to turn stimulation on or off. Menu 7014 provides different screens where information related to the device can be viewed. Component button 7006 can show the user additional components associated with the patient, and button 7008 can show additional factors related to MRI eligibility. Cancel button 7010 will cancel that portion of the MRI exam. Selection of confirm button 7012 will confirm that the MRI test can proceed. Figure 71 Screen 7100 is shown showing the system qualifications for each component of the system. Figure 72 The screen 7200 is configured to receive user input to turn off or on stimulation for MRI imaging. Figure 72 An enter MRI mode button 7204 is provided which, when selected, causes the programmer to place the IMD in MRI mode. A report button 7202 will cause user interface 400 to present a report regarding MRI eligibility for the patient. Figure 73Included is screen 7300 which indicates a pop-up screen 7302 where the user can confirm that the system should enter a treatment mode eligible for an MRI scan by selecting an OK button 7306. A Cancel button 7304 will cancel the MRI setup. Figure 74 Screen 7400 is provided indicating that the IMD is in MRI mode. Report button 7402 will cause user interface 400 to present a report related to MRI mode to the patient. Programmer 106 will control the IMD to exit MRI mode in response to the user selecting Exit MRI Mode button 7404.

[0220] Figure 75 is a flow chart illustrating an exemplary technique for managing the sensing of brain signals. Figure 75 As shown in the exemplary flow chart of FIGURE 1, LFP power can be recorded and presented to the user to adjust the settings of the treatment that is not automatically adjusted. For example, the processing circuit 310 of the programmer 104 can determine the sensing electrode configuration based on the monopolar review of the electrode combination (7502). The processing circuit 310 then determines the therapeutic window for stimulation (7504). This process can be automated or performed using input from the user. The processing circuit 310 then analyzes the LFP energy sensed on the different sensing channels (7506).

[0221] Based on the LFP energy, the processing circuit 310 determines the values ​​of the stimulation parameters and / or other feedback, such as feedback from the patient or clinician (7508). The processing circuit 310 then controls the IMD 106 to deliver the therapy using these stimulation parameter values ​​(7510). If there is no patient or clinician feedback (the "no" branch of box 7512), the processing circuit 310 continues to analyze the LFP energy and adjusts the stimulation parameter values ​​as needed to adapt the stimulation to the changing brain state (7506). This automated process involving the LFP signal implements adaptive stimulation for the patient. If the processing circuit 310 determines that there is patient or clinician feedback (the "yes" branch of box 7512), the processing circuit 310 analyzes the feedback to make any adjustments to one or more stimulation parameters (7514). For example, feedback indicating that the patient experiences movement disorders at some time may cause the processing circuit 310 to reduce the upper limit of the stimulation amplitude.

[0222] Figure 76 is a flow chart illustrating an exemplary technique for setting up and managing adaptive stimulation using brain signals. Figure 76As shown in the exemplary flow chart of , the IMD can use LFP power to automatically adjust one or more stimulation parameters to maintain the LFP power at an appropriate level relative to one or more thresholds. For example, the processing circuit 310 of the programmer 104 can determine the sensing electrode configuration based on a monopolar review of the electrode combination (7602). The processing circuit 310 then determines the therapeutic window for stimulation (7604). This process can be automated or performed using input from the user. The processing circuit 310 then analyzes the LFP energy sensed on the different sensing channels (7606).

[0223] Based on the LFP energy, the processing circuit 310 determines the values ​​of the stimulation parameters and / or other feedback, such as feedback from the patient or clinician (7608). The processing circuit 310 then controls the IMD 106 to deliver the treatment using these stimulation parameter values ​​(7610). If the clinician does not make adjustments or no other clinician intervenes during the office visit (the "no" branch of box 7612), the processing circuit 310 continues to analyze the LFP energy and adjusts the stimulation parameter values ​​as needed to adapt the stimulation to the changing brain state (7606). This automated process involving the LFP signal implements adaptive stimulation for the patient. If the processing circuit 310 determines that there are clinician adjustments (the "yes" branch of box 7612), the processing circuit 310 analyzes the feedback to make any adjustments to one or more stimulation parameters (7614). For example, the clinician can review the data and request adjustments to the LFP threshold and / or stimulation limits.

[0224] The following embodiments are described herein. Embodiment 1. A method, comprising: obtaining, by a processing circuit, brain signal information for at least one electrode combination among a plurality of electrode combinations of one or more electrical leads; determining, by the processing circuit, a corresponding frequency for the at least one electrode combination based on the brain signal information; outputting a plurality of selectable lead icons for display, wherein each of the plurality of selectable lead icons represents a different electrode combination among the plurality of electrode combinations; outputting, for display, the corresponding frequency determined for the at least one electrode combination in association with the corresponding selectable lead icon associated with the at least one electrode combination; receiving user input selecting one of the plurality of selectable lead icons; and in response to receiving the user input, selecting, by the processing circuit, a sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing.

[0225] Example 2. According to the method described in Example 1, the method also includes: outputting a selectable signal test icon for display; receiving user input selecting the selectable signal test icon; and in response to receiving the user input selecting the selectable signal test icon, controlling the medical device to obtain brain signal information of at least one electrode combination among the multiple electrode combinations.

[0226] Example 3. The method of any one of Examples 1 to 2, wherein the plurality of electrode combinations includes all electrode combinations possible for the one or more electrical leads implanted in the patient.

[0227] Example 4. According to the method described in any one of Examples 1 to 3, the method further includes: analyzing the brain signal information for the presence of an artifact associated with at least one of electrocardiographic sensing or movement of the one or more electrical leads; determining that the artifact does not exist in the brain signal information; and in response to determining that the artifact does not exist, approving the one or more electrode combinations for user selection for subsequent brain signal sensing.

[0228] Example 5. The method of Example 4, wherein analyzing the brain signal information for the presence of the artifact comprises applying a logistic regression classifier to at least a portion of the brain signal information.

[0229] Example 6. According to the method described in Example 5, the method also includes determining multiple signal features from the brain signal information, the multiple signal features including entropy of multiple frequency bands within the brain signal information and multiple time-domain threshold crossing features, wherein applying the logistic regression classifier to the portion of the brain signal information includes applying the logistic regression classifier to the multiple signal features.

[0230] Example 7. A method according to any one of Examples 4 to 6, wherein analyzing the brain signal information for the presence of the artifact associated with the electrocardiogram includes analyzing the fast Fourier transform (FFT) amplitude spacing of the brain signal information at approximately 8 Hz between a first brain signal detected during electrical stimulation delivery and a second brain signal detected during no electrical stimulation delivery; and wherein the FFT amplitude spacing being less than a spacing threshold indicates the absence of the artifact.

[0231] Example 8. A method according to any one of Examples 1 to 7, wherein the brain signal information includes one or more local field potential signals.

[0232] Embodiment 9. The method of any one of embodiments 1 to 8, wherein the processing circuit is comprised by an external programmer configured to control an implantable medical device configured to be coupled to the one or more electrical leads.

[0233] Example 10. An external programmer, comprising: a processing circuit configured to: obtain brain signal information of at least one electrode combination among a plurality of electrode combinations of one or more electrical leads; determine a corresponding frequency for the at least one electrode combination based on the brain signal information; output a plurality of selectable lead icons for display, wherein each of the plurality of selectable lead icons represents a different electrode combination among the plurality of electrode combinations; output the corresponding frequency determined for the at least one electrode combination in association with the corresponding selectable lead icon associated with the at least one electrode combination for display; receive user input selecting one of the plurality of selectable lead icons; and in response to receiving the user input, select a sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing.

[0234] Example 11. An external programmer according to Example 10, wherein the processing circuit is further configured to: output a selectable signal test icon for display; receive user input selecting the selectable signal test icon; and in response to receiving the user input selecting the selectable signal test icon, control the medical device to obtain brain signal information of at least one electrode combination among the multiple electrode combinations.

[0235] Embodiment 12. The external programmer of any one of Embodiments 10 to 11, wherein the plurality of electrode combinations includes all electrode combinations possible for the one or more electrical leads implanted in the patient.

[0236] Example 13. An external programmer according to any one of Examples 10 to 12, wherein the processing circuit is further configured to: analyze the brain signal information for the presence of an artifact associated with at least one of electrocardiographic sensing or movement of the one or more electrical leads; determine that the artifact is not present in the brain signal information; and in response to determining that the artifact is not present, approve the one or more electrode combinations as available for user selection for subsequent brain signal sensing.

[0237] Example 14. The external programmer of Example 13, wherein the processing circuit is configured to analyze the presence of the artifact in the brain signal information by applying at least a logistic regression classifier to at least a portion of the brain signal information.

[0238] Example 15. An external programmer according to Example 14, wherein the processing circuit is further configured to determine a plurality of signal features from the brain signal information, the plurality of signal features comprising entropy of a plurality of frequency bands within the brain signal information and a plurality of time-domain threshold crossing features, wherein the processing circuit is configured to apply the logistic regression classifier to the portion of the brain signal information by at least applying the logistic regression classifier to the plurality of signal features.

[0239] Example 16. An external programmer according to any one of Examples 13 to 15, wherein the processing circuit is configured to analyze the brain signal information for the presence of the artifact associated with the electrocardiogram by at least: analyzing the fast Fourier transform (FFT) amplitude spacing of the brain signal information at approximately 8 Hz between a first brain signal detected during electrical stimulation delivery and a second brain signal detected during no electrical stimulation delivery; and wherein the FFT amplitude spacing being less than a spacing threshold indicates the absence of the artifact.

[0240] Embodiment 17. An external programmer according to any one of embodiments 10 to 16, wherein the brain signal information includes one or more local field potential signals.

[0241] Embodiment 18. The external programmer of any one of Embodiments 1 to 17, wherein the external programmer is configured to control an implantable medical device configured to be coupled to the one or more electrical leads.

[0242] Embodiment 19. An external programmer comprising means for performing the method according to any one of embodiments 1 to 9.

[0243] Example 20. A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to obtain brain signal information of at least one electrode combination among a plurality of electrode combinations of one or more electrical leads; determine a corresponding frequency for the at least one electrode combination based on the brain signal information; output a plurality of selectable lead icons for display, wherein each selectable lead icon among the plurality of selectable lead icons represents a different electrode combination among the plurality of electrode combinations; output the corresponding frequency determined for the at least one electrode combination in association with the corresponding selectable lead icon associated with the at least one electrode combination for display; receive user input selecting one of the plurality of selectable lead icons; and in response to receiving the user input, select a sensing electrode combination associated with the one selectable lead icon selected by the user input for subsequent brain signal sensing.

[0244] Embodiment 21. A method comprising: obtaining, by a processing circuit, a brain signal representing electrical activity of a patient's brain; controlling, by the processing circuit, a medical device to deliver electrical stimulation defined by at least a first value of a stimulation parameter; adjusting, by the processing circuit, the first value of the stimulation parameter to a second value of the stimulation parameter, identifying a patient condition at the second value; and determining, by the processing circuit, a threshold of the brain signal associated with the patient condition, wherein the medical device is configured to limit automatic adjustment of the stimulation parameter to the second value associated with the threshold.

[0245] Embodiment 22. The method of embodiment 21, wherein the threshold of the brain signal is associated with one of an upper threshold associated with a therapeutic benefit or a lower threshold of the brain signal associated with a side effect.

[0246] Example 23. A method according to any one of Examples 21 and 22, wherein the patient condition includes a therapeutic benefit and the threshold includes a first threshold associated with an upper threshold, the method further comprising: adjusting the stimulation parameter to a third value, identifying a side effect at the third value, the third value being different from the second value; and determining a second threshold of the brain signal associated with the side effect, the second threshold being associated with a lower threshold, wherein the medical device is configured to limit automatic adjustment of the stimulation parameter to between the second value and the third value, so that the brain signal remains between the upper threshold and the lower threshold.

[0247] Embodiment 24. The method according to any one of embodiments 21 to 23 further comprises controlling a user interface to: display the upper threshold value and the lower threshold value on a first coordinate graph; and display the second value and the third value on a second coordinate graph.

[0248] Embodiment 25. The method of embodiment 24, wherein the upper threshold and the second value are represented by a first color, and wherein the lower threshold and the third value are represented by a second color different from the first color.

[0249] Example 26. A method according to any one of Examples 21 to 25, wherein adjusting the first value of the stimulation parameter to the second value of the stimulation parameter includes: receiving user input requesting adjustment from the first value to the second value via a user interface; and adjusting the first value to the second value in response to receiving the user input.

[0250] Example 27. A method according to any one of Examples 21 to 26, wherein determining the threshold of the brain signal includes: receiving user input requesting capture of the threshold via a user interface; and identifying the threshold of the brain signal corresponding to the amplitude value of the brain signal obtained when the user input is received.

[0251] Example 28. A method according to any one of Examples 21 to 27, wherein the threshold includes a first threshold, wherein the method further comprises: receiving user input requesting manual adjustment of the first threshold via a user interface; and adjusting the first threshold to a second threshold based on the user input.

[0252] Example 29. A method according to any one of Examples 21 to 28, further comprising controlling a user interface to: display the threshold value of the brain signal on a first coordinate graph; display the second value of the stimulation parameter on a second coordinate graph; display a representation of the electrodes through which the electrical stimulation is delivered; and display a stimulation field representing the electrical stimulation relative to the representation of these electrodes.

[0253] Example 30. A method according to any one of Examples 21 to 29, wherein the brain signal comprises one or more local field potential signals.

[0254] Embodiment 31. The method of any one of Embodiments 21 to 30, wherein an external programmer comprises the processing circuit, the external programmer being configured to control the medical device, the medical device being configured to be coupled to the one or more electrical leads.

[0255] Embodiment 32. An external programmer configured to perform the method according to any one of Embodiments 21 to 31.

[0256] Embodiment 33. An external programmer comprising means for performing the method according to any one of Embodiments 21 to 31.

[0257] Embodiment 34. A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to perform the method of any one of Embodiments 21 to 32.

[0258] Example 41. A method comprising: obtaining, by a processing circuit, a brain signal representing electrical activity of a patient's brain; obtaining, by the processing circuit, one or more values ​​of a stimulation parameter, the stimulation parameter at least partially defining an electrical stimulation that can be delivered to a portion of the patient's brain; and outputting a coordinate graph for display on a user interface, the coordinate graph comprising a first trace of the brain signal over a time period and a second trace of the one or more values ​​of the stimulation parameter over the time period.

[0259] Example 42. A method according to Example 41, wherein the coordinate graph is a first coordinate graph and the time period is a first time period, and wherein the method further comprises: outputting a second coordinate graph for display on the user interface, the second coordinate graph comprising a third trace of the brain signal information within the second time period and a fourth trace of the one or more values ​​of the stimulation parameter within the second time period, wherein the second time period is greater than the first time period, and wherein the second time period includes the first time period.

[0260] Example 43. The method according to any one of Examples 41 and 42, further comprising outputting at least one of the upper threshold value of the brain signal or the lower threshold value of the brain signal on the coordinate graph for display on the user interface.

[0261] Embodiment 44. The method according to any one of embodiments 41 to 43, further comprising outputting at least one of the lower limit of the stimulation parameter or the upper limit of the stimulation parameter on the coordinate graph for display on the user interface.

[0262] Example 45. A method according to any one of Examples 41 to 44, further comprising controlling the medical device to limit the stimulation parameter to between at least one of a lower limit of the stimulation parameter corresponding to the upper threshold value of the brain signal or an upper limit of the stimulation parameter corresponding to the lower threshold value of the brain signal.

[0263] Example 46. A method according to any one of Examples 41 to 45, wherein the first trace of the brain signal within a certain time period and the second trace of the one or more values ​​of the stimulation parameter within the time period include near real-time values ​​for the brain signal and the stimulation parameter.

[0264] Example 47. A method according to any one of Examples 41 to 46, wherein the brain signal includes one or more local field potential signals.

[0265] Embodiment 48. The method of any one of Embodiments 41 to 47, wherein an external programmer comprises the processing circuit, the external programmer being configured to control the medical device, the medical device being configured to be coupled to the one or more electrical leads.

[0266] Embodiment 49. An external programmer configured to perform the method according to any one of embodiments 41 to 48.

[0267] Embodiment 50. An external programmer comprising means for performing the method according to any one of Embodiments 41 to 48.

[0268] Embodiment 51. A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to perform the method of any one of Embodiments 41 to 48.

[0269] Example 61. A method, comprising: obtaining, by a processing circuit, brain signal information representing electrical activity of a patient's brain within a certain time period from a first memory; obtaining, by the processing circuit, stimulation parameter information, the stimulation parameter information including one or more values ​​of stimulation parameters, the stimulation parameters at least partially defining the electrical stimulation delivered to a portion of the patient's brain during the time period; and outputting a coordinate graph for display on a user interface, the coordinate graph including a first tracing line of the brain signal information within the time period and a second tracing line of the one or more values ​​of the stimulation parameters within the time period.

[0270] Example 62. The method according to Example 61 further includes: obtaining one or more patient events corresponding to corresponding user input received during the time period; and outputting one or more corresponding first marks representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding first marks are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph.

[0271] Example 63. The method according to any one of Examples 61 and 62, further comprising: obtaining one or more system-identified events corresponding to corresponding automatically identified events during the time period; and outputting one or more corresponding second marks representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding second marks are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph.

[0272] Example 64. The method according to Example 61 further includes: obtaining one or more patient events corresponding to corresponding user inputs received during the time period; outputting one or more corresponding first marks representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding first marks are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph; obtaining one or more system-recognized events corresponding to corresponding automatically recognized events during the time period; and outputting one or more corresponding second marks representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding second marks are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph.

[0273] Example 65. A method according to any one of Examples 61 to 63, further comprising: receiving user input selecting a mark presented on the coordinate graph; and in response to receiving the user input, displaying a pop-up coordinate graph of the brain signal information corresponding to the time associated with the mark, the pop-up coordinate graph including a spectrum graph of the brain signal information at the time associated with the mark.

[0274] Example 66. A method according to any one of Examples 61 to 65, wherein: the brain signal information includes electrical activities of the first hemisphere of the brain and the second hemisphere of the brain during the time period, the stimulation parameter information includes one or more values ​​of a first stimulation parameter and one or more values ​​of a second stimulation parameter, the first stimulation parameter at least partially defines the electrical stimulation delivered to the first hemisphere of the brain during the time period, and the second stimulation parameter at least partially defines the electrical stimulation delivered to the second hemisphere of the brain during the time period; and the coordinate graph is a first coordinate graph, the first coordinate graph includes the first tracing line of the brain signal information of the electrical activity of the first hemisphere of the brain during the time period and the second tracing line of the one or more values ​​of the first stimulation parameter during the time period, and wherein the method further includes: outputting a second coordinate graph on the same screen as the first coordinate graph for display by the user interface, wherein the second coordinate graph includes a third tracing line of the brain signal information of the electrical activity of the second hemisphere of the brain during the time period and a fourth tracing line of the one or more values ​​of the second stimulation parameter during the time period.

[0275] Example 67. A method according to any one of Examples 61 and 66, wherein the coordinate graph includes: at least one of an upper threshold value or a lower threshold value displayed together with the first trace of the brain signal information; and at least one of a lower limit or an upper limit displayed together with the second trace of the one or more values ​​of the stimulation parameter.

[0276] Example 68. A method according to any one of Examples 61 to 67, wherein the brain signal includes one or more local field potential signals.

[0277] Example 69. The method of any one of Examples 61 to 68, wherein an external programmer comprises the processing circuit, the external programmer being configured to control the medical device, the medical device being configured to be coupled to the one or more electrical leads.

[0278] Embodiment 70. An external programmer, comprising: a first memory; and a processing circuit, the processing circuit being configured to: obtain brain signal information representing electrical activity of a patient's brain over a certain time period from the first memory; obtain stimulation parameter information, the stimulation parameter information comprising one or more values ​​of stimulation parameters, the stimulation parameters at least partially defining the electrical stimulation delivered to a portion of the patient's brain during the time period; and output a coordinate graph for display in a user interface, the coordinate graph comprising a first trace of the brain signal information over the time period and a second trace of the one or more values ​​of the stimulation parameters over the time period.

[0279] Example 71. An external programmer according to Example 70, wherein the processing circuit is further configured to: obtain one or more patient events corresponding to corresponding user inputs received during the time period; and output one or more corresponding first marks representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding first marks are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph.

[0280] Example 72. An external programmer according to any one of Examples 70 and 71, wherein the processing circuit is further configured to: obtain one or more system-identified events corresponding to corresponding automatically identified events during the time period; and output one or more corresponding second markers representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding second markers are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph.

[0281] Example 73. An external programmer according to any one of Examples 70 to 72, wherein the processing circuit is further configured to: obtain one or more patient events corresponding to corresponding user inputs received during the time period; output one or more corresponding first markers representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding first markers are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph; obtain one or more system-recognized events corresponding to corresponding automatically recognized events during the time period; and output one or more corresponding second markers representing the one or more patient events on the coordinate graph for display by the user interface, wherein the one or more corresponding second markers are located at the corresponding time when the corresponding user input is received along the time axis of the coordinate graph.

[0282] Example 74. An external programmer according to any one of Examples 70 to 73, wherein the processing circuit is further configured to: receive user input selecting a mark presented on the coordinate graph; and in response to receiving the user input, control the display to display a pop-up coordinate graph of the brain signal information corresponding to the time associated with the mark, the pop-up coordinate graph including a spectrum of the brain signal information at the time associated with the mark.

[0283] Example 75. An external programmer according to any one of Examples 70 to 74, wherein: the brain signal information includes electrical activities of the first hemisphere of the brain and the second hemisphere of the brain during the time period, the stimulation parameter information includes one or more values ​​of a first stimulation parameter and one or more values ​​of a second stimulation parameter, the first stimulation parameter at least partially defines the electrical stimulation delivered to the first hemisphere of the brain during the time period, and the second stimulation parameter at least partially defines the electrical stimulation delivered to the second hemisphere of the brain during the time period; and the coordinate graph is a first coordinate graph, the first coordinate graph includes the first tracing line of the brain signal information of the electrical activity of the first hemisphere during the time period and the second tracing line of the one or more values ​​of the first stimulation parameter during the time period, and wherein the processing circuit is further configured to: output a second coordinate graph on the same screen as the first coordinate graph for display by the user interface, wherein the second coordinate graph includes a third tracing line of the brain signal information of the electrical activity of the second hemisphere during the time period and a fourth tracing line of the one or more values ​​of the second stimulation parameter during the time period.

[0284] Example 76. An external programmer according to any one of Examples 70 to 75, wherein the coordinate graph includes: at least one of an upper threshold value or a lower threshold value displayed together with the first trace of the brain signal information; and at least one of a lower limit or an upper limit displayed together with the second trace of the one or more values ​​of the stimulation parameter.

[0285] Embodiment 77. An external programmer according to any one of embodiments 70 to 76, wherein the brain signal comprises one or more local field potential signals.

[0286] Embodiment 78. The external programmer of any one of Embodiments 70 to 77, wherein the external programmer is configured to control a medical device configured to be coupled to the one or more electrical leads.

[0287] Embodiment 79. An external programmer comprising means for performing the method according to any one of embodiments 61 to 69.

[0288] Embodiment 80. A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to obtain brain signal information representing electrical activity of a patient's brain over a time period from a first memory; obtain stimulation parameter information, the stimulation parameter information comprising one or more values ​​of a stimulation parameter that at least partially defines the electrical stimulation delivered to a portion of the patient's brain during the time period; and output a coordinate graph for display on a user interface, the coordinate graph comprising a first trace of the brain signal information over the time period and a second trace of the one or more values ​​of the stimulation parameter over the time period.

[0289] Example 81. A method, the method comprising: obtaining, by a processing circuit, brain signal information representing electrical activity of a patient's brain within a certain time period; determining, by the processing circuit, a first amount of time during the time period when the amplitude of the brain signal information is greater than an upper threshold value; determining, by the processing circuit, a second amount of time during the time period when the amplitude of the brain signal information is less than a lower threshold value; determining, by the processing circuit, a third amount of time during the time period when the amplitude of the brain signal information is between the upper threshold value and the lower threshold value; and outputting representations of the first amount of time, the second amount of time, and the third amount of time for display via a user interface.

[0290] Example 82. The method according to Example 81, wherein the amplitude of the brain signal information above the upper threshold indicates ineffective electrical stimulation for treating the patient's symptoms.

[0291] Embodiment 83. The method of any one of Embodiments 81 and 82, wherein the amplitude of the brain signal information below the lower threshold value indicates a side effect caused by the electrical stimulation delivered to the patient.

[0292] Embodiment 84. The method of any one of Embodiments 81 to 83, wherein the representation comprises a table having a corresponding entry for each of the first amount of time, the second amount of time, and the third amount of time.

[0293] Embodiment 85. The method of any one of Embodiments 81 to 84, wherein the representation comprises a coordinate graph showing each of the first amount of time, the second amount of time, and the third amount of time.

[0294] Example 86. A method according to any one of Examples 81 to 85, further comprising outputting as part of the representation at least one of an average amplitude of the stimulation, an amount of time that stimulation is disconnected due to adaptive stimulation being delivered to the patient, or an amount of time that adaptive stimulation is delivered to the patient during the time period.

[0295] Embodiment 87. A method according to any one of embodiments 81 to 86, wherein the brain signal information includes one or more local field potential signals.

[0296] Embodiment 88. The method of any one of Embodiments 81 to 87, wherein an external programmer comprises the processing circuit, the external programmer being configured to control the medical device, the medical device being configured to be coupled to the one or more electrical leads.

[0297] Embodiment 89. An external programmer configured to perform the method according to any one of Embodiments 81 to 88.

[0298] Embodiment 90. An external programmer comprising means for performing the method according to any one of embodiments 81 to 88.

[0299] Embodiment 91. A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to perform the method of any one of Embodiments 81 to 88.

[0300] Embodiment 101. A method comprising: receiving, by a processing circuit, an indication of an event at a certain time; storing, in response to receiving the indication of the event, spectral information of a brain signal recorded at the time; and outputting a coordinate graph for display on a user interface, the coordinate graph indicating the spectral information of the brain signal recorded at the time.

[0301] Example 102. A method according to Example 101, wherein the indication is a first indication, the event is a first event, the brain signal is a first brain signal, and the time is a first time, and the method further includes: receiving a second indication of a second event at a second time by the processing circuit; storing spectral information of the second brain signal recorded at the second time in response to receiving the second indication of the second event; and outputting the coordinate graph for display on the user interface, the coordinate graph indicating the spectral information of the first brain signal recorded at the first time and the spectral information of the second brain signal recorded at the second time.

[0302] Embodiment 103 The method of any one of Embodiments 101 and 102, wherein receiving the indication of the event comprises receiving user input indicating the event via a user interface.

[0303] Embodiment 104. The method according to any one of Embodiments 101 to 103, further comprising: recording the brain signal in response to receiving the indication of the event; and generating the spectral information of the brain signal after recording the brain signal.

[0304] Example 105. A method according to any one of Examples 101 to 104, wherein the spectral information of the brain signal recorded at the time is stored including selecting the brain signal from a rolling buffer, which includes brain signals sensed within a time period including the time.

[0305] Embodiment 106. The method of any one of Embodiments 101 to 105, wherein receiving the indication of the event comprises automatically identifying, by the processing circuit, the event from at least one of brain signal information or electrical stimulation status.

[0306] Embodiment 107. The method of any one of Embodiments 101 to 106, wherein the event comprises at least one of a patient fall, a medication administration time, a patient symptom, or a stimulation delivery event.

[0307] Example 108. A method according to any one of Examples 101 to 107, wherein the brain signal recorded at the time is one brain signal among multiple brain signals recorded at the corresponding time, and wherein the method further comprises: receiving user input for selecting at least the one brain signal from the multiple brain signals; and outputting the spectral information of the at least one brain signal selected according to the user input for display via the user interface.

[0308] Embodiment 109. The method according to any one of embodiments 101 to 108, wherein the coordinate graph displays the spectral information as a graph of the relationship between the magnitude of the brain signal and the frequency of the brain signal.

[0309] Embodiment 110. A method according to any one of embodiments 101 to 109, wherein the brain signal includes one or more local field potential signals.

[0310] Embodiment 111. The method of any one of Embodiments 101 to 110, wherein an external programmer comprises the processing circuit, the external programmer being configured to control the medical device, the medical device being configured to be coupled to the one or more electrical leads.

[0311] Embodiment 112 An external programmer configured to perform the method according to any one of Embodiments 101 to 111.

[0312] Embodiment 113. An external programmer comprising means for performing the method according to any one of Embodiments 101 to 111.

[0313] Embodiment 114. A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to perform the method according to any one of Embodiments 101 to 111.

[0314] Embodiment 115. A system comprising an implantable deep brain stimulation device and an external programmer according to any one of embodiments 10, 11, 32, 33, 49, 50, 69, 70, 89, 90, 112 and 113.

[0315] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the techniques may be implemented within one or more processors, such as fixed-function processing circuits and / or programmable processing circuits, including one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuits, and any combination of such components. The term "processor" or "processing circuitry" may generally refer to any of the foregoing logic circuitry, or any other equivalent circuitry, alone or in combination with other logic circuitry. A control unit comprising hardware may also perform one or more of the techniques of this disclosure.

[0316] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various operations and functions described in this disclosure. In addition, any of the units, modules, or components may be implemented together or individually as discrete but interoperable logical devices. Describing different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be implemented by separate hardware or software components. On the contrary, the functions associated with one or more modules or units may be performed by separate hardware or software components, or integrated within common or separate hardware or software components.

[0317] The techniques described in this disclosure may also be embedded or encoded in a computer-readable medium (such as a computer-readable storage medium) containing instructions. The instructions embedded or encoded in the computer-readable storage medium may cause a programmable processor or other processor to perform the method, for example, when executing these instructions. The computer-readable storage medium may include a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette tape, a magnetic medium, an optical medium, or other computer-readable medium.

[0318] Various examples have been described. These and other examples are within the scope of the following claims.

Claims

1. A method comprising: obtaining, by a processing circuit, brain signal information of at least one electrode combination among a plurality of electrode combinations of one or more electrical leads; determining, by the processing circuitry, a corresponding frequency for the at least one electrode combination based on the brain signal information; outputting a plurality of selectable lead icons for display, wherein each selectable lead icon of the plurality of selectable lead icons represents a different electrode combination of the plurality of electrode combinations; outputting for display the respective frequencies determined for the at least one electrode combination in association with a respective selectable lead icon associated with the at least one electrode combination; receiving user input selecting one of the plurality of selectable lead icons; as well as In response to receiving the user input, the processing circuit selects, for subsequent brain signal sensing, a sensing electrode combination associated with the one selectable lead icon selected by the user input.

2. The method according to claim 1, further comprising: Output selectable signal test icon for display; receiving user input selecting the selectable signal test icon; as well as In response to receiving the user input selecting the selectable signal test icon, controlling the medical device to obtain brain signal information of at least one electrode combination of the plurality of electrode combinations.

3. The method of any one of claims 1 or 2, wherein the plurality of electrode combinations comprises all electrode combinations possible for the one or more electrical leads implanted in the patient.

4. The method according to claim 1 or 2, further comprising: analyzing the brain signal information for the presence of artifacts associated with at least one of electrocardiographic sensing or movement of the one or more electrical leads; determining that the artifact does not exist in the brain signal information; as well as In response to determining that the artifact is not present, the at least one electrode combination is approved for user selection for subsequent brain signal sensing. 5 . The method of claim 4 , wherein analyzing the brain signal information for the presence of the artifact comprises applying a logistic regression classifier to at least a portion of the brain signal information.

6. The method according to claim 5 further includes determining multiple signal features from the brain signal information, the multiple signal features including entropy of multiple frequency bands within the brain signal information and multiple time-domain threshold crossing features, wherein applying the logistic regression classifier to the portion of the brain signal information includes applying the logistic regression classifier to the multiple signal features.

7. A method according to claim 4, wherein analyzing the presence of the artifact associated with the electrocardiogram in the brain signal information includes analyzing the fast Fourier transform (FFT) amplitude spacing of the brain signal information at approximately 8 Hz between a first brain signal detected during electrical stimulation delivery and a second brain signal detected during no electrical stimulation delivery; and wherein the FFT amplitude spacing being less than a spacing threshold indicates the absence of the artifact.

8. The method according to claim 1 or 2, wherein the brain signal information includes one or more local field potential signals.

9. The method of claim 1 or 2, wherein the processing circuit is comprised by an external programmer configured to control an implantable medical device configured to be coupled to the one or more electrical leads. 10 . An external programmer, configured to execute the method according to claim 1 .

11. The external programmer of claim 10, wherein the external programmer is configured to control an implantable medical device configured to be coupled to one or more electrical leads. 12 . A non-transitory computer-readable medium comprising instructions that, when executed, control a processing circuit to perform the method according to claim 1 .

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