Patient therapy management using sensed patient data

Abstract

In general, devices, systems, and techniques are described for managing therapy based on monitoring sensed signals from a patient. In one example, a digital health system includes processing circuitry configured to receive sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient, determine aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time, generate a graph comprising the aggregate characteristic values for the repeatable duration; and control a user interface to display the graph.

Description

Docket No.: A0013259W001 / 1123-863W001PATIENT THERAPY MANAGEMENT USING SENSED PATIENT DATA

[0001] This application is a PCT application claiming priority to, and the benefit of U.S. Provisional Patent Application No. 63 / 700,455, filed September 27, 2024, the entire contents of which is incorporated herein by reference.TECHNICAL FIELD

[0002] This disclosure generally relates to managing patient therapy, and specifically, monitoring collected data related to patient therapy.BACKGROUND

[0003] Medical devices may be external or implanted and may be used to deliver electrical stimulation therapy to various tissue sites of a patient to treat a variety of symptoms or conditions such as chronic pain, tremor, Parkinson’s disease, other movement disorders, epilepsy, urinary or fecal incontinence, sexual dysfunction, obesity, or gastroparesis. A medical device may deliver electrical stimulation therapy via one or more leads that include electrodes located proximate to target locations associated with the brain, the spinal cord, pelvic nerves, peripheral nerves, or the gastrointestinal tract of a patient. Hence, electrical stimulation may be used in 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 may monitor various data regarding the patient. In addition, the clinician may select values for a number of programmable parameters in order to define the electrical stimulation therapy to be delivered by the implantable stimulator to a patient. For example, the clinician may select one or more electrodes for delivery of the stimulation, a polarity of each selected electrode, a voltage or current amplitude, a pulse width, and a pulse frequency as stimulation parameters. A set of parameters, such as a set including electrode combination, electrode polarity, voltage or current amplitude, pulse width and pulse rate, may be referred to as a program in the sense that they define the electrical stimulation therapy to be delivered to the patient.SUMMARY

[0005] In general, the disclosure describes devices, systems, and techniques related to a digital health platform. The digital health platform can be provided by a digital health system that includes one or more servers, computing devices, programmers, and / or other devices. The digital health system can be configured to receive information related to therapy of a patient,Docket No.: A0013259W001 / 1123-863W001 such as medical schedules, medication dosages, patient activity, sensed signals (e.g., bioelectrical signals such as local field potentials (LFPs)), parameters that define delivered electrical stimulation therapy, or any other information. The digital health platform may include a user interface that is generated by one or more devices such as an external server, external programmer, or other device.

[0006] The digital health system can perform analysis on received information, control medical devices based on updated parameters, and control the user interface to present any received information in different configurations. For example, the digital health system may be configured to control the user interface to display sensed data, medication schedules, stimulation parameter values for different periods of time which can enable a user to view differences between periods of time that the patient received therapy or otherwise was monitored. In some examples, the system can control the user interface to present a graph that tracks different symptoms of the patient over time. This user interface can receive user selection of stimulation parameter values or input to change other aspects of therapy, such as parameters that define adaptive stimulation therapy or closed-loop stimulation therapy, e.g., adaptive deep brain stimulation (aDBS), which can control a medical device to change one or more stimulation parameters based on sensed brain signals.

[0007] In some examples, the system may include an external programming device that communicates with a medical device and / or the medical device (e.g., an implantable medical device) configured to sense physiological signals such as electrical signals originating in the patient’s brain. The system may employ aspects of these signals for presenting information to the user and automating selection of various parameters, such as values for one or more adaptive stimulation thresholds, for subsequent sensing and / or delivering stimulation. Although aDBS is one non-limiting example therapy, the techniques of this disclosure may be applied to many forms of adaptive stimulation therapy that may be configured to treat other conditions and / or other anatomical structures of the patient. Information received by the external programmer may be delivered to other devices of the digital health platform, such as a remote server via an internet and / or network connections.

[0008] In one example, a digital health system includes processing circuitry configured to receive sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determine aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time; generate a graph comprising the aggregate characteristic values for the repeatable duration; and control a user interface to display the graph.Docket No.: A0013259W001 / 1123-863W001

[0009] In another example, a method includes receiving, by processing circuitry, sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determining, by the processing circuitry, aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time; generating, by the processing circuitry, a graph comprising the aggregate characteristic values for the repeatable duration; and controlling, by the processing circuitry, a user interface to display the graph.

[0010] In another example, a non-transitory computer-readable medium includes instructions that, when executed, control processing circuitry to receive sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determine aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time; generate a graph comprising the aggregate characteristic values for the repeatable duration; and control a user interface to display the graph .

[0011] The details of one or more examples of the techniques of this disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques will be apparent from the description and drawings, and from the claims.BRIEF DESCRIPTION OF DRAWINGS

[0012] FIG. l is a conceptual diagram illustrating an example system that includes an implantable medical device (IMD) configured to deliver DBS to a patient according to an example of the techniques of the disclosure.

[0013] FIG. 2 is a block diagram of the example IMD of FIG. 1 for delivering DBS therapy according to an example of the techniques of the disclosure.

[0014] FIG. 3 is a block diagram of the external programmer of FIG. 1 for controlling delivery of DBS therapy according to an example of the techniques of the disclosure.

[0015] FIG. 4 is a block diagram illustrating an example digital health system that includes an external device, such as a server, and one or more computing devices that are coupled to an implantable medical device and external programmer shown in FIG. 1 via a network.

[0016] FIG. 5 is a conceptual diagram illustrating an example patient selection screen for a digital health platform.

[0017] FIGS. 6A, 6B, and 6C are conceptual diagrams illustrating an example screen showing various received information regarding the patient.

[0018] FIGS. 6D and 6E are conceptual diagrams illustrating different screens for receiving input regarding symptoms to track and the severity of symptoms.

[0019] FIG. 6F is a conceptual diagrams illustrating an example screen showing various received information regarding the patient and changes that have occurred.Docket No.: A0013259W001 / 1123-863W001

[0020] FIG. 6G is a conceptual diagrams illustrating an example screen showing various received information regarding patient therapy and recorded events for the patient.

[0021] FIG. 7 is a conceptual diagram illustrating an example timeline trend screen of sensed signals and stimulation parameters for the patient.

[0022] FIGS. 8A and 8B are conceptual diagrams illustrating example medication screens displaying medications for different periods of time.

[0023] FIG. 9 is a conceptual diagram illustrating an example sensing configuration screen displaying signals detectable from different electrode combinations.

[0024] FIG. 10 is a conceptual diagram illustrating an example screen displaying aggregate characteristic values for different hemispheres of the brain.

[0025] FIGS. 11 A, 11B, and 11C are conceptual diagrams illustrating an example screen displaying aggregate characteristic values for different periods of time, stimulation parameters, and medication information for the patient.

[0026] FIG. 1 ID is a conceptual diagram illustrating an example print screen that the user interface can present including the medication schedule for the patient.

[0027] FIG. 1 IE is a conceptual diagram illustrating an example screen of the user interface that can accept user input for one or more thresholds and a histogram of sensed data with respect to the thresholds.

[0028] FIG. 12 is a conceptual diagram illustrating an example change screen indicating changes made to programming and medication schedule for the patient during the current clinician session.

[0029] FIG. 13 A is a conceptual diagram illustrating an example timeline trend screen showing sensed data during stimulation and non-stimulation periods of time.

[0030] FIG. 13B is a conceptual diagram illustrating an example streaming data screen showing sensed LFP power and stimulation amplitude together on a graph.

[0031] FIG. 13C is a conceptual diagram illustrating an example streaming data screen showing spectrogram and time domain graphs of sensed LFP signals over a period of time.

[0032] FIG. 14A is a conceptual diagram illustrating an example sensing configuration screen displaying signals detectable from different electrode combinations.

[0033] FIG. 14B is a conceptual diagram illustrating an example sensing configuration screen displaying signal quality for different electrodes and medication status for the patient during sensing of those signals.

[0034] FIG. 14C is a conceptual diagram illustrating an example sensing configuration screen displaying sensed signals for different electrodes selectable based on date data was sensed.Docket No.: A0013259W001 / 1123-863W001

[0035] FIG. 14D is a conceptual diagram illustrating an example sensing configuration screen displaying delivered amplitudes from each electrode during stimulation in addition with other stimulation parameters.

[0036] FIG. 14E is a conceptual diagram illustrating an example graph of the time sensed LFP values were below, between, or above respective thresholds for a certain period of time.

[0037] FIG. 15 is a conceptual diagram illustrating an example sensing configuration screen displaying signals detectable from different electrode combinations at different periods of time.

[0038] FIG. 16 is a flowchart illustrating an example technique for receiving user input selecting desired tabs of the user interface to navigate to different screens of the user interface.

[0039] FIG. 17 is a flowchart illustrating an example technique generating aggregate information for sensed data for a period of time.

[0040] FIG. 18 is a flowchart illustrating an example technique for generating a DBS flag indicating the patient could receive DBS therapy based on sensed data for the patient.

[0041] FIGS. 19 and 20 are conceptual illustrations of an example user interface for annotating or changing initial programming decisions.DETAILED DESCRIPTION

[0042] This disclosure describes example devices, systems, and techniques for a digital health platform that enables the collection of different types of data relating to patient monitoring and therapy, analysis and comparison of collected data, and adjustment of medication and / or stimulation therapy for treating the patient. A patient may suffer from one or more symptoms treatable by medication, electrical stimulation therapy, or combination thereof. For example, a patient may suffer from brain disorder such as Parkinson’s disease, Essential Tremor, OCD, Epilepsy, Dystonia, or other disease states. In some examples, one or more different medications may alleviate various symptoms and improve a patient’s quality of life. In some examples, deep brain stimulation (DBS) may be an effective treatment to reduce the symptoms associated with such disorders. However, it may be difficult and time consuming for a clinician to determine how and when to adjust medication, how medication or DBS changes are affecting patient symptoms or when a patient may benefit from DBS. Moreover, during DBS therapy, the clinician may have difficulty viewing collected data for determining any changes that may be needed to therapy, medication, or other aspects of treatment for the patient.

[0043] In addition, it can be challenging for clinicians to identify patient events, e.g., falls, and patient conditions and what types of adjustments could be made to improve therapy over time. Even if a system could detect an indication of these patient changes, that introducesDocket No.: A0013259W001 / 1123-863W001 another parameter that the clinician would need to identify as part of initial set-up of therapy and / or over the life of therapy delivery for that patient.

[0044] In a closed-loop adaptive stimulation therapy scenario, one or more parameters that define the stimulation can be automatically adjusted in response to sensed signals from the patient. For example, a sensed signal, such as an LFP signal, can be compared to one or more thresholds. In response to a characteristic value of the LFP signal (e.g., spectral power for a specific frequency or frequency band of the LFP signal) meeting or exceeding a threshold, the system may automatically adjust a stimulation parameter value (e.g., an amplitude value) to bring that characteristic of the LFP signal back below (or above) the threshold value. In some examples, a clinician may initially select the value for one or more thresholds. If two thresholds are used, this may create a “homeostatic window” for the sensed signal. Other thresholds may also be used, such as one or more limits that can define a “therapeutic window” defining acceptable stimulation parameter values (e.g., amplitude) for stimulation. For some patients, medication may be prescribed in addition to stimulation therapy. This medication can change how the patient perceives symptoms and / or responds to stimulation therapy. If the clinician initially sets threshold values when no medication is being taken, the threshold values may be inaccurate when the patient is taking medication. Threshold value determination may be more accurate when the patient is taking medication, but that may not be possible in the clinic setting or when the patient is otherwise initially fitted for therapy. The clinician and / or patient may adjust these threshold values over time, but this manual adjustment is usually a “best guess” based on subjective feedback from the patient. Moreover, the patient may not accurately convey perceived symptoms or when side effects are felt due to inappropriate stimulation settings during therapy. Even if the clinician adjusts a threshold value in the right direction, the magnitude of such threshold value change may not be appropriate and require additional adjustments over time. Over this time of manual adjustments, the patient may be experiencing therapy that is less efficacious than otherwise possible.

[0045] As described herein, various devices, systems, and techniques enable a digital health platform that can acquire various data on the patient and provide insight, analysis, and visual data that a clinician may use to monitor and adjust any element of treatment. For example, one or more networked devices of a digital health system can support the digital health platform and provide a user interface that can be accessed by a clinician or other user via a networked computing device, programmer, or other devices. In this manner, a clinician can review data for one or more patients remotely. In addition, the digital health system can analyze data and present the data in forms that are easy to understand and highlight differences due to changes in patientDocket No.: A0013259W001 / 1123-863W001 condition, changes to therapy, changes in time, or other differences that may cause changes in the patient’s therapy.

[0046] The user interface may include a plurality of different screens and enable the user to navigate between the screens as desired using respective tabs. For example, in response to receiving selection of one of the tabs via the user interface, the system can present information for the selected tab. Via these tabs, the user interface can present information regarding tracked symptoms, symptom severity, medication schedules, DBS programming information (e.g., one or more groups of stimulation parameters and / or separate parameters), and other notes regarding the patient. The digital health system may receive sensed data from an IMD or other device that generates sensed signals from the patient, such as electrical signals from the brain (e.g., LFP signals), evoked signals (e.g., evoked resonant neural activation (ERNA) signals), or any other signals. The digital health system may collect this sensed data, generate various aggregate characteristic data (e.g., average, weighted average, median, etc.) of the sensed data for repeatable periods of time, variances of this data, stimulation parameters used to deliver stimulation, and generate graphs of this information for presentation via a screen of the user interface. The user interface may also present other DBS parameters, initial setup information, or any other information related to therapy.

[0047] In some examples, the digital health system may analyze sensed data from the patient to identify when the patient may begin to benefit from DBS therapy. For example, the system may compare medication schedules (e.g., expected or known taken dosages by the patient) with sensed data (e.g., LFP signals) and determine if medication can effectively control patient symptoms. If the system determines that medication is no longer effective, the system could suggest adjusted medication dosage or compound, or recommend starting DBS therapy. The system may also monitor effectiveness of delivered DBS therapy and generate flags for the clinician if DBS therapy is not effective or could benefit from adjustments to one or more parameters.

[0048] These various features of the systems and techniques described herein may provide advantages over other systems and improve system functionality and patient outcomes. For example, the system may generate a user interface that can be customized by the user for comparing collected information for the patient. The system can analyze sensed data and generate aggregated values for different information over different periods of time in order to identify, and display, changes for the patient. In some examples, the system may also be configured to receive user changes to any therapy parameters via the user interface which can reduce clinician time and improve patient outcomes. These features associated with monitoring therapy and collected data over time in one location can reduce expended clinician time, improveDocket No.: A0013259W001 / 1123-863W001 consistency of parameter / medication selection, and improve therapeutic results for the patient by increasing therapeutic stimulation efficacy and reducing side effects.

[0049] FIG. 1 is a conceptual diagram illustrating an example system 100 that includes an implantable medical device (IMD) 106 configured to deliver deep brain stimulation to a patient 112. DBS may be delivered in an open-loop manner in which stimulation therapy is delivered according to pre-set parameters that are only changed manually as needed. Alternatively, DBS may be adaptive (aDBS) in the sense that IMD 106 (or other device) may automatically adjust, increase, or decrease the value of one or more stimulation parameters that define the DBS in response to changes in patient activity or movement, a severity of one or more symptoms of a disease of the patient, a presence of one or more side effects due to the DBS, or one or more sensed signals of the patient, etc. For example, system 100 may use one or more sensed signals of the patient as a control signal such that the IMD 106 adjusts the magnitude of the one or more parameters of the electrical stimulation in response to the magnitude or change in magnitude of the one or more sensed signals. This process enables system 100 to automatically adjust stimulation therapy in response to changes to the patient condition, such as changes to brain activity indicative of a level of therapy efficacy.

[0050] Example therapy system 100 includes medical device programmer 104, implantable medical device (IMD) 106, lead extension 110, and leads 114A and 114B with respective sets of electrodes 116, 118. In the example shown in FIG. 1, electrodes 116, 118 of leads 114A, 114B are positioned to deliver electrical stimulation to a tissue site within brain 120, such as a deep brain site under the dura mater of brain 120 of patient 112. In some examples, delivery of stimulation to one or more regions of brain 120, such as the subthalamic nucleus, globus pallidus or thalamus, may be an effective treatment to manage movement disorders, such as Parkinson’s disease. Some or all of electrodes 116, 118 also may be positioned to sense bioelectrical brain signals within brain 120 of patient 112. In some examples, some of electrodes 116, 118 may be configured to sense bioelectrical brain signals and others of electrodes 116, 118 may be configured to deliver adaptive electrical stimulation to brain 120. In other examples, all of electrodes 116, 118 are configured to both sense bioelectrical brain signals and deliver adaptive electrical stimulation to brain 120.

[0051] IMD 106 includes a therapy module (e.g., which may include processing circuitry, signal generation circuitry or other electrical 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 that are used to deliver electrical stimulation to patient 112, and, in some cases, the polarity of the subset of electrodes 116, 118,Docket No.: A0013259W001 / 1123-863W001 may be referred to as a stimulation electrode combination. As described in further detail below, the stimulation electrode combination can be selected for a particular patient 112 and target tissue site (e.g., selected based on bioelectrical signal information and the patient condition). The group of electrodes 116, 118 includes at least one electrode and can include a plurality of electrodes. In some examples, the plurality of electrodes 116 and / or 118 may have a complex electrode geometry such that two or more electrodes are located at different positions around the perimeter of the respective lead.

[0052] According to some techniques of the disclosure, system 100, via IMD 106, delivers electrical stimulation therapy defined by one or more parameters, such as voltage or current amplitude, adjusted in response to a signal deviating from a range defined by a homeostatic window (e.g., a window defined by one or more thresholds to which a brain signal is compared, such as a lower threshold and upper threshold). The homeostatic window may be used as part of an adaptive stimulation mode for adjusting stimulation therapy over time. In some examples, system 100 may change other parameters in response to sensed signals such as stimulation pulse frequency, pulse burst duration, pulse burst frequency, duty cycle, or electrode combination.

[0053] In some examples, the medication taken by patient 112 is a medication for controlling one or more symptoms of Parkinson’s disease, such as tremor or rigidity due to Parkinson’s disease. Such medications include extended release forms of dopamine agonists, regular forms of dopamine agonists, controlled release forms of carbidopa / levodopa (CD / LD), regular forms of CD / LD, entacapone, rasagiline, selegiline, and amantadine. The system may have data identifying the medication schedule, but in some examples, the system may not have data identifying when medication is delivered. Typically, to set the upper threshold and lower threshold of the homeostatic window, the patient has been off medication, i.e., the upper and lower thresholds are set when the patient is not taking medication that is intended to reduce the symptoms. The patient may be considered to be not taking the medication when the patient, prior to the time the upper threshold is set, has not taken the medication for at least approximately 72 hours for extended release forms of dopamine agonists, the patient has not taken the medication for at least approximately 24 hours for regular forms of dopamine agonists and controlled release forms of CD / LD, and the patient has not taken the medication for at least approximately 12 hours for regular forms of CD / LD, entacapone, rasagiline, selegiline, and amantadine. If only stimulation is suppressing brain signals (e.g., LFP signals), then system 100 can measure these brain signals for various values of stimulation parameters without outside inputs. Once the upper threshold and lower threshold is established, system 100 can identify when medication wears off because the brain signals will cross the lower or upper threshold. In response to identifying the brain signal crossing a threshold, system 100 may turn on, or adjust the amplitude or intensity of,Docket No.: A0013259W001 / 1123-863W001 electrical stimulation to bring back brain signal amplitudes back between the lower threshold and the upper threshold to reduce symptoms once again. Programmer 104 or IMD 106 may initially set the lower threshold and the upper threshold and make adjustments to one or both thresholds over time. Programmer 104 or IMD 106 may also determine and display information regarding the amount of time stimulation amplitude is above, below, or between the thresholds. The system may be configured to determine frequencies, adaptive modes, and one or more thresholds based on bioelectric (or other) signals sensed while the patient is subjected to medication and / or not subjected to medication. Whether or not the patient is medicated may influence which adaptive mode or thresholds are used to adjust subsequent therapy.

[0054] As described herein, “reducing” or “suppressing” the symptoms of the patient refer to alleviating, in whole or in part, the severity of one or more symptoms of the patient. In one example, the clinician makes a determination of the severity of one or more symptoms of Parkinson’s disease of patient 112 with reference 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 application of the MDS-UPDRS is provided by 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 content of which is incorporated herein in its entirety. Other assessment scales may be used in other examples and correlated to respective disease states. The digital health system may present those assessments appropriate for the patient or the clinician can select desired assessments and / or create custom assessment scales for any symptoms.

[0055] In some examples, system 100 may be configured to determine the upper threshold of a homeostatic window while the patient is not taking medication, and while, via IMD 106, electrical stimulation therapy is delivered to the brain 120 of patient 112. In one example, system 100 determines the point 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 for the patient 112. For example, system 100 may gradually increase the magnitude of one or more parameters, such as amplitude, defining the electrical stimulation therapy and determine the point at which further increase to the magnitude of one or more parameters defining the electrical stimulation therapy causes a perceptible side effect for patient 112. As described herein, IMD 106 may sense LFPs during this process and display the LFP signal and / or LFP signal magnitude that may correspond to the respective thresholds. In this manner, system 100 may automatically determine these thresholds.Docket No.: A0013259W001 / 1123-863W001

[0056] As also described herein, system 100 can also determine the lower threshold of the homeostatic window while the patient is off medication and while, via IMD 106, electrical stimulation therapy is delivered to the brain 120 of patient 112. In one example, system 100 determines the point at which decreasing the magnitude of one or more parameters, such as amplitude, defining the electrical stimulation therapy causes break-through of one or more symptoms of the patient 112. This break-through of symptoms may refer to re-emergence of at least some symptoms that were substantially suppressed up to the point of re-emergence due to the decrease in magnitude of the one or more electrical stimulation therapy parameters. For example, system 100 may gradually decrease the magnitude of one or more parameters defining the electrical stimulation therapy and determine the point at which the symptoms of Parkinson’s disease in patient 112 emerge, as measured by sudden increase with respect to tremor or rigidity, in the score of patient 112 under the UPDRS or MDS-UPDRS. In another example, system 100 measures a physiological parameter of patient 112 correlated to one or more symptoms of the disease of patient 112 (e.g., wrist flexion of patient 112) and determines the point at which further decrease to the magnitude of one or more parameters defining the electrical stimulation therapy causes a sudden increase in the one or more symptoms of the disease of patient 112 (e.g., onset of lack of wrist flexion of patient 112). Although initial thresholds of the homeostatic window may be determined when medication is off for patient 112, threshold determination when patient 112 is taking medication may be more effective in some examples. My monitoring patient events and sensed brain signals over time that therapy is delivered, the thresholds may be selected to more appropriately account for patient consumption of medication that may not be otherwise possible via manual identification during a clinic visit.

[0057] At the magnitude of one or more parameters defining the electrical stimulation therapy at which further decrease to the magnitude of one or more parameters defining the electrical stimulation therapy causes a sudden increase in the one or more symptoms of the disease of patient 112, system 100 can measure the magnitude of the signal of the patient 112 and set this magnitude as the lower threshold of the homeostatic window. In some examples, system 100 may select a lower threshold of the homeostatic window to be a predetermined amount, e.g., 5% or 10%, higher than the magnitude at which the symptoms of the patient 112 first emerge during decrease in the magnitude of one or more electrical stimulation parameters to prevent emergence of the symptoms of the patient 112 during subsequent use.

[0058] In another example, system 100 can set a lower threshold by first ensuring that the patient is off medication for the one or more symptoms. In this example, system 100 delivers electrical stimulation having a value for the one or more parameters approximately equal to the upper threshold of the therapeutic window. In some examples, system 100 delivers electricalDocket No.: A0013259W001 / 1123-863W001 stimulation having a value for the one or more parameters slightly below the magnitude which induces side effects in the patient 112. Typically, this causes greater reduction of the one or more symptoms of the disease of the patient 112, and therefore greater reduction of the signal. At this magnitude of the one or more parameters, system 100 measures the magnitude of the signal of the patient 112 and sets, via external programmer 104, this magnitude as the lower threshold of the homeostatic window. In some examples, system 100 may select a value for the lower threshold of the homeostatic window to be a predetermined amount, e.g., 5% or 10%, higher than the magnitude at which the symptoms of the patient 112 emerge to prevent emergence of the symptoms of the patient 112 during subsequent use.

[0059] System 100 can monitor one or more signals of the patient. These signals may be bioelectric brain signals such as LFP signals, evoked signals, or any other signals that can be detected from the patient. In some examples, the sensed signals may be used to monitor patient conditions or identify changes to the patient due to medication consumption, medication effectiveness, or even when the patient may be a candidate to receive DBS therapy. In some examples, the sensed signals may be used for selecting one or more parameters defining stimulation and / or adjusting stimulation in a closed-loop manner. In one example, the signal is a bioelectrical signal of a patient, such as a brain signal (e.g., LFP) with a frequency within a Beta frequency band and / or a Gamma frequency band of the brain of the patient. For example, the monitored signal may be a power of the respective Beta frequency band and / or Gamma frequency band (determined based on which frequency varies during stimulation delivery and / or under the influence of medication). In yet a further example, the signal can be a signal indicative of a physiological parameter of the patient, such as a severity of a symptom of the patient, a movement of the patient, a posture of the patient, a respiratory function of the patient, a heart rate, or an activity level of the patient. System 100 may use a single signal or combination of different signals for initially selecting and / or adjusting one or more parameters that define subsequent stimulation therapy. System 100, via IMD 106, can be configured to deliver electrical stimulation to the patient, wherein one or more parameters defining the electrical stimulation are proportional to the magnitude of the monitored signal or adjusted in response to a magnitude of the monitored signal exceeding one or more thresholds.

[0060] System 100 may be configured to treat one or more patient conditions, such as a movement disorder, neurodegenerative impairment, a mood disorder, or a seizure disorder of patient 112. Patient 112 ordinarily is a human patient. In some cases, however, therapy system 100 may be applied to other mammalian or non-mammalian, non-human patients. While movement disorders and neurodegenerative impairment are primarily referred to herein, in other examples, therapy system 100 may provide therapy to manage symptoms of other patientDocket No.: A0013259W001 / 1123-863W001 conditions, such as, but not limited to, seizure disorders (e.g., epilepsy) or mood (or psychological) disorders (e.g., major depressive disorder (MDD), bipolar disorder, anxiety disorders, post-traumatic stress disorder, dysthymic disorder, and obsessive-compulsive disorder (OCD)). At least some of these disorders may be manifested in one or more patient movement behaviors. As described herein, a movement disorder or other neurodegenerative impairment may include symptoms such as, for example, muscle control impairment, motion impairment or other movement problems, such as rigidity, spasticity, bradykinesia, rhythmic hyperkinesia, nonrhythmic hyperkinesia, and akinesia. In some cases, the movement disorder may be a symptom of Parkinson’s disease. However, the movement disorder may be attributable to other patient conditions.

[0061] In some examples, the bioelectrical signals sensed within brain 120 may reflect changes in electrical current produced by the sum of electrical potential differences across brain tissue. Examples of bioelectrical brain signals include, but are not limited to, electrical signals generated from local field potentials (LFP) sensed within one or more regions of brain 120, such as an electroencephalogram (EEG) signal, or an electrocorticogram (ECoG) signal. Local field potentials, however, may include a broader genus of electrical signals within brain 120 of patient 112. Other brain signals that may be sensed may be or include evoked signals such as a ERNA signals.

[0062] In some examples, the bioelectrical brain signals that are used to select a stimulation electrode combination may be sensed within the same region of brain 120 as the target tissue site for the electrical stimulation. As previously indicated, these tissue sites may include tissue sites within anatomical structures such as the thalamus, subthalamic nucleus or globus pallidus of brain 120, as well as other target tissue sites. The specific target tissue sites and / or regions within brain 120 may be selected based on the patient condition. Thus, in some examples, the electrodes used for delivering electrical stimulation may be different than the electrodes used for sensing bioelectrical brain signals. In other examples, the same electrodes may be used to deliver electrical stimulation and sense brain signals. However, this configuration may require system 100 to switch between stimulation generation and sensing circuitry and may reduce the time system 100 can sense brain signals.

[0063] Electrical stimulation generated by IMD 106 may be configured to manage a variety of disorders and conditions. In some examples, the stimulation generator of IMD 106 is configured to generate and deliver electrical stimulation pulses to patient 112 via electrodes of a selected stimulation electrode combination. However, in other examples, the stimulation generator of IMD 106 may be configured to generate and deliver a continuous wave signal, e.g., a sine wave or triangle wave. In either case, a stimulation generator within IMD 106 mayDocket No.: A0013259W001 / 1123-863W001 generate the electrical stimulation therapy for DBS according to a therapy program that is selected at that given time in therapy. In examples in which IMD 106 delivers electrical stimulation in the form of stimulation pulses, a therapy program may include a set of therapy parameter values (e.g., stimulation parameters), such as a stimulation electrode combination for delivering stimulation to patient 112, pulse frequency, pulse width, and a current or voltage amplitude of the pulses. As previously indicated, the electrode combination may indicate the specific electrodes 116, 118 that are selected to deliver stimulation signals to tissue of patient 112 and the respective polarities of the selected electrodes.

[0064] IMD 106 may be implanted within a subcutaneous pocket above the clavicle, or, alternatively, on or within cranium 122 or at any other suitable site within patient 112. Generally, IMD 106 is constructed of a biocompatible material that resists corrosion and degradation from bodily fluids. IMD 106 may comprise a hermetic housing to substantially enclose components, such as a processor, therapy module, and memory.

[0065] As shown in FIG. 1, implanted lead extension 110 is coupled to IMD 106 via connector 108 (also referred to as a connector block or a header of IMD 106). In the example of FIG. 1, lead extension 110 traverses from the implant site of IMD 106 and along the neck of patient 112 to cranium 122 of patient 112 to access brain 120. In the example shown in FIG. 1, leads 114A and 114B (collectively “leads 114”) are implanted within the right and left hemispheres, respectively, of patient 112 in order deliver electrical stimulation to one or more regions of brain 120, which may be selected based on the patient condition or disorder controlled by therapy system 100. The specific target tissue site and the stimulation electrodes used to deliver stimulation to the target tissue site, however, may be selected, e.g., according to the identified patient behaviors and / or other sensed patient parameters. Other lead 114 and IMD 106 implant sites are contemplated. For example, IMD 106 may be implanted on or within cranium 122, in some examples. Or leads 114 may be implanted within the same hemisphere or IMD 106 may be coupled to a single lead implanted in a single hemisphere.

[0066] Existing lead sets include axial leads carrying ring electrodes disposed at different axial positions and so-called “paddle” leads carrying planar arrays of electrodes. Selection of electrode combinations within an axial lead, a paddle lead, or among two or more different leads presents a challenge to the clinician. In some examples, more complex lead array geometries may be used.

[0067] Although leads 114 are shown in FIG. 1 as being coupled to a common lead extension 110, in other examples, leads 114 may be coupled to IMD 106 via separate lead extensions or directly to connector 108. Leads 114 may be positioned to deliver electrical stimulation to one or more target tissue sites within brain 120 to manage patient symptoms associated with aDocket No.: A0013259W001 / 1123-863W001 movement disorder of patient 112. Leads 114 may be implanted to position electrodes 116, 118 at desired locations of brain 120 through respective holes in cranium 122. Leads 114 may be placed at any location within brain 120 such that electrodes 116, 118 are capable of providing electrical stimulation to target tissue sites within brain 120 during treatment. For example, electrodes 116, 118 may be surgically implanted under the dura mater of brain 120 or within the cerebral cortex of brain 120 via a burr hole in cranium 122 of patient 112, and electrically coupled to IMD 106 via one or more leads 114.

[0068] In the example shown in FIG. 1, electrodes 116, 118 of leads 114 are shown as ring electrodes. Ring electrodes may be used in aDBS applications because they are relatively simple to program and are capable of delivering an electrical field to any tissue adjacent to electrodes 116, 118. In other examples, electrodes 116, 118 may have different configurations. For example, in some examples, at least some of the electrodes 116, 118 of leads 114 may have a complex electrode array geometry that is capable of producing shaped electrical fields. The complex electrode array geometry may include multiple electrodes (e.g., partial ring or segmented electrodes) around the outer perimeter of each lead 114, rather than one ring electrode. In this manner, electrical stimulation may be directed in a specific direction from leads 114 to enhance therapy efficacy and reduce possible adverse side effects from stimulating a large volume of tissue. In some examples, a housing of IMD 106 may include one or more stimulation and / or sensing electrodes. In alternative examples, leads 114 may have shapes other than elongated cylinders as shown in FIG. 1. For example, leads 114 may be paddle leads, spherical leads, bendable leads, or any other type of shape effective in treating patient 112 and / or minimizing invasiveness of leads 114.

[0069] In the example shown in FIG. 1, IMD 106 includes a memory to store a plurality of therapy programs that each define a set of therapy parameter values. In some examples, IMD 106 may select a therapy program from the memory based on various parameters, such as sensed patient parameters and the identified patient behaviors. IMD 106 may generate electrical stimulation based on the selected therapy program to manage the patient symptoms associated with a movement disorder.

[0070] External programmer 104 wirelessly communicates with IMD 106 as needed to provide or retrieve therapy information. Programmer 104 is an external computing device that the user, e.g., a clinician and / or patient 112, may use to communicate with IMD 106. For example, programmer 104 may be a clinician programmer that the clinician uses to communicate with IMD 106 and program one or more therapy programs for IMD 106. Alternatively, programmer 104 may be a patient programmer that allows patient 112 to select programs and / or view and modify therapy parameters. The clinician programmer may include more programming featuresDocket No.: A0013259W001 / 1123-863W001 than the patient programmer. In other words, more complex or sensitive tasks may only be allowed by the clinician programmer to prevent an untrained patient from making undesirable changes to IMD 106. Programmer 104 may be any type of device that is configured to communicate with IMD 106, such as a smart watch, hand-held computer, mobile device, recharger, or any other device.

[0071] When programmer 104 is configured for use by the clinician, programmer 104 may be used to transmit initial programming information to IMD 106. This initial information may include hardware information, such as the type of leads 114 and the electrode arrangement, the position of leads 114 within brain 120, the configuration of electrode array 116, 118, initial programs defining therapy parameter values, and any other information the clinician desires to program into IMD 106. Programmer 104 may also be capable of completing functional tests (e.g., measuring the impedance of electrodes 116, 118 of leads 114). In addition, or as an alternative, to programmer 104, a different external computing device may perform any of the functionality of programmer 104. The external computing device may be a networked device and in communication with IMD 106 directly or via programmer 104.

[0072] The clinician may also store therapy programs within IMD 106 with the aid of programmer 104 or another device of a digital health system that is in communication with IMD 106. During a programming session, system 100 may determine one or more therapy programs that may provide efficacious therapy to patient 112 to address symptoms associated with the patient condition, and, in some cases, specific to one or more different patient states, such as a sleep state, movement state or rest state. For example, system 100 may select one or more stimulation electrode combination with which stimulation is delivered to brain 120. During the programming session, system 100 may evaluate the efficacy of the specific program being evaluated based on feedback provided by the clinician, patient 112, or based on one or more physiological parameters of patient 112 (e.g., muscle activity, muscle tone, rigidity, tremor, etc.). Alternatively, identified patient behavior from video information may be used as feedback during the initial and subsequent programming sessions.

[0073] Programmer 104 may also be configured for use by patient 112. When configured as a patient programmer, programmer 104 may have limited functionality (compared to a clinician programmer) in order to prevent patient 112 from altering critical functions of IMD 106 or applications that may be detrimental to patient 112. In this manner, programmer 104 may only allow patient 112 to adjust values for certain therapy parameters or set an available range of values for a particular therapy parameter. When programmer 104 is configured for use by patient 112 (e.g., a patient programmer), programmer 104 may have a limited set of adjustments and / or data available to the user compared with a clinician programmer. In this manner, the patientDocket No.: A0013259W001 / 1123-863W001 programmer version may prevent the patient from causing detrimental changes to therapy, but allow the patient to make some adjustments to therapy as desired.

[0074] Programmer 104 may also provide an indication to patient 112 when therapy is being delivered, when patient input has triggered a change in therapy or when the power source within programmer 104 or IMD 106 needs to be replaced or recharged. For example, programmer 112 may include an alert LED, may flash a message to patient 112 via a programmer display, generate an audible sound or somatosensory cue to confirm patient input was received, e.g., to indicate a patient state or to manually modify a therapy parameter.

[0075] Therapy system 100 may be implemented to provide chronic stimulation therapy to patient 112 over the course of several months or years. However, system 100 may also be employed on a trial basis to evaluate therapy before committing to full implantation. If implemented temporarily, some components of system 100 may not be implanted within patient 112. For example, patient 112 may be fitted with an external medical device, such as a trial stimulator, rather than IMD 106. The external medical device may be coupled to percutaneous leads or to implanted leads via a percutaneous extension. If the trial stimulator indicates DBS system 100 provides effective treatment to patient 112, the clinician may implant a chronic stimulator within patient 112 for relatively long-term treatment.

[0076] Although IMD 104 is described as delivering electrical stimulation therapy to brain 120, IMD 106 may be configured to direct electrical stimulation to other anatomical regions of patient 112 in other examples. In other examples, system 100 may include an implantable drug pump in addition to, or in place of, IMD 106. Further, an IMD may provide other electrical stimulation such as spinal cord stimulation to treat a movement disorder.

[0077] System 100 can define a homeostatic window (e.g., one or more thresholds of an adaptive stimulation mode) and / or a therapeutic window for delivering aDBS to patient 112. System 100 may 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 the sensed bioelectrical signal, e.g., LFP signal, evoked resonant neural activity (ERNA), and EEG, within the homeostatic window. For example, system 100 may adjust the one or more parameters defining the electrical stimulation in response to the sensed signal falling below the lower threshold or exceeding the upper threshold of the homeostatic window but may not adjust the one or more parameters defining the electrical stimulation such that they fall below the lower limit or exceed the upper limit of the therapeutic window.

[0078] In one example, external programmer 104 issues commands to IMD 106, via instructions transmitted from external programmer 104 to IMD 106, causing IMD 106 to deliverDocket No.: A0013259W001 / 1123-863W001 electrical stimulation therapy via electrodes 116, 118 via leads 114. As described above, in one example, the therapeutic window can define an upper bound and / or a lower bound for one or more parameters (e.g., amplitude or pulse width) defining the delivery of electrical stimulation therapy to patient 112. In other words, the one or more bounds for the therapeutic window may refer to the limits of values that the parameter defining stimulation can be adjusted. For example, the one or more parameters include a current amplitude (for a current-controlled system) or a voltage amplitude (for a voltage-controlled system), a pulse rate or frequency, and a pulse width. In examples where the electrical stimulation is delivered according to a “burst” of pulses, or a series of electrical pulses defined by an “on-time” and an “off-time,” the one or more parameters may further define one or more of a number of pulses per burst, an on-time, and an off-time. In one example, the therapeutic window defines an upper bound and a lower bound for one or more parameters, such as upper and lower threshold for a current amplitude of the electrical stimulation therapy (in current-controlled systems) or upper and lower threshold of a voltage amplitude of the electrical stimulation therapy (in voltage-controlled systems). While the examples herein are typically given with respect to adjusting a voltage amplitude or a current amplitude, the techniques herein may equally be applied to a homeostatic window and a therapeutic window using other parameters, such as, e.g., pulse rate or pulse width. Example implementations of the therapeutic window are provided in further detail below.

[0079] Typically, a patient programmer 104 may not have access to adjustments to any thresholds or limits for sensing or stimulation related to aDBS. For example, patient programmer 104 may only enable a patient to adjust a stimulation parameter value between limits set by the clinician programmer. However, in other examples, system 100 may provide aDBS by permitting a patient 112, e.g., via a patient programmer 104, to indirectly adjust the activation, deactivation, and magnitude of the electrical stimulation by adjusting the lower and upper threshold of the homeostatic window. In one example, the patient programmer 104 may only be enabled to adjust an upper or lower threshold of the homeostatic window a small magnitude or percentage of the clinician-set value. In another example, by adjusting one or both thresholds of the homeostatic window, patient 112 may adjust the point at which the sensed signal deviates from the homeostatic window, triggering system 100 to adjust one or more parameters of the electrical stimulation within a parameter range defined by the lower and upper threshold of the therapeutic window.

[0080] In some examples, a patient may provide feedback, e.g., via programmer 104, to adjust one or both thresholds of the homeostatic window. For example, programmer 104 may provide an input mechanism where the patient can provide an input indicating when therapy is no longer effective (e.g., symptoms are detected by the patient) or a side effect is felt. ProgrammerDocket No.: A0013259W001 / 1123-863W001104 may then use this patient event data, and the associated sensed signals corresponding to this event, to automatically adjust a threshold of the homeostatic window and / or a bound of the therapeutic window in order to reduce the issue associated with the patient feedback. In one examples, programmer 104 may determine a range of appropriate values for one or more thresholds within which the user can select a new threshold value, or programmer 104 may automatically select a new threshold value which may be presented for confirmation from a user. In another example, programmer 104 may re-run the threshold determination process described herein or analyze stored sensed bioelectric signals (e.g., LFP signals) and associated stimulation amplitudes to adjust one or more of the thresholds of the adaptive mode. In this manner, programmer 104 and / or IMD 106 may automatically adjust one or more thresholds of the homeostatic window based on one or more physiological or bioelectrical signals of patient 112 sensed by IMD 106 and corresponding patient events that have been identified. In response to deviations in the sensed signal of the patient outside of the homeostatic window, system 100 (e.g., IMD 106 or programmer 104) may automatically adjust one or more parameters (e.g., amplitude) defining the electrical stimulation therapy delivered to the patient in a manner that is proportional to the magnitude of the sensed signal and within the therapeutic window defining lower and upper thresholds for the one or more parameters. The adjustment to the one or more stimulation therapy parameters based on the deviation of the sensed signal may be proportional or inversely proportional to the magnitude of the signal.

[0081] Hence, in some examples, system 100, via programmer 104 or IMD 106, may adjust one or more parameters of the electrical stimulation, such as voltage or current amplitude, within the therapeutic window based on patient input that adjusts the homeostatic window, or based on one or more signals, such as sensed physiological parameters or sensed bioelectrical signals, or a combination of two or more of the above. In particular, system 100 may adjust a parameter of the electrical stimulation, automatically in response to the sensed signal satisfying the one or more thresholds of the homeostatic window and / or in response to patient input that adjusts the homeostatic window, provided the value of the electrical stimulation parameter is constrained to remain within a range specified by the upper and lower bound of the therapeutic window. This range may be considered to include the upper and lower bound themselves.

[0082] In some examples where system 100 adjusts multiple parameters of the electrical stimulation, system 100 may adjust at least one of a voltage amplitude or current amplitude, a stimulation frequency, a pulse width, or a selection of electrodes, and the like. In such an example, system 100 may set an order or sequence for adjustment of the parameters (e.g., adjust voltage amplitude or current amplitude, then adjust stimulation frequency, and then adjust the selection of electrodes). In other examples, system 100 may randomly select a sequence ofDocket No.: A0013259W001 / 1123-863W001 adjustments to the multiple parameters. In either example, system 100 may adjust a value of a first parameter of the parameters of the electrical stimulation. If the signal does not exhibit a response to the adjustment of the first parameter, system 100 may adjust a value of a second parameter of the parameters of the electrical stimulation, and so on until the signal returns to within the homeostatic window.

[0083] To adaptively adjust a parameter that defines DBS based on a bioelectrical signal, for example, two or more electrodes 116, 118 of IMD 106 may be configured to monitor a bioelectrical signal (e.g., an LFP signal) of patient 112. In some examples, at least one of electrodes 116, 118 may be provided on a housing of IMD 106, providing a unipolar stimulation and / or sensing configuration. In one example, the bioelectrical signal may be selected to be a signal within a Beta frequency band of brain 120 of patient 112. For example, bioelectrical signals within the Beta frequency band of patient 112 may correlate to one or more symptoms of Parkinson’s disease in patient 112. Generally, bioelectrical signals within the Beta frequency of patient 112 may be approximately proportional to the severity of the symptoms of patient 112. For example, as tremor induced by Parkinson’s disease increases, bioelectrical signals within the Beta frequency of patient 112 increase (e.g., magnitude of the signal and / or spectral power). Moreover, bioelectrical signals within the Beta frequency are considered proportional because system 100 may be configured such that an increase in signal magnitude may trigger system 100 to increase delivered stimulation therapy magnitude according to disclosed techniques. Similarly, as tremor induced by Parkinson’s disease decreases, bioelectrical signals within the Beta frequency of patient 112 decrease (e.g., magnitude of the signal and / or spectral power), and the decrease may trigger system 100 to decrease the magnitude of delivered stimulation. However, in some examples, these relationships between signal changes and symptom changes may be inversed for some patients which require the system to react in an inverse manner. In some examples, one or more frequencies in the Gamma band may be responsive to stimulation for some patients. This Gamma band responsiveness may come with or without Beta suppression from stimulation therapy.

[0084] In some examples, each of a sensor within IMD 106 is an accelerometer, a bonded piezoelectric crystal, a mercury switch, or a gyro. In some examples, these sensors may provide a signal that indicates a physiological parameter of the patient, which in turn varies as a function of patient activity. For example, the device may monitor a signal that indicates the heart rate, electrocardiogram (ECG) morphology, electroencephalogram (EEG) morphology, respiration rate, respiratory volume, core temperature, subcutaneous temperature, or muscular activity of the patient. Any of these sensed signals may be used to identify a patient event that may be a symptom and / or side effect of the patient.Docket No.: A0013259W001 / 1123-863W001

[0085] In some examples, the sensors generate a signal both as a function of patient activity and patient posture. For example, accelerometers, gyros, or magnetometers may generate signals that indicate both the activity and the posture of a patient 112. External programmer 104 may use such information regarding posture to determine whether external programmer 104 should perform adjustments to the therapeutic window. Sensors such as these may be used for any therapy or monitoring or patient activity, including DBS or SCS therapy.

[0086] For example, in order to identify posture, the sensors such as accelerometers may be oriented substantially orthogonally with respect to each other. In addition to being oriented orthogonally with respect to each other, each of the sensors used to detect the posture of a patient 112 may be substantially aligned with an axis of the body of a patient 112. When accelerometers, for example, are aligned in this manner, the magnitude and polarity of DC components of the signals generate by the accelerometers indicate the orientation of the patient relative to the Earth’s gravity, e.g., the posture of a patient 112. Further information regarding use of orthogonally aligned accelerometers to determine patient posture may be found in a commonly assigned U.S. Patent No. 5,593,431, which issued to Todd J. Sheldon, the entire content of which is incorporated by reference herein.

[0087] Other sensors that may generate a signal that indicates the posture of a patient 112 include electrodes that generate a signal as a function of electrical activity within muscles of a patient 112, e.g., an electromyogram (EMG) signal, or a bonded piezoelectric crystal that generates a signal as a function of contraction of muscles. Electrodes or bonded piezoelectric crystals may be implanted in the legs, buttocks, chest, abdomen, or back of a patient 112, and coupled to one or more of external programmer 104 and IMD 106 wirelessly or via one or more leads. Alternatively, electrodes may be integrated in a housing of the IMD 106, or piezoelectric crystals may be bonded to the housing when IMD 106 is implanted in the buttocks, chest, abdomen, or back of a patient 112. The signals generated by such sensors when implanted in these locations may vary based on the posture of a patient 112, e.g., may vary based on whether the patient is standing, sitting, or lying down.

[0088] Further, the posture of a patient 112 may affect the thoracic impedance of the patient. Consequently, sensors may include an electrode pair, including one electrode integrated with the housing of IMDs 106 and one of electrodes 116, 118, that generate a signal as a function of the thoracic impedance of a patient 112, and IMD 106 may detect the posture or posture changes of a patient 112 based on the signal. 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 electrodes located proximate to the spine of a patient for delivery of SCS therapy, and IMD 106 with an electrode integrated in its housing may be implanted in the abdomen or chest of patientDocket No.: A0013259W001 / 1123-863W001112. As another example, IMD 106 may include electrodes implanted to detect thoracic impedance in addition to leads 114 implanted within the brain of patient 112. The posture or posture changes may affect the delivery of DBS or SCS therapy to patient 112 for the treatment of any type of bioelectrical disorder, and may also be used to detect patient sleep, as described herein.

[0089] Additionally, changes of the posture of a patient 112 may cause pressure changes with the cerebrospinal fluid (CSF) of the patient. Consequently, sensors may include pressure sensors coupled to one or more intrathecal or intracerebroventricular catheters, or pressure sensors coupled to IMDs 106 wirelessly or via one of leads 114. CSF pressure changes associated with posture changes may be particularly evident within the brain of the patient, e.g., may be particularly apparent in an intracranial pressure (ICP) waveform.

[0090] Accordingly, in some examples, instead of, or in addition to, monitoring a bioelectrical signal of the patient, system 100 monitors one or more signals from sensors indicative of a magnitude of a physiological parameter of patient 112. Upon detecting that one or more signals from sensors exceed the upper bound of a homeostatic window, system 100 increases stimulation at a maximum ramp rate determined by system 100 until one or more signals from sensors return to within the homeostatic window, or until the magnitude of the electrical stimulation reaches an upper limit of a therapeutic window determined by system 100. Similarly, upon detecting that one or more signals from sensors falls below the lower bound of the homeostatic window, system 100 decreases stimulation at a maximum ramp rate determined by system 100 until one or more signals from sensors return to within the homeostatic window, or until the magnitude of the electrical stimulation reaches a lower limit of a therapeutic window determined by system 100. Upon detecting that one or more signals from sensors are within the threshold of the homeostatic window, system 100 holds the magnitude of the electrical stimulation constant.

[0091] Such a system 100 for delivering aDBS to the patient by monitoring a physiological parameter may provide advantages over other techniques that use a bioelectrical signal as a threshold in that the techniques of the disclosure allow an IMD to control delivery of therapy using hysteresis. In other words, such a system 100 can be configured to use the physiological parameter (alone or in addition to a sensed bioelectric signal) of the patient to create a closed loop feedback algorithm for not only controlling the delivery of therapy, but also controlling the magnitude of the delivered therapy. Such a system may be less intrusive on the activity of a patient because system 100 adapts the stimulation to the current needs of the patient, and thus may reduce the side effects that the patient experiences.Docket No.: A0013259W001 / 1123-863W001

[0092] In some circumstances, system 100, as described herein, may deliver, based on the upper and lower threshold of the homeostatic window, a lower magnitude of electrical stimulation than patient 112 requires to prevent breakthrough of his or her symptoms. For example, a patient receiving therapy from an IMD 106 that controls delivery of electrical stimulation therapy using the homeostatic window may, in certain circumstances, experience results that are less optimal than if the patient received continuous electrical stimulation therapy at a maximum therapy magnitude. To prevent these occurrences, system 100 may determine a value for the at least one electrical stimulation parameter as defined by the homeostatic window, as described above. Further, the IMD 106 of system 100 may increase the value for the at least one electrical stimulation parameter by a bias amount greater than the determined magnitude defined by the homeostatic window so as to further prevent breakthrough of the symptoms of patient 112. Thus, system 100 may avoid delivering electrical stimulation therapy that is of a magnitude that may be insufficient for prevention of symptom breakthrough.

[0093] The architecture of system 100 illustrated in FIG. 1 is shown as an example. The techniques as set forth in this disclosure may be implemented in the example system 100 of FIG. 1, as well as other types of systems not described specifically herein. Nothing in this disclosure should be construed so as to limit the techniques of this disclosure to the example architecture illustrated by FIG. 1. In some examples, the functionality assigned to IMD 106 and / or programmer 104 may be performed by other devices, such as a networked server, remote computing device, or other device of a digital health system, that may be in communication with IMD 106. These devices of the digital health system can receive information from IMD 106 (e.g., sensed data and / or stimulation parameters) and programmer 104 (e.g., patient or clinician input such as indications of symptoms or changes to therapy parameters), and IMD 106 can receive instructions and / or any other data from other devices of the digital health system.

[0094] FIG. 2 is a block diagram of the example IMD 106 of FIG. 1 configured for delivering deep brain stimulation therapy, which may include aDBS therapy, and / or monitoring electrical signals or other signals from the patient. In the example shown in FIG. 2, IMD 106 includes processing circuitry 210, memory 211, stimulation generator 202, sensing module 204, switch module 206, telemetry module 208, sensor 212, and power source 220. Each of these modules may be or include electrical circuitry configured to perform the functions attributed to each respective module. For example, processing circuitry 210 may include one or more processors part of the processing circuitry, switch module 206 may include switch circuitry, sensing module 204 may include sensing circuitry, stimulation generator 202 may include stimulation generation circuitry, and telemetry module 208 may include telemetry circuitry. Switch module 204 may not be necessary for multiple current source and sink configurations in which each current sourceDocket No.: A0013259W001 / 1123-863W001 and sink are directly connected to each electrode, but may be connected or disconnected via a respective switch. Memory 211 may include any volatile or non-volatile media, such as a random-access memory (RAM), read only memory (ROM), non-volatile RAM (NVRAM), electrically erasable programmable ROM (EEPROM), flash memory, and the like. Memory 211 may store computer-readable instructions that, when executed by processing circuitry 210, cause IMD 106 to perform various functions. Memory 211 may be a storage device or other non- transitory medium.

[0095] In the example shown in FIG. 2, memory 211 stores therapy programs 214 and sense electrode combinations and associated stimulation electrode combinations 218 in separate memories within memory 211 or separate areas within memory 211. Each stored therapy program 214 defines a particular set of electrical stimulation parameters (e.g., a therapy parameter set), such as a stimulation electrode combination, electrode polarity, current or voltage amplitude, pulse width, and pulse rate. In some examples, individual therapy programs may be stored as a therapy group, which defines a set of therapy programs with which stimulation may be generated. The stimulation signals defined by the therapy programs of the therapy group may be delivered together on an overlapping or non-overlapping (e.g., time-interleaved) basis. Therapy programs 214 may also store adaptive stimulation parameters that define adaptive stimulation, such as one or more thresholds for a homeostatic window and / or one or more limits for a therapeutic window. Processing circuitry 210 may directly change and / or update any of these parameter values based on commands from programmer 104, for example.

[0096] Sense and stimulation electrode combinations 218 stores sense electrode combinations and associated stimulation electrode combinations. As described above, in some examples, the sense and stimulation electrode combinations may include the same subset of electrodes 116, 118, a housing of IMD 106 functioning as an electrode, or may include different subsets or combinations of such electrodes. Thus, memory 211 can store a plurality of sense electrode combinations and, for each sense electrode combination, store information identifying the stimulation electrode combination that is associated with the respective sense electrode combination. The associations between sense and stimulation electrode combinations can be determined, e.g., automatically by processing circuitry 210. In some examples, corresponding sense and stimulation electrode combinations may comprise some or all of the same electrodes. In other examples, however, some or all of the electrodes in corresponding sense and stimulation electrode combinations may be different. For example, a stimulation electrode combination may include more electrodes than the corresponding sense 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 than theDocket No.: A0013259W001 / 1123-863W001 tissue site closest to the corresponding sense electrode combination but is within the same region, e.g., the thalamus, of brain 120 in order to mitigate any irregular oscillations or other irregular brain activity within the tissue site associated with the sense electrode combination.

[0097] Stimulation generator 202, under the control of processing circuitry 210, generates stimulation signals for delivery to patient 112 via selected combinations of electrodes 116, 118. An example range of electrical stimulation parameters believed to be effective in DBS to manage a movement disorder of patient include:

[0098] 1. Pulse Rate, i.e., Frequency: between approximately 1 Hertz and approximately 500Hertz, such as between approximately 40 to 185 Hertz or such as approximately 140 Hertz.

[0099] 2. In the case of a voltage controlled system, Voltage Amplitude: between approximately 0.1 volts and approximately 50 volts, such as between approximately 2 volts and approximately 3 volts.

[0100] 3. In the alternative case of a current controlled system, Current Amplitude: between approximately 0.2 milliamps to approximately 100 milliamps, such as between approximately 1.3 milliamps and approximately 2.0 milliamps.

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

[0102] Accordingly, in some examples, stimulation generator 202 generates electrical stimulation signals in accordance with the electrical stimulation parameters noted above, subject to application of the upper and lower threshold of a therapeutic window to one or more of the parameters, such that an applicable parameter resides within the range prescribed by the window. Other ranges of therapy parameter values may also be useful and may depend on the target stimulation site within patient 112. While stimulation pulses are described, stimulation signals may be of any form, such as continuous-time signals (e.g., sine waves) or the like.

[0103] Processing circuitry 210 may include fixed function processing circuitry and / or programmable processing circuitry, and may comprise, for example, any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), discrete logic circuitry, or any other processing circuitry configured to provide the functions attributed to processing circuitry 210 herein may be embodied as firmware, hardware, software or any combination thereof. Processing circuitry 210 may control stimulation generator 202 according to therapy programs 214 stored in memory 211 to apply particular stimulation parameter values specified by one or more of programs, such as voltage amplitude or current amplitude, pulse width, or pulse rate.Docket No.: A0013259W001 / 1123-863W001

[0104] In the example shown in FIG. 2, 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. Processing circuitry 210 also controls switch module 206 to apply the stimulation signals generated by stimulation generator 202 to selected combinations of electrodes 116, 118. In particular, switch module 204 may couple stimulation signals to selected conductors within leads 114, which, in turn, deliver the stimulation signals across selected electrodes 116, 118. Switch module 206 may be a switch array, switch matrix, multiplexer, or any other type of switching module configured to selectively couple stimulation energy to selected electrodes 116, 118 and to selectively sense bioelectrical brain signals with selected electrodes 116, 118. Hence, stimulation generator 202 is coupled to electrodes 116, 118 via switch module 206 and conductors within leads 114. In some examples, however, IMD 106 does not include switch module 206.

[0105] Stimulation generator 202 may be a single channel or multi-channel stimulation generator. In particular, 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 multiple stimulation pulses at a given time via multiple electrode combinations. In some examples, however, stimulation generator 202 and switch module 206 may be configured to deliver multiple channels on a time-interleaved basis (e.g., pulses from one channel are at least partially alternating with at least some pulses from another channel). For example, switch module 206 may serve to time divide the output of stimulation generator 202 across different electrode combinations at different times to deliver multiple programs or channels of stimulation energy to patient 112. Alternatively, stimulation generator 202 may comprise multiple voltage or current sources and sinks that are coupled to respective electrodes to drive the electrodes as cathodes or anodes. In this example, IMD 106 may not require the functionality of switch module 206 for time-interleaved multiplexing of stimulation via different electrodes.

[0106] Electrodes 116, 118 on respective leads 114 may be constructed of a variety of different designs. For example, one or both of leads 114 may include two or more electrodes at each longitudinal location along the length of the lead, such as multiple electrodes at different perimeter locations around the perimeter of the lead at each of the locations A, B, C, and D. On one example, the electrodes may be electrically coupled to switch module 206 via respective wires that are straight or coiled within the housing the lead and run to a connector at the proximal end of the lead. In another example, each of the electrodes of the lead may be electrodes deposited on a thin film. The thin film may include an electrically conductive trace for each electrode that runs the length of the thin film to a proximal end connector. The thin film may thenDocket No.: A0013259W001 / 1123-863W001 be wrapped (e.g., a helical wrap) around an internal member to form the lead 114. These and other constructions may be used to create a lead with a complex electrode geometry.

[0107] Although sensing module 204 is incorporated into a common housing with stimulation generator 202 and processing circuitry 210 in FIG. 2, in other examples, sensing module 204 may be in a separate housing from IMD 106 and may communicate with processing circuitry 210 via wired or wireless communication techniques. Example bioelectrical brain signals include, but are not limited to, a signal generated from 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 with respect to brain 120.

[0108] Sensor 212 may include one or more sensing elements that sense values of a respective patient parameter. For example, sensor 212 may include one or more accelerometers, optical sensors, chemical sensors, temperature sensors, pressure sensors, or any other types of sensors. Sensor 212 may output patient parameter values that may be used as feedback to control delivery of therapy. IMD 106 may include additional sensors within the housing of IMD 106 and / or coupled via one of leads 114 or other leads. In addition, IMD 106 may receive sensor signals wirelessly from remote sensors via telemetry module 208, for example. In some examples, one or more of these remote sensors may be external to patient (e.g., carried on the external surface of the skin, attached to clothing, or otherwise positioned external to the patient). Processing circuitry 210 may identify and / or store patient events according to signals from sensor 212.

[0109] Telemetry module 208 supports wireless communication between IMD 106 and an external programmer 104 or another computing device (such as a device of the digital health system) under the control of processing circuitry 210. Processing circuitry 210 of IMD 106 may receive, as updates to programs, values for various stimulation parameters such as magnitude and electrode combination, from programmer 104 via telemetry module 208. The updates to the therapy programs may be stored within therapy programs 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, may accomplish communication by radiofrequency (RF) communication techniques. In addition, telemetry module 208 may communicate with external medical device programmer 104 via proximal inductive interaction of IMD 106 with programmer 104. Accordingly, telemetry module 208 may send information to external programmer 104 on a continuous basis, at periodic intervals, or upon request from IMD 106 or programmer 104.

[0110] Power source 220 delivers operating power to various components of IMD 106. Power source 220 may include a small rechargeable or non-rechargeable battery and a powerDocket No.: A0013259W001 / 1123-863W001 generation circuit to produce the operating power. Recharging may be accomplished through proximal inductive interaction between an external charger and an inductive charging coil within IMD 220. In some examples, power requirements may be small enough to allow IMD 220 to utilize patient motion and implement a kinetic energy-scavenging device to trickle charge a rechargeable battery. In other examples, traditional batteries may be used for a limited period of time.

[0111] According to the techniques of the disclosure, processing circuitry 210 of IMD 106 delivers, electrodes 116, 118 interposed along leads 114 (and optionally switch module 206), electrical stimulation therapy to patient 112. The aDBS therapy is defined by one or more therapy programs 214 having one or more parameters stored within memory 211 (and may specify the adaptive mode and corresponding one or more thresholds). For example, the one or more parameters may include a current amplitude (for a current-controlled system) or a voltage amplitude (for a voltage-controlled system), a pulse rate or frequency, and a pulse width, or quantity of pulses per cycle. The collection of one or more of these parameter values may define a parameter set that defines each therapy program. In examples where the electrical stimulation is delivered according to a “burst” of pulses, or a series of electrical pulses defined by an “on- time” and an “off-time,” the one or more parameters may further define one or more of a number of pulses per burst, an on-time, and an off-time. In one example, the therapeutic window defines an upper limit and / or a lower limit for a voltage amplitude of the electrical stimulation therapy. In another example, the therapeutic window defines an upper limit and / or a lower limit for a current amplitude of the electrical stimulation therapy. In particular, a parameter of the electrical stimulation therapy, such as voltage or current amplitude, is constrained to a therapeutic window having an upper limit and a lower limit, such that the voltage or current amplitude may be adjusted provided the amplitude remains greater than or equal to the lower limit and less than or equal to the upper limit. It is noted that a single limit may be used in some examples.

[0112] In one example, processing circuitry 210, via electrodes 116, 118 of IMD 106, monitors the behavior of a signal of patient 112 that correlates to one or more symptoms of a disease of patient 112 within a homeostatic window. Processing circuitry 210, via electrodes 116, 118, delivers to patient 112 aDBS and may adjust one or more parameters defining the electrical stimulation within a parameter range defined by lower and upper thresholds of a therapeutic window based on the activity of the sensed signal within the homeostatic window.

[0113] In one example, the signal is a bioelectrical signal (e.g., a LFP signal) within the Beta frequency band of brain 120 of patient 112. The signal within the Beta frequency band of patient 112 may correlate to one or more symptoms of Parkinson’s disease in patient 112. Generally speaking, bioelectrical signals within the Beta frequency band of patient 112 may beDocket No.: A0013259W001 / 1123-863W001 approximately proportional to the severity of the symptoms of patient 112. For example, as tremor induced by Parkinson’s disease increases, one or more of electrodes 116, 118 detect an increase in the magnitude of bioelectrical signals within the Beta frequency band of patient 112.

[0114] Similarly, as tremor induced by Parkinson’s disease decreases, processing circuitry 210, via the one or more of electrodes 116, 118, detects a decrease in the magnitude of the bioelectrical signals within the Beta frequency band of patient 112. In another example, the signal is a bioelectrical signal within the Gamma frequency band of brain 120 of patient 112. The signal within the Gamma frequency band of patient 112 may also correlate to one or more side effects of the electrical stimulation therapy. However, in contrast to bioelectrical signals within the Beta frequency band, generally speaking, bioelectrical signals within the Gamma frequency band of patient 112 may be approximately inversely proportional to the severity of the side effects of the electrical stimulation therapy. For example, as side effects due to electrical stimulation therapy increase, processing circuitry 210, via the one or more of electrodes 116, 118, detects a decrease in the magnitude of the signal within the Gamma frequency band of patient 112. Similarly, as side effects due to electrical stimulation therapy decrease, processing circuitry 210, via the one or more of electrodes 116, 118, detects an increase in the magnitude of the signal within the Gamma frequency band of patient 112.

[0115] In response to detecting that the signal of the patient, e.g., a sensed bioelectrical signal, has deviated from the homeostatic window, processing circuitry 210 dynamically adjusts the magnitude of the one or more parameters of the electrical stimulation therapy such as, e.g., pulse current amplitude or pulse voltage amplitude, to drive the signal of the patient back into the homeostatic window. For example, wherein the signal is a bioelectrical signal within the Beta frequency band of brain 120 of patient 112, processing circuitry 210, via the one or more of electrodes 116, 118, monitors the Beta magnitude of patient 112. Upon detecting that the Beta magnitude of patient 112 exceeds the upper bound of the homeostatic window, processing circuitry 210 increases a magnitude of the electrical stimulation delivered via electrodes 116, 118 at a maximum ramp rate, e.g., determined automatically or by the clinician until the magnitude of the bioelectrical signal within the Beta band falls back to within the homeostatic window, or until the magnitude of the electrical stimulation reaches an upper limit of a therapeutic window determined by system 100 (FIG. 1). Similarly, upon detecting that the Beta magnitude of patient 112 falls below the lower bound of the homeostatic window, processing circuitry 210 decreases stimulation magnitude at a maximum ramp rate determined by system 100 until the Beta magnitude rises back to within the homeostatic window, or until the magnitude of the electrical stimulation reaches a lower limit of a therapeutic window determined by system 100. Upon detecting that the Beta magnitude is presently within the threshold of the homeostatic window orDocket No.: A0013259W001 / 1123-863W001 has returned to within the threshold of the homeostatic window, processing circuitry 210 holds the magnitude of the electrical stimulation constant. In other examples, processing 210 may automatically determine the ramp rate at which stimulation parameters are adjusted to cause the brain signal to fall back within the target range. The ramp rate may be selected based on prior data indicating general patient comfort or comfort or preferences of the specific patient.

[0116] In some examples, processing circuitry 210 continuously measures the signal in real time. In other examples, processing circuitry 210 periodically samples the signal according to a predetermined frequency or after a predetermined amount of time. In some examples, processing circuitry 210 periodically samples the signal at a frequency of approximately 150 Hertz.

[0117] Furthermore, processing circuitry 210 delivers electrical stimulation therapy that is constrained by an upper limit and a lower limit of a therapeutic window. In some examples, values defining the therapeutic window are stored within memory 211 of IMD 106. For example, in response to detecting that the brain signal has deviated from the homeostatic window, processing circuitry 210 of IMD 106 may adjust one or more parameters of the electrical stimulation therapy to provide responsive treatment to patient 112. For example, in response to detecting that the signal has exceeded an upper threshold of the homeostatic window and prior to delivering the electrical stimulation therapy, processing circuitry 210 increases an amplitude of stimulation (e.g., but not above the upper limit) in order to bring the signal back down below the upper threshold. For example, in a voltage-controlled system wherein the clinician has set the upper limit of the therapeutic window to be 3 Volts, processing circuitry 210 can increase the voltage amplitude to values no greater than 3 Volts in an attempt to decrease the brain signal below the upper threshold.

[0118] In another example, in response to detecting that the signal has fallen below a lower threshold of the homeostatic window and prior to delivering the electrical stimulation therapy, processing circuitry 210 decreases the voltage amplitude, for example, but not lower than the magnitude of the lower limit. For example, in the above voltage-controlled system wherein the clinician has set the lower bound of the therapeutic window to be 1.2 Volts, processing circuitry 210 can decrease the voltage amplitude down to no lower than 1.2 Volts in an attempt to raise the brain signal back above the lower threshold and into the homeostatic window. Thus, processing circuitry 210 of IMD 106 may deliver aDBS to patient 112 wherein the one or more parameters defining the aDBS is within the therapeutic window defined by a lower and upper limit for the parameter.

[0119] In the foregoing example, the limit of the therapeutic window is inclusive (i.e., the upper and lower limit are valid values for the one or more parameters). However, in other examples, the limit of the therapeutic window is exclusive (i.e., the upper and lower limits are notDocket No.: A0013259W001 / 1123-863W001 valid values for the one or more parameters). In such an example of an exclusive therapeutic window, processing circuitry 210 instead sets the adjustment to the one or more parameters to be the next highest valid value (in the case of an adjustment potentially exceeding the upper limit) or the next lowest valid value (in the case of an adjustment potentially exceeding the lower limit).

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

[0121] In another example, processing circuitry 210, via telemetry module 208 and from external programmer 104, receives instructions to adjust one or more limits of the therapeutic window. For example, such instructions may be in response to patient feedback on the efficacy of the electrical stimulation therapy, or in response to one or more sensors that have detected a signal of the patient. Such signals from sensors may include bioelectrical signals, such as a signal within the Beta frequency band or signal within the Gamma frequency band of brain 120 of patient 112, or physiological parameters and measurements, such as a signal indicating one or more of a patient activity level, posture, and respiratory function. Further, such signals from sensors may indicate a lack of reduction of one or more symptoms of the patient 112, such as tremor or rigidity or the presence of side effects due to electrical stimulation therapy, such as paresthesia. In response to these instructions, processing circuitry 210 may adjust one or more thresholds of the homeostatic window. For example, processing circuitry 210 may adjust the magnitude of the upper threshold, the lower threshold, or shift the overall position of the homeostatic window such that the threshold, defined by the homeostatic window, for adjustment of the one or more parameters of electrical stimulation, is itself adjusted. Thereafter, processing circuitry 210, via electrodes 116 and 118, delivers the adjusted electrical stimulation to patient 112.

[0122] FIG. 3 is a block diagram of the external programmer 104 of FIG. 1. Although programmer 104 may generally be described as a hand-held device, programmer 104 may be a larger portable device or a more stationary device. In some examples, programmer 104 may be referred to as a tablet computing device. In addition, in other examples, programmer 104 may be included as part of an external charging device or include the functionality of an externalDocket No.: A0013259W001 / 1123-863W001 charging device. Programmer 104 may be part of the digital health system that can distribute collected patient information (e.g., sensed data and / or received user input) to other devices that can analyze the information and generate a user interface for presenting and comparing information as part of patient therapy. As illustrated in FIG. 3, programmer 104 may include a processing circuitry 310, memory 311, user interface 302, telemetry module 308, and power source 320. Memory 311 may store instructions that, when executed by processing circuitry 310, cause processing circuitry 310 and external programmer 104 to provide the functionality ascribed to external programmer 104 throughout this disclosure. Each of these components, or modules, may include electrical circuitry that is configured to perform some or all of the functionality described herein. For example, processing circuitry 310 may include processing circuitry configured to perform the processes discussed with respect to processing circuitry 310.

[0123] In general, programmer 104 comprises any suitable arrangement of hardware, alone or in combination with software and / or firmware, to perform the techniques attributed to programmer 104, and processing circuitry 310, user interface 302, and telemetry module 308 of programmer 104. In various examples, programmer 104 may include one or more processors, which may include fixed function processing circuitry and / or programmable processing circuitry, as formed by, for example, one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. Programmer 104 also, in various examples, may include a memory 311, such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, a hard disk, a CD-ROM, comprising executable instructions for causing the one or more processors to perform the actions attributed to them. Moreover, although processing circuitry 310 and telemetry module 308 are described as separate modules, in some examples, processing circuitry 310 and telemetry module 308 may be functionally integrated with one another. In some examples, processing circuitry 310 and telemetry module 308 correspond to individual hardware units, such as ASICs, DSPs, FPGAs, or other hardware units.

[0124] Memory 311 (e.g., a storage device) may store instructions that, when executed by processing circuitry 310, cause processing circuitry 310 and programmer 104 to provide the functionality ascribed to programmer 104 throughout this disclosure. For example, memory 311 may include instructions that cause processing circuitry 310 to obtain a parameter set from memory, select one or more parameters for electrical stimulation or adaptive stimulation according to sensed signals, or receive user input and send a corresponding command to IMD 104, or instructions for any other functionality. In addition, memory 311 may include a plurality of programs, where each program includes a parameter set that defines stimulation therapy.Docket No.: A0013259W001 / 1123-863W001

[0125] User interface 302 may include a button or keypad, lights, a speaker for voice commands, a display, such as a liquid crystal (LCD), light-emitting diode (LED), or organic light-emitting diode (OLED). In some examples the display may be a touch screen. User interface 302 may be configured to display any information related to the delivery of stimulation therapy, identified patient behaviors, sensed patient parameter values, automatically selected parameters, prompts for user input regarding stimulation parameters or adaptive stimulation parameters, patient behavior criteria, or any other such information. User interface 302 may also receive user input via user interface 302. The user input may be, for example, in the form of pressing a button on a keypad or selecting an icon from a touch screen. The user input may indicate that a patient event has occurred, and may, in some examples, indicate the type of patient event (e.g., a symptom occurred, a side effect occurred, or any other type of patient event). In some examples, processing circuitry 310 may time stamp this patient event to correlate with sensed signals later retrieved from IMD 106. In some examples, processing circuitry 310 may transmit the indication of the patient event to IMD 106 to associate the patient event and store sensed signals and / or immediately request the sensed signals from IMD 106 for association with the patient event and storage in memory 311 for further processing. User interface 302 may refer to hardware configured to present information to the user and / or receive input from the user. In some examples, processing circuitry 310 directly controls this hardware. In other examples, processing circuitry 310 may communicate with drive hardware that controls hardware of user interface 302. In some examples, user interface 302 may include display and / or interactive display configurations as described herein.

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

[0127] Examples of local wireless communication techniques that may be employed to facilitate communication between programmer 104 and IMD 106 include RF communication according to the 802.11 or Bluetooth specification sets or other standard, inductive telemetry, or any proprietary telemetry protocols. In this manner, other external devices may be capable of communicating with programmer 104 without needing to establish a secure wireless connection.Docket No.: A0013259W001 / 1123-863W001As described herein, telemetry module 308 may be configured to transmit a spatial electrode movement pattern or other stimulation parameter values to IMD 106 for delivery of stimulation therapy.

[0128] According to the techniques of the disclosure, in some examples, processing circuitry 310 of external programmer 104 defines the parameters of a homeostatic therapeutic window, stored in memory 311, for delivering aDBS to patient 112. In one example, processor 311 of external programmer 104, via telemetry module 308, issues commands to IMD 106 causing IMD 106 to deliver electrical stimulation therapy via electrodes 116, 118 via leads 114.

[0129] The following examples illustrate various user interfaces and techniques for managing the sensing of physiological signals, such as brain signals, programming adaptive stimulation therapy, and managing electrical stimulation as described herein. Programmer 104, or another external computing device, may output the user interfaces and screens described herein. The example user interface screens may be separately presented or selectable in any order, or programmer 106 (for example) may present each screen in order as part of one or more automated programming processes to assist the user through the programming process for setting up or adjusting adaptive stimulation therapy. User input may be prompted at various times, either to select parameter values or to confirm automatically selected parameter values. In some examples, programmer 106 may perform each step automatically and present the user with fully automated and selected parameters at the end of the process. The user may confirm the parameter values or review one or more of the parameter values using each respective screen of the user interface as needed to customize the stimulation therapy, which may include adaptive stimulation therapy such as aDBS.

[0130] FIG. 4 is a block diagram illustrating an example system 1400 that includes an external device, such as a server 482, and one or more computing devices 484A-484N, that are coupled to IMD 106 and external programmer 104 shown in FIG. 1 via a network 486. System 1400 may be an example of a digital health system that supports a digital health platform that collects, analyzes, and presents information related to the treatment of one or more patients. IMD 106 may use its telemetry circuit 88 to communicate with external programmer 104 via a first wireless connection, and to communicate with an access point 488 via a second wireless connection. In some examples, system 400 may include additional devices. For example, system 400 may also include communication device 402 which may be an intermediary device that is configured to communicate with IMD 106 via one communication protocol and communicate with programmer 104 and / or network 486 with a different communication protocol. Communication device 402 may provide other functionality, such as recharging functionality for a rechargeable battery of IMD 106. Communication device 402 may be referred to as anDocket No.: A0013259W001 / 1123-863W001“intermediate device” that can act to transfer data between IMD 106 and network 486 and other servers or computing devices.

[0131] As described herein, system 400 may be a part of a digital health platform that can share information between devices and enable certain functionality, such as sharing information sensed or otherwise obtained by IMD 106 and / or programmer 104 to other remote computing devices in addition to transferring updated sensing and / or programming instructions from remote computing devices such as server 482 and / or computing devices 484A-484N back to programmer 104 and / or IMD 106. System 400 may be configured to support a user interface that presents this information for user viewing, analyzes data for comparison and understanding of changes over time, and receives user updates to one or more parameters that define therapy for the patient (e.g., medication regimen and / or stimulation therapy). The user interface provided by system 400 can also be used to track a plurality of patients as needed by a clinician, clinic, or any other health care organization.

[0132] In the example of FIG. 4, access point 488, external programmer 104, server 482, and computing devices 484A-484N are interconnected, and able to communicate with each other, through network 486. In some cases, one or more of access point 488, external programmer 104, server 482, and computing devices 484A-484N may be coupled to network 486 through one or more wireless connections. IMD 106, external programmer 104, server 1482, and computing devices 484A-484N may each comprise one or more processors, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic circuitry, or the like, that may perform various functions and operations, such as those described in this disclosure.

[0133] Access point 488 may comprise a device, such as a home monitoring device, that connects to network 486 via any of a variety of connections, such as telephone dial-up, digital subscriber line (DSL), cable modem connections, fiber optic communications, etc. In other examples, access point 488 may be coupled to network 486 through different forms of connections, including wired or wireless connections.

[0134] During operation, IMD 106 may collect and store various forms of data. For example, IMD 106 may collect sensed electrical signals and / or event data during therapy delivery that indicate therapy efficacy and / or disease state of patient 12. In some cases, IMD 106 may directly analyze the collected data to evaluate the patient 12, such as identifying events and / or sensed data. In other cases, however, IMD 106 may send stored data relating to events and / or other sensed data to external programmer 104 and / or server 482, either wirelessly or via access point 488 and network 486, for remote processing and analysis. For example, IMD 106 may transmit sensed information, such as event data, to computing device 484A, and computingDocket No.: A0013259W001 / 1123-863W001 device 484A can evaluate the sensed information and generated updated stimulation parameters, event data, or other information pertaining to the patient.

[0135] In some cases, server 482 may be configured to provide a secure storage site for archival of information that has been collected from IMD 106, external programmer 104, or any other devices of system 400. Network 486 may comprise a local area network, wide area network, or global network, such as the Internet. In some cases, external programmer 104 or server 482 may assemble sensed data, event data, or other therapy information in web pages or other documents for viewing by trained professionals, such as clinicians, via viewing terminals associated with computing devices 484A-484N. In this manner, system 400 functioning as a digital health platform may enable cloud-based functionality for any of the processes and / or user interactions described herein.

[0136] For example, a user may be able to log into the digital health platform of system 1400 via one or more devices such as any of computing devices 484A-484N. In one example, a user may log into the digital health platform using computing device 484A. The user may interact with a user interface (e.g., user interface 500 described herein) that is displayed via an internet browser application or other specific software application. For example, screens of user interface 500 may be displayed. With respect to the functionality described herein, the platform may provide the user with information related to event data and / or therapy, such as which hemisphere of the brain is associated with a symptom or side effect that has occurred or is occurring, and the LFP values of sensed bioelectric signal information associated with that symptom, side effect, or related event. In some examples, the user interface provided via the digital health platform may include information such as graphs, text, or other interactive elements. The user interface may then be configured to receive user input approving a suggested updated threshold(s) according to the LFP values or adjusting the threshold(s). In some examples, the user interface may present additional information regarding the one or more thresholds. For example, the user interface may present information that setting a threshold within the range suggested by the LFP value(s) may reduce an occurrence of an event because adaptive stimulation therapy will be adjusted based on the updated threshold(s). System 400 may then transmit the updated threshold(s) back to IMD 106 via network 486.

[0137] Furthermore, although the disclosure is described with respect to DBS therapy, such techniques may be applicable to IMDs that convey other therapies in which sensed data and event data information is important, such as, e.g., spinal cord stimulation (SCS), pelvic floor stimulation, gastric stimulation, occipital stimulation, functional electrical stimulation, and the like. Also, in some aspects, techniques for evaluating posture state information, as described in this disclosure, may be applied to IMDs that provide other therapy (e.g., drug pumps) or IMDsDocket No.: A0013259W001 / 1123-863W001 that are generally dedicated to sensing or monitoring and do not include stimulation or other therapy components.

[0138] FIGS. 5-15 are example screens of a user interface for a digital health platform as described herein. The digital health platform refers to the product that includes the digital health system (e.g., at least of the components of system 400 of FIG. 4) and the user interface generated and displayed that enables users to interact with the information for one or more patients. FIGS. 5-15 are just some examples, and elements of each screen of user interface 500 may be used in different combinations with other screens or used in multiple aspects. Furthermore, some elements of a single screen may be presented together at the same screen as enabled by the display size of the display device used to present the information. For example, a user may scroll through the screen to view various elements of a single screen if the display is not large enough or does not have the appropriate resolution to show the information together. System 400 will generally be described with respect to the functionality of user interface 500, but one or more devices may contribute to the functionality. For example, computing device 484A, and the processing circuitry and display device of computing device 484A may generate and display user interface 500. However, any other device of system 400 may be configured to similarly present user interface 500, analyze information, and / or receive user input, or contribute to any functions in a distributed computing environment, for example.

[0139] FIG. 5 is a conceptual diagram illustrating an example patient selection screen for a digital health platform. User interface 500 may include several different screens as the user can navigate to different functions to view sensed information, view stored data, or determine or adjust various stimulation parameter values. As shown in the example of FIG. 5, home screen 502 includes information associated with one or more patients that can be selected for further information. Each patient entry 501 provides information for a single patient. Although only one patient entry 501 is shown in home screen 502, many patients (e.g., any number of patients such as 2, 3, 4, 10, or even hundreds of patients) may be shows. Each patient entry 501 may be selectable such that system 400 can show information for that particular patient on other screens of user interface 500.

[0140] Patient entry 501 may include various information in respective fields for the patient, such as name field 506, device field 508, implant date field 510, last session field 512, impedance field 514 (indicators may be color coded for good, caution, and bad), battery status field 516 (indicators can be color coded for good, medium, and low), and estimated replacement indicator field 518 (usage can be based on actual battery usage for operation). Patient entry 501 may include other patient information such as the patient date of birth, the patient identification number, serial number of any IMD, or other information. In some examples, user interface 500Docket No.: A0013259W001 / 1123-863W001 may be configured to sort all of the patients based on any of the details or criteria listed with respect to the patient. In some examples, system 400 can generate email notifications, text notifications, or other notifications that are sent to the clinic and / or clinician of device issues, such as the need for a battery replacement. This information may be collected from programmer 104 or other devices. In some examples, patient entry 501 may also include any patient diagnoses. Download reports icon 520 may be selected, and in response, system 400 may download an offline copy of the information for all patients listed in home screen 502 to the device. In some examples, system 400 can email or otherwise notify a clinician if a battery of a patient device needs to be replaced. Search bar 504 can receive text input from a user to search for a particular patient or group of patients. Upon receiving input to search bar 504, system 400 can populate screen 502 with the list of patients satisfying the search criteria. Upon selection of patient entry 501, system 400 can present information specific to the selected patient in other screens, such as screen 602 of FIG. 6 A.

[0141] FIGS. 6A, 6B, and 6C are conceptual diagrams illustrating an example screen 602 showing various received information regarding the patient. As shown in FIG. 6A. screen 602 presents a number of selectable tabs (e.g., tabs 606-620). Each of the selectable tabs can cause system 400 to present a different screen of user interface 500 that displays different types of information regarding the patient. Although the selectable tabs are shown along the left side of screen 602, user interface 500 may place the tabs at different locations. In some examples, system 500 may configure or populate the selectable tabs within screen 602 according to the therapy of the patient and according to the data available to show to the user.

[0142] System 400 can be configured to control user interface 500 to display the plurality of selectable tabs to include a variety of different tabs. These tabs may include decision record 606, timeline 608 of at least a portion of the sensed data, medication information 610, a graph 612 of spectral power for different electrode combinations, and a therapy setup page 620. Additional tabs as shown include in-clinic streaming 614 that enables the user to view sensed data and / or stimulation parameters from the medical device of the patient in real-time, history 616 that provides historical patient condition and / or programming information, and profile 618 that includes additional details regarding the patient.

[0143] Screen 602 may not be configured to present all of the information of decision record 606 at the same time, depending on the size and / or resolution of the screen that displays user interface 500. In this manner, a scroll bar may be provided that enables the user to move to different areas of screen 602, as is indicated by the different areas of screen 602 shown in FIGS. 6A, 6B, and 6C. In general, decision record 606 can provide information that the user can view for determining the treatment for the patient. Screen 602 includes add notes button 622 that,Docket No.: A0013259W001 / 1123-863W001 when selected, enables the user to add text notes regarding the patient. Assessment button 624, when selected, causes user interface 500 to enter an assessment screen for the patient in order to add various information, such as symptoms and / or severities of symptoms as shown in screens 682 of FIG. 6D and 687 of FIG. 6E.

[0144] Graph 626 includes information regarding the symptoms and severity of symptoms experienced by the patient. Location bar 628 provides selectable filters for the location of each symptom that, when selected, will filter the symptoms shown on graph 626. The items of location bar 628 can be customized by the user as desired to group various symptoms as desired by the user. Ambulatory indicator 635 indicates the period of time on graph 626 that the patient was ambulatory (e.g., at home away from the clinic and ambulatory). Ambulatory indicator 635 can include shading within graph 626 (instead of or in addition to the dotted line) to indicate when the patient was ambulatory on graph 626. In some examples, user interface 500 may receive user selection within the identified area and responsively show information associated with that time and / or symptom of graph 626. Ambulatory information used by system 400 to generate this indication of activity may be generated automatically by activity sensors of IMD 106 and / or via patient input or other input describing the patient condition. Stimulation bar 634 indicates the times when the patient received stimulation therapy during graph 626. Symptom indicators 636, 638, and 640 graphically depict the severity of respective symptoms over time. Symptom indicators 636, 638, and 640 can be color coded for easy identification and for association by color to the respective symptoms indicated in symptom legend 642. Colors may be assigned automatically or manually by the user for each symptom. In addition, user interface 500 can receive selection of each symptom in legend 642 to toggle that particular symptom on or off in graph 626. Medication icon 630 indicates when the medication regimen has changed and can be selected to show the user what medication was taken. Information icon 632 can show other information related to the patient, such as other programming changes or an event.

[0145] System 400 can be configured to receive symptom input regarding one or more patient symptom types over a period of time. Symptom input may be received via programmer 104 or other device, and may be provided via a screen such as screen 682 of FIG. 6D. The one or more patient symptom types comprise at least one of a facial expression, a postural stability, or a posture. These different symptoms may be associated with a side of the body (right or left) or without a side (e.g., axial). System 400 can also determine a medication schedule that medication is consumed by the patient and determine an ambulatory period for the patient during the period of time. System 400 can then control user interface 500 to present graph 626 including the symptom input (e.g., severity and / or presence of one or more symptoms), medication schedule (e.g., when medication should have been take or was confirmed to beDocket No.: A0013259W001 / 1123-863W001 taken), and the ambulatory period over time. The user can select copy button 644 which can, when selected, copy the information of screen 602 for pasting into another document or electronic medical record (EMR) as desired by the user. The system could also conduct a push / pull of data with EMR, such that the DEEP can pull data from the EMR and then interpret the data and apply it in specific areas where the DEEP can assess, possibly with other data to identify specific insight, i.e.. pull medications, overlay them on the daily average graph to determine medication efficacy, duration of action, etc.to assist the HCP with understanding how their medication changes have affected the patient symptoms, LFP, etc.

[0146] FIG. 6B shows screen 650, which may be a different area of screen 602 as the user scrolled down to view another area of decision record 606. Screen 650 can include a summary of any changes, such as changes to any active groups of parameters that are used for stimulation therapy. Setting button 654 can, when selected, cause user interface 500 to bring the user to another screen for viewing and / or changing stimulation parameters of one or more groups of parameters.

[0147] Screen 650 can also show medication field 656 that would indicate any changes to medication during the current session and medications button 658 that can display the current medications that the patient is taking. Notes field 660 can include any notes that the clinician added for the patient. View notes button 662 can, when selected, cause user interface 500 to show all of the notes for the patient.

[0148] FIG. 6C shows screen 670, which may be a different area of screen 602 as the user scrolled down to view another area of decision record 606. Screen 670 includes programming information for DBS therapy. Group tabs 672 show information for each program group and can be selectable to show the respective group. Programming fields 674A and 674B provide the stimulation parameters for the left and right hemispheres of the brain of the patient, respectively. For example, programming field 674A shows the electrode combination 676, stimulation parameter values 678, and sensing parameters 680.

[0149] Simulation settings 678 may include the amplitude, amplitude limits (e.g., upper and lower limits), pulse width, and frequency, etc.. Other parameters may be shown in other examples. Sensing parameters 680 indicate parameters for sensing bioelectrical signals, such as the frequency of a sensing band, and the thresholds used for aDBS (e.g., the upper and lower threshold). Simulation settings 678 and sensing parameters 680 may indicate which parameters have changed during this programming session from the last parameter values. As shown in FIG. 6C, the new values are shown as well as the difference (increased or decreased) from the previous value for that parameter. In some examples, the changed parameter values, or the differences resulting from the change, may be highlighted with respective colors to visuallyDocket No.: A0013259W001 / 1123-863W001 indicate what has changed and the magnitude. For example, increased parameters can be highlighted in blue, and decreased parameters can be heighted in purple. These are only example colors, any other colors, shading, size, and / or font could be used in other examples.

[0150] In some examples, screen 670 may accept changes to any values of stimulation settings 678 and / or sensing parameters 680. In this manner, system 400 can be configured to receive, via the user interface, user input selecting a value for one or more stimulation parameters that define subsequent brain stimulation therapy and control IMD 106 to deliver the subsequent brain stimulation therapy according to the value for the one or more stimulation parameters. For example, changing a parameter value via user interface 500 can cause system 400 to transmit the change to IMD 106 for subsequent therapy.

[0151] FIGS. 6D and 6E are conceptual diagrams illustrating different screens 682 and 687 for receiving input regarding symptoms to track and the severity of symptoms. Screens 682 and 687 may be pop-up windows over screen 602 or separate screens that can be navigated to as desired. In the example of FIG. 6D, screen 682 provides various selectable symptoms that, when selected, are highlighted as symptoms experienced by the patient. These symptoms can be groups for ease of viewing, such as the last tracked symptoms 684, axial symptoms 685, left body symptoms 686, etc. Group selector 683 can be used to select and filter the available symptoms as the user looks for symptoms experienced by the patient and should be entered. Button 681 can be selected to confirm the selected symptoms and move to screen 687. Other assessment scales may be used in other examples and correlated to respective disease states. The digital health system may present those assessments appropriate for the patient or the clinician can select desired assessments and / or create custom assessment scales for any symptoms.

[0152] As shown in FIG. 6E, screen 687 displays each selected symptom and severity inputs selectable to indicate the severity of each symptom for the patient. For example, the user can select the appropriate severity score for each of finger tapping symptom 688, freezing gait 689, hand tremor 690, etc. In other examples, the user may enter the severity score my entering text, a number, moving a slider, rotating a dial, or providing any other input indicative of the severity of the symptom. In some examples, the severity score range may be the same or different for different symptoms. Selection of button 691 will cause user interface 500 to move to the next screen, such as showing the resulting selected symptoms or returning to screen 602. The system can also accept patient symptom and severity scoring that can be input either directly into the system or through an ancillary device such as patient programmer, watch, etc.

[0153] FIG. 6F is a conceptual diagrams illustrating an example screen 693 showing various received information regarding the patient and changes that have occurred. Screen 693 may be similar to screen 602 of FIG. 6A. However, screen 693 also includes change windows 694 thatDocket No.: A0013259W001 / 1123-863W001 indicate which categories of information have changed and the extent of that change. For example, the categories may include symptom severity, average reported events, average LFP variability, and total LEDD. The changes may be shown as the magnitude of the change, the percentage of change, the prior and current values, etc. User interface 500 may show positive changes as one color (green) and negative changes as another color (red).

[0154] FIG. 6G is a conceptual diagrams illustrating an example screen 664 of user interface 500 showing various received information regarding patient therapy and recorded events for the patient. As shown in the example of FIG. 6G, screen 664 provides information regarding therapy delivered to the patient over time. Graph 695 includes LFP aggregate values 697 and stimulation aggregate values 698 for different times during a predetermined period, such as a 24-hour day. LFP aggregate values 697 may be the average sensed LFP power for a certain frequency range, and a standard deviation or other variance may be displayed as well in graph 695. Stimulation aggregate values 698 may be the average amplitude values of stimulation over the same period of time, such as the 24-hour day.

[0155] In addition, patient event indicator 696 provides an indication (e.g., via color, number, etc.) of the number of patient events that are recorded during specific times of the predetermined period of graph 695. This indicator may function as a heat map for one or more types of patient events. In this manner, patient event indicator 696 can indicate correlations between increased frequency of patient events and LFP aggregate values 697 and / or stimulation aggregate values 698. Example patient events may be IMD sensed events, patient indicated events, or other events associated with patient symptoms (e.g., falls, pain, dyskinesia, etc.). Patient event indicator 696 may be calculated based on an aggregate number of patient events for a repeatable duration (e.g., one hour) during a period of time (e.g., a 24-hour period of time). In this manner, each repeatable duration can be associated with the patient events that occurred during each repeatable duration such as the system can generate an indication of the number of patient events that occur during each repeatable duration. Patient events summary 699 can also show the percentage of total events for different types of events for a period of time. Patient events summary 699 may indicate the total number of events for each type of events, the number of events for different periods, a trend indicator showing whether that type of event is increasing or decreasing in occurrence, or any other type of information.

[0156] In some examples, user interface 500 can display all patient events from all visits, or periods of time. Each of the patient events that were recorded may also be associated with an LFP snapshot, which is a portion of LFP sensed data for a period of time corresponding to the patient event. In some examples, screen 664 may present a medication indicator that indicates the times of day and / or events that are associated with the patient taking medication. The patientDocket No.: A0013259W001 / 1123-863W001 event can also indicate information associated with the medication schedule, such as the medication being too high, too low, there were breakthrough symptoms, etc. In this manner, graph 695 of screen 664 can include all of this information - sensed data, stimulation amplitude, patient events, medication consumption, etc. User interface 500 may present one or more toggles that, when selected by a user, toggles any one of these different types of data on or off from screen 664 to facilitate insight and ease of use. In some examples, the period of time of data shown in screen 664 may be user selected and correspond to specific date ranges, different periods between clinic visits, specific ambulatory periods, etc.

[0157] In some examples, user interface 500 may enable a user to explore an individual LFP snapshot information (e.g., frequency slider, highlighting magnitude of sensed LFP signals along the trace) stored for a specific patient event. The system may present the LFP snapshot information for any patient events when selected from patient event indicator 696, the events within patient event summary 699, or any other indicator of the patient event presented in user interface 500. In some examples, user interface 500 may enable a user to filter and / or select patient events may the name of the specific patient type of event.

[0158] Patient event counts, such as shown in patient event summary 699, can be provided for any selected period of time. The patient event count may be a total count for all types of patient events, for one specific type of patient event, or for groups of types of events. In some examples, patient event summary 699 may be presented for a period that the patient is ambulatory and undergoing typical daily routines. The patient events may be shown as a pie chart, scatter plot, or have daily average views. In some examples, user interface 500 can accept user selection of a specific patient event or other data point and move to a timeline view of the data for the patient associated with that patient event. In this manner, user interface 500 can enable the user to quickly navigate between screens by clicking trough different data instead of explicitly choosing a different screen.

[0159] In some examples, the system can store LFP changes before and / or after the patient event is marked by the user (or sensed by the system). For an example, up to an hour (or longer) before and after the patient event may have sensed data stored for review. The system may specify the period of time before and / or after the patient event to store LFP data based on the type of the patient event (e.g., a seizure may be longer periods of time and tremor may be shorter periods of time). User interface 500 may accept user input selecting the period of time to store LFP data for each patient event. In some examples, the patient events may be triggered by an LFP signature (e.g., power or time domain), scheduled events (e.g., patient awake / sleep, medication schedule, device implanted, etc.), data derived events (e.g., when medication should have been taken, patient exercise, when the patient falls asleep, other activity).Docket No.: A0013259W001 / 1123-863W001

[0160] In some examples, user interface 500 may be configured to predict or derive when medication was taken by the patient based on sensed LFP signals. In this manner, user interface 500 may be configured to automatically determine medication schedule without needing the patient to manually enter when medication was selected. The system may predict medication consumption based on changes to the LFP signals indicative of medication effectiveness. User interface 500 may determine patient compliance to a medication schedule based on this sensed medication, automatically change delivered stimulation, suggest changes to stimulation or medication, etc.

[0161] In some examples, user interface 500 can present different correlations between data. For examples, screen 664 can filter or determine those events that occurred during specific stimulation settings, such as low or how stimulation amplitude, or when medication consumption was on or off for the patient. Patient events may be good or bad. User interface 500 may compare and / or overlap good events with bad events for the patient. User interface 500 can also display the center frequency (or other characteristic of sensed LFP data) for the different good or bad patient events in order to identify different frequencies of the LFP sensed data corresponding to various different events.

[0162] User interface 500 may also show additional information related to the leads of the patient. For example, user interface 500 can show a historical or longitudinal view of impedance values over time for each electrode and / or lead implanted within the patient. A comparison feature can show the different impedance data sets for different respective time periods. In some examples, user interface 500 can show a simple historical view of the leads for clinicians to know when leads, extensions, electrodes are starting to show signs of wear and tear. For example, this historical view can indicate the trend in impedance changes, rate of change, or even a prediction of when the leads will no longer be acceptable based on the trend in measured impedance for one or more electrodes on a lead. In some examples, this historical impedance data can be displayed in the stimulation screen so that when the clinician is programming the patient, the clinician can easily see which electrodes are not functional or at risk of not providing therapy which can save programming time and streamline optimization.

[0163] In some examples, the impedance trends or historical information can be shown together with patient events, sensed data, stimulation values, etc. to indicate why the impedances may be changing. User interface 500 may also collect additional information from the patient, such as dehydration events or other situations that can affect the impedance measurements. In some examples, patient events (e.g., symptoms) can be tracked together with impedance. User interface 500 can correlate the impedance to patient events or patient event trends that can indicate when the leads may not be providing expected stimulation intensity to tissue. ForDocket No.: A0013259W001 / 1123-863W001 example, increasing impedance correlated with increased patient symptoms may be determined by the system to be a potential lead integrity issue. In other words, the system may identify the return of patient symptoms and either identify a lead integrity issue based on increased impedance or determine stimulation needs to be changed because lead integrity is still sufficient (e.g., impedance is acceptable). The system may also determine MRI indications based on the impedance values or other signals and display the MRI indication to the user via user interface 500. The system may even determine that otherwise out-of-range impedances for an electrode or lead may be fine for the electrodes based on historical data for that patient or for other patients.

[0164] FIG. 7 is a conceptual diagram illustrating an example timeline trend screen 700 of sensed signals and stimulation parameters for the patient. As shown in the example of FIG. 7, selection of the tab of timeline 608, screen 700 is presented to show historical data relating the sensed data (e.g., LFP data) and stimulation parameters. Hemisphere menu 702 can be selected to show information for a desired hemisphere or both, date range 704 can be selected to choose the date range of graphs 708 and 720, and events button 706 can be selected to identify various events of the patient. Zoom button 710 can be selected to reset the zoom of graph 708 to the predetermined period of time.

[0165] Graph 708 presents the sensed data and stimulation parameters (e.g., amplitude) used for stimulation during that time. Sensed data 716 (e.g., LFP power sensed over time) can include sensed data 714A which may refer to sensed data using stimulation parameters from Group A and sensed data 714B which may refer to sensed data using stimulation parameters from Group C. Event 712 indicates an event occurred at that time, and may be selected to show details of the event in event field 722. Stimulation parameter 718 indicates the amplitude (or other parameter) over the same time period as the sensed data of graph 708. Graph 708 is shown for the left hemisphere, and graph 720 can be scrolled down to view similar information of the right hemisphere.

[0166] FIGS. 8A and 8B are conceptual diagrams illustrating example medication screens displaying medications for different periods of time. As shown in the example of FIG. 8 A, screen 800 of user interface 500 is shown after selection of medication tab 610. Medication column 802 identifies the medications scheduled as part of the regimen for the patient. Date columns 804 show when then medication regimen changed and the updated medication and dosage. Change button 806 can be selected to cause user interface 500 to present another screen where the user can change any aspect of the medication regimen or schedule. The system can calculate / provide Levodopa Equivalent Daily Dose (LEDD), which was developed to compare drug regimens in the treatment of Parkinson's disease (PD). The LEDD may also provide insight into disease state progression, identifying when a patient may be a candidate for DBS, etc.Docket No.: A0013259W001 / 1123-863W001As shown in the example of FIG. 8B, screen 820 of user interface 500 is shown as an example of detailed medication schedule for the patient. Daily chart 822 indicates the daily dose schedule for each medication. If there are any changes to the medication, timing, and / or dosage, daily chart 822 may indicate those changes by including strikethrough old value, in some examples. Additionally, or alternatively, the new and old values may be identified by different colors (e.g., blue and purple) or some other visual indication. Change chart 824 provides the medications and dosage changes for the different dates in columns 826, 828, and 830. In some examples, the user may input changes to the medication regimen via one or more fields of screen 820. In some examples, change button 832 can be selected to cause user interface 500 to present another screen where the user can change any aspect of the medication regimen or schedule.

[0168] FIG. 9 is a conceptual diagram illustrating an example sensing configuration screen 900 displaying signals detectable from different electrode combinations. As shown in FIG. 9, selection of the sensing tab 612 can display screen 900 that shows the sensing configuration of IMD 106 for sensing electrical signals from the brain of the patient. Hemisphere menu 902 can be selected to show information for a desired hemisphere or both, and date range 904 can be selected to choose the date range for the sensed data. Lock button 906 can be toggled to lock or unlock the axes of graph 914. Levels button can be selected to toggle between different electrodes. Lead view 912 indicates the electrodes that can be used for different sensing configurations. Graph 914 indicates the sensed LFP power vs. frequency for each sensing electrode combination as respective data lines 916. Data lines 916 are color coded to the different sensing electrode combinations described in key 922. Frequency identifier 918 can be moved along the frequency axis to identify the frequency in box 920 according to a peak of interest in graph 914. Graph 914 is shown for the left hemisphere, but the user can scroll down to see similar information for the right hemisphere. The system can filter out specific electrode pairs to maximize data to include, adjacent and brainsense pairs, etc.

[0169] FIG. 10 is a conceptual diagram illustrating an example screen 1000 displaying aggregate characteristic values for different hemispheres of the brain. As shown in FIG. 10, selection of the decision record tab 606 can display screen 1000 that shows characteristic values from the sensed data and additional information. Screen 1000 may be similar to screen 602 of FIG. 6A. .

[0170] Screen 1000 can include graphs for one or both hemispheres for comparison purposes (or any different sensing area). Graph 1010 can include aggregate characteristic values 1014 of sensed brain signals, variance values 1016 of the brain signals, aggregate stimulation values 1012, and medication intake 1018. All of information of graph 1010 may be generated for a repeatable period of time from an larger period of time that the data was collected. In thisDocket No.: A0013259W001 / 1123-863W001 example, the repeatable period of time is one 24 hour period that corresponds to a single calendar day. However, other shorter or longer repeatable periods may be used in other examples. The aggregate values for that repeatable period of time may thus be calculated from the values at the same corresponding time during each repeatable period within the entire period time from which the data was collected. Average LFP toggle 1002 can be selected to show or hide line 1014, and average stimulation toggle 1004 can be selected to show or hide stimulation value 1012 (which is the average stimulation amplitude in the example of FIG. 10). The color of toggles 1002 and 1004 may correspond to the color of respective lines 1014 and 1012.

[0171] Aggregate values correspond to values that are aggregated, or calculated, from a plurality of values that were collected. Examples of aggregate values include an average, weighted average, median, or other values that may be representative of the data collected over the period of time for the repeatable periods of time. For example, as shown in FIG. 10, the aggregate characteristic value for the bioelectric brain signal is the average power of the LFP signal over the repeatable period of time for the entire period of time that the sensed data was collected. The average power of the LFP signal may be determined by averaging LFP signals sampled for similar time durations over the repeatable period of time. In one specific example, the power of the LFP signal may be averaged for a 10 minute time window. That average may thus be representative of the LFP signal for that 10 minute window. The system can continue to collect and / or determine the average powers of the LFP signal for each 10 minute window over the entire time period. Then, the system can average app of the 10 minute time windows at the same time point within each repeatable period of time, such as the same time of day (e.g., the 10 minute period from 9:00am to 9: 10am.). All of these averaged time windows can then be plotted to create the average LFP powers of line 1014. Although the window was 10 minutes in this example, the window may have different durations in other examples, such as a few seconds to dozens of minutes or even hours. In some examples, this window, or how the aggregate value is determined, may be selected by the user.

[0172] In addition to the aggregate characteristic values, system 400 may determine the variance of the aggregate characteristic values. Variance values 1016 may be displayed as a range from line 1014 to indicate the variance of the aggregate characteristic values for each window of time during the repeatable duration of time. Variance values 1016 are shown as a shaded range that includes line 1014, but could be displayed with upper and lower bounds instead of, or in addition to, the shading in other examples. Variance toggle 1006 can be selected or unselected to view or remove variance values 1016. Medication toggle 1008 can be selected to view or remove the indication of medication taking (expected medication based on the schedule, or actual taken medication) from graph 1012.Docket No.: A0013259W001 / 1123-863W001

[0173] Medication icons 1018 can show when during the repeatable period of time that the patient was scheduled to take medication. The user may select each icon 1018 for a pop-up window to indicate the medication and / or dosage that should have been taken. In some examples, the data used for graph 1010 is only take from a period of time during which the medication schedule was constant (i.e., no medication changes were made during that period of time). In this manner, the medication schedule would be consistent and accurate for the repeatable period of time that is shown. If the medication schedule was changed, system 400 may generate a separate period of time with associated sensed data and provide a different graph corresponding to the different medication schedule. Graph 1020 may show similar data to graph 1010, but for the right hemisphere instead of the left hemisphere. This graph can also display marked patient events that may be applicable to the graph, e.g., medication taken, falls, or other patient events.

[0174] As described herein, processing circuitry of system 400 can be configured to receive sensed data indicative of bioelectric brain signals (e.g., LFP signals or calculated powers of the LFP signals) sensed during delivery of brain stimulation therapy to the patient. System 400 can determine aggregate characteristic values (e.g., average values) of the bioelectric brain signals for a repeatable duration during the period of time and generate graph 1010 (and 1020) that includes the aggregate characteristic values for the repeatable duration. System 400 can then control user interface 500 to display graph 1010. System 400 can also determine the variance (e.g., variance values 1016) of the aggregate characteristic values for the repeatable duration during the period of time. System 400 can then control user interface 500 to visually indicate the variance together with the average characteristic values.

[0175] System 400 can also determine a medication schedule that medication is consumed by the patient, or should be consumed by the patient, during the repeatable duration. System 400 can then control user interface 500 to display medication icon 1018 at respective times on graph 1018 that includes the average characteristic values 1014. In addition, or alternatively, system 400 can determine an aggregate parameter value (e.g., stimulation value 1012) for the repeatable duration that defined brain stimulation therapy was delivered during the period of time and control user interface 500 to display the aggregate parameter value 1012 on the graph that includes the average characteristic values 1014 from the sensed data. Similar to the aggregate characteristic values of the bioelectric brain signal, the aggregate parameter value may be calculated as an average, median, or other representative value of the stimulation parameter at respective times during the repeating period of time during the entire duration of the period.

[0176] FIGS. 11 A, 11B, and 11C are conceptual diagrams illustrating an example screen 1100 displaying aggregate characteristic values for different periods of time, stimulationDocket No.: A0013259W001 / 1123-863W001 parameters, and medication information for the patient. Screen 1100 may be similar to screen 1000 of FIG. 10. However, screen 1100 displays data for different time periods together on the same screen to facilitate comparison of patient data between the different time periods.

[0177] For example, screen 1100 provides first field 1102 and second field 1104 that correspond to respective different time periods. Both first field 1102 and second field 1104 show that only Group A was used to define DBS, but in other examples different parameter groups may be used. The percentage of time that the group was used to provide stimulation may also be shown. Graphs 1110 and 1120 may be substantially similar to graphs 1010 and 1020 of FIG. 10. However, graph 1110 is shown for the left hemisphere for a first time period and graph 1120 is shown for the left hemisphere of a second time period. Three or more time periods may be shown next to each other in other examples. Each graph 1110 and 1120 may include the aggregate characteristic values 1014 of the sensed bioelectric brain signals and variance values 1016. Graphs 1124 and 1126 are also viewable when scrolling down to identify data collected from the right hemisphere. Pop-up window 1122 may show the actual aggregate characteristic value and stimulation parameter value at any point in time on a graph when the user selects that point in time, such as “mousing over” that point on the graph.

[0178] In this manner, system 400 can show multiple graphs of collected data for different periods of time. System 400 can receive second sensed data indicative of second bioelectric brain signals sensed during delivery of second brain stimulation therapy to a patient during a second period of time, determine second aggregate characteristic values of the second bioelectric brain signals for the repeatable duration during the second period of time, generate a second graph comprising the second aggregate characteristic values for the repeatable duration, and control the user interface to display the second graph (e.g., graph 1120) adjacent to the first graph (e.g., graph 1110) on a same screen 1000 of the user interface.

[0179] User interface 500 may be configured to compare any desired periods of time to any other period of time. The user may identify desired periods of time, and system 400 can generate graphs of the collected data (e.g., LFP data and stimulation parameters) for the identified periods of time. In some examples, user interface 500 may limit the time frame for each period of time. These limits may be based on absolute periods of time (e.g., one week, one month, one year, etc.), patient events (e.g., episodes, falls, etc.), change in medication, change in stimulation parameters, etc.

[0180] FIG. 1 IB shows programming information 1130 and 1140 for each of first field 1102 and second field 1104, respectively. Each of the programming information can include information such as lead configuration 1134, stimulation settings 1138, sensing configuration information 1136, and the like. Advance settings button 1132 can be selected to view additionalDocket No.: A0013259W001 / 1123-863W001 programming information or information related to stimulation during the time period associated with the period of time for the field.

[0181] FIG. 11C shows medication information 1150 and 1152 for each of first field 1102 and second field 1104, respectively. Medical information 1150 and 1152 may show the specific medications, schedule, and dosages for each time period. Notes 1154 and 1156 may also be shown for each of first field 1102 and second field 1104, respectively.

[0182] FIG. 1 ID is a conceptual diagram illustrating an example print screen 1160 that the user interface can present including the medication schedule for the patient. User interface 500 can generate print screen 1160 to summarize the medication regimen for the patient determined during the clinician session. Print screen 1160 may be configured to print a physical copy of the medication regimen and / or send an email to the patient for their information.

[0183] FIG. 1 IE is a conceptual diagram illustrating an example screen of user interface 500 that can accept user input for one or more thresholds and a histogram 1176 of sensed data with respect to the thresholds. As shown in the example of FIG. 1 IE, user interface 500 can display LFP statistics 1170 from the sensed data, such as the LFP power mean, LFP power standard deviation, LFP power median, and the range of the LFP power. The system can use the LFP statistics 1170 from sensed information for the patient to determine one or more thresholds that can be used as feedback to drive automatic adjustments to stimulation in response to LFP power measurements. FIG. 1 IE shows data for one hemisphere of the patient, but data for left and right hemispheres of the brain of the patient can be shown together on the same screen in some examples for comparison and ease of programming.

[0184] For example, the system can determine an upper threshold and a lower threshold for the LFP power based on a percentile of LFP power data detected for the patient. LFP percentile inputs 1172 are fields that the user can input a desired value for the lower percentile and the upper percentile. A default value for each percentile may be used in some examples, such as 25 percentile for the lower threshold and 75 percentile for the upper threshold. Other default percentiles may range from 5-40% for the lower threshold and 60-95% for the upper threshold. However, the default values may be different in other examples. In response to the percentiles being input, the system can calculate the lower threshold (lower LFP power) and the upper threshold (upper LFP power) that corresponds to those respective percentiles in the sensed data, illustrates the percentiles of the LFP power that occurs within the total range of LFP power sensed over time for the patient. Lower threshold 1178 would correspond to the lower percentile and upper threshold 1180 would correspond to the upper percentile. In this manner, histogram 1176 displays where the typical LFP powers would fall within the lower and upper thresholds as selected. The user can change the percentiles as desired. The clinician can enter the lower andDocket No.: A0013259W001 / 1123-863W001 upper thresholds directly into a clinician programmer for programming the IMD, or the system can directly update the programming of the IMD from user interface 500.

[0185] In some examples, the user can select the period of time for the data to be displayed in LFP statistics 1170 and histogram 1176. A custom time range percentile calculator can be a feature designed to offer users the ability to analyze LFP data within a specific time range of a day and determine the value that splits the data into a desired percentile. This feature can enable quick programming without the need to scroll through large volumes of LFP data manually. In some examples, the information of FIG. 1 IE can be provided together with screen 1100 or an other screen to indicate the thresholds together with the LFP data that is already shown. In some examples, users can select a starting hour and an ending hour for the specific day of data. This flexibility allows users to focus their analysis on specific periods, such as daytime hours. Default values can be 8 am to 8 pm, in some examples. LFP percentile inputs 1172 may accept a percentile value between 0 and 100. This percentile represents the point at which the data is divided into the desired proportion. For instance, entering 50 will give a threshold that splits the data into two equal halves, while entering 90 will provide a threshold that results in 10% of the data set being above that threshold. In some examples, the time period selected by the user can be chosen using drop-down menus or sliders for selecting the starting and ending hours.

[0186] In some examples, user interface 500 can facilitate the time selection for LFP data of FIG. 1 IE or other screens. User interface 500 may enable user selections for the patient awake hours, daytime hours, sleep hours, or any other general periods of time. The user may select any desired time. Therefore, the data making up histogram 1176 may be the same time period for each day, or may correlate to all of the data between two events (awake and sleep) or other such events.

[0187] In some examples, user interface 500 may provide additional information to inform the selection of the lower threshold, upper threshold, or any other thresholds. For example, user interface 500 may show the percentage of time between each threshold, the number of times or frequency that each threshold was crossed, or any other related metric. If the user changes a percentile, histogram 1176 can show where the new threshold would be with respect to the data. In some examples, the system can recommend one or more percentile according to the sensed information in order to treat patient symptoms. Or, the system can recommend whether or not adaptive DBS would be appropriate based on the distribution of the sensed data. User interface 500 can also compare histograms for different periods of time. The user can select two or more different periods of time, and user interface 500 can show the different histograms for comparison purposes. In some examples, user interface 500 can show histograms for before and after adaptive stimulation to indicate how LFP data has changed. User interface 500 can alsoDocket No.: A0013259W001 / 1123-863W001 suggest a single threshold or dual threshold configuration for adaptive DBS based on the distribution of LFP power in the histogram.

[0188] In some examples, the system can compare histograms from a cohort of different patients and identify thresholds and / or other stimulation parameters that were effective for those patients. The system can then cause user interface 500 may recommend a threshold or percentile based on previous successful therapy. The system can also suggest single or dual thresholds based on histograms of other patients. In some examples, user interface 500 may even recommend a particular patient that the clinician treated and corresponding histogram data or other information that may be an appropriate starting point to find similar therapy for a new patient. In addition, user interface 500 may present other information in histogram or other data formats. For example, the system may calculate the speed at which the patient (or other patients) LFP power responds to stimulation changes and recommend one or more threshold values to compensate for differences in patient response. For example, slower response patients may require more narrow thresholds to enable sufficient treatment. Conversely, faster response patients may enable large spreads in thresholds.

[0189] FIG. 12 is a conceptual diagram illustrating an example change screen 1200 indicating changes made to programming and medication schedule for the patient during the current clinician session. Screen 1200 indicates the changes to programming 1202, medications 1204, or any notes 1206 associated with this clinician session. This can be an easy view to identify what has changed, instead of showing all parameters and information. In some examples, the changes may be shown with respect to the previous parameters as well.

[0190] FIG. 13A is a conceptual diagram illustrating an example timeline trend screen 1300 showing sensed data during stimulation and non-stimulation periods of time. As shown in the example of FIG. 13A, timeline 608 tab can be selected to show screen 1300 that includes stored sensed data. Graph 1302 shows the sensed bioelectric brain signals 1306 and 1314 over time for respective periods 1304 and 1312 in the left hemisphere. Group indicator 1310 indicates the stimulation group that was used for stimulation. Stimulation line 1316 shows that stimulation was delivered during this time. Events 1308 are markers of events that may have occurred for the patient and or system generated such as MRI mode activated, MRI mode deactivated, Impedance measured, etc. User selection of each event 1308 can present details on the event that occurred. Graph 1320 shows similar data as graph 1302, but for the right hemisphere.

[0191] FIG. 13B is a conceptual diagram illustrating an example streaming data screen showing sensed LFP power and stimulation amplitude together on graph 1330. Graph 1330 can present collected sensing data (such as LFP, ERNA, and other patient physiological data) from various targets in one or more brain hemispheres or spine, etc.) from one or more periods of timeDocket No.: A0013259W001 / 1123-863W001 in which data streaming was performed for the patient. This data can include LF, ERNA, etc., in any characteristics such as power values in various formats (e.g., spectrogram, time domain, etc.). Stimulation parameters shown on graph 1330 can include one or more of amplitude, pulse width, pulse rate (frequency).

[0192] As shown in the example of FIG. 13B, user interface 500 includes graph 1330 that displays LFP power 1332 and stimulation amplitude 1334 vs. time. In this manner, graph 1330 can show both of LFP power 1332 and stimulation amplitude 1334 together to view how stimulation changes can correlate to brain signal changes. Time window 1336 indicates the smaller portion of data selected from a larger data set that is used for the time period of graph 1330. Other types of sensed data and / or stimulation parameters may be used in other examples. Therapy data 1338 includes all or a subset of data collected as part of therapy. For example, therapy data 1338 can include an indication of when the data was sensed, the stimulation program, LFP power (e.g., average, maximum, minimum, etc.), lower and upper LFP threshold, stimulation amplitude, stimulation amplitude limits (e.g., lower and upper limits), LFP frequency, the sense channel, the threshold mode used for aDBS, the pulse width, stimulation frequency, or any other parameters. User interface 500 can also provide toggle inputs that enable the user to turn any data of graph 1330 on or off for purposes of comparing different types of data.

[0193] User interface 500 can then enable the user to utilize various data illustrations (such as LFP, ERNA, and stimulation, spectrogram, and time domain data) as example information to identify various correlations and / or insights that may inform adjustments or determinations to stimulation therapy and / or other therapies. User interface 500 can enable users to select which data sessions and stream data they wish to view or compare to one or more other sessions in which data was collected. The system can present different information to facilitate comparisons and / or monitor various frequencies of interest of one or more data sets. In some examples, user interface 500 can compare one or more sensing data types to one or more other captured data sets (e.g., comparison of LFP and ERNA signals captured on different periods of time. In some examples, the system and / or user interface 500 can determine when the sensed data changes (e.g., LFP power) due to one or more stimulation parameters defining therapy. User interface 500 can also provide relative data displayed when the data changes and by how much (e.g., the relative value, percent of a value, etc.). This data may be provided for both hemispheres of the brain to show how the sensed data and / or stimulation information is similar or different for different regions of the brain.

[0194] User interface 500 can also present information indicative of, and / or system identified aspects, such as ECG or other artifacts within the sensed data, whether the current frequency ofDocket No.: A0013259W001 / 1123-863W001 interest of the sensed data is acceptable or if another frequency would be more informative to brain activity of the patient, whether gamma frequencies indicate the patient may be experiencing dyskinesia (and should be tracked for aDBS therapy). In some examples, user interface 500 may present information that indicates appropriate stimulation limits or ineffective scenarios for aDBS for the patient based on the sensed signals. The system can assist the user in finding appropriate frequencies of the LFP (or other type) signal sensed from the patient that can inform adjustments to patient therapy (e.g., aDBS). In other words, user interface 500 can present frequencies of sensed data for which the power is reactive to stimulation indicating a possible feedback signal for aDBS. For example, user interface 500 can mark patient events such as medication states or other patient symptoms compared to a spectrogram or other characteristics of the sensed data to indicate those frequencies corresponding to changes. User interface 500 can highlight any of those frequencies that may be responsive to patient state and suggest the user to select for further analysis or use in tracking LFP power. User interface 500 can also show different LFP powers for different frequencies and illustrate to the user how each frequency may correspond to other patient events or data. Medication may change which frequencies of sensed data are indicative of patient state, and the system may track different sensed data frequencies for different medication states in order to reduce situations in which a frequency of sensed signals is being masked by medication.

[0195] FIG. 13C is a conceptual diagram illustrating an example streaming data screen showing spectrogram 1350 and time domain graph 1352 of sensed LFP signals over a period of time. The information from spectrogram 1350 and time domain graph 1352 can be used to identify if the patient is a candidate for aDBS therapy or if the patient may not benefit from aDBS. Generally, if the LFP signal does not change in response to stimulation delivery, the system may not be able to identify any changes to patient state as a result of stimulation changes.

[0196] As shown in the example of FIG. 13C, both spectrogram 1350 and time domain graph 1352 can be provided to illustrate different forms of the sensed LFP signals. Spectrogram 1350 displays LFP frequency vs. time, where different colors (or textures, etc.) correspond to respective power levels at that frequency and time. User interface 500 can provide a window input that the user can use to change the time period of the data shown in each of spectrogram 1350 and time domain graph 1352 or any other graph described herein. The system can remove noise in the background of any data and filter for various frequencies and / or power.

[0197] In some examples, user interface 500 may identify and display a frequency to track over time for aDBS and / or monitor disease progression. User interface 500 can identify any signals that correspond to patient events, such as identify when gamma frequency signals become present indicating the presence of dyskinesia. User interface 500 can also identify stimulationDocket No.: A0013259W001 / 1123-863W001 artifacts or other artifacts (e.g., aliasing) present in the data. In some examples, user interface 500 can identify when an artifact in the sensed data may prevent the IMD from providing aDBS due to the artifact obscuring sensing for the patient. This identification can be used during a trial period to determine patient candidacy for aDBS or over time. In some examples, the artifact may be associated with medication, cardiac events, other implanted device operation, etc. User interface 500 can display data from different periods of time together for comparison purposes. In some examples, user interface 500 can identify seizures or other patient events that correspond to the sensed data. User interface 500 may be configured to generate an aDBS candidate score based on the patient events, sensed data, response to stimulation, or any other criteria.

[0198] In some examples, user interface 500 can modify any of spectrogram 1350 and time domain graph 1352, and other graphs shown in a screen, in response to user input. For example, the user can select a frequency within spectrogram 1350 and, responsive to selection of that frequency, user interface can adjust the LFP power shown in another graph to correspond to the newly selected frequency. This adjustment to the other graph can be done for real-time streaming of data and / or processing of previously recorded information. User interface 500 can also update the graphs to show multiple frequencies selected together for comparison of LFP power for these different selected frequencies.

[0199] FIG. 14A is a conceptual diagram illustrating an example sensing configuration screen 1400 displaying signals detectable from different electrode combinations. As shown in the example of FIG. 14A, screen 1400 may be substantially similar to screen 900 of FIG. 9. However, screen 1400 may provide sensing configuration for a complex electrode geometry where different electrodes are provided at different locations around the circumference of the lead. Screen 1400 may include lead view 1412 that indicates the electrodes that can be used for different sensing configurations, which include electrodes located both at different axial locations along the lead and at different circumferential positions. Graph 1414 indicates the sensed LFP power vs. frequency for each sensing electrode combination as respective data lines 1416. Data lines 1416 are color coded to the different sensing electrode combinations described in key 1422. Frequency identifier 1418 can be moved along the frequency axis to identify the frequency according to a peak of interest in graph 1414. Graph 1414 is shown for the left hemisphere, but the user can scroll down to see similar information for the right hemisphere. In some examples, user interface 500 may be configured to filter the different data in graph 1414 based on any characteristics such as adjacent pairs of electrodes, brainsense pairs, signals above or below a threshold, etc.

[0200] FIG. 14B is an example user interface 500 that includes an example sensing configuration screen 1430 displaying signal quality for different electrodes and medication statusDocket No.: A0013259W001 / 1123-863W001 for the patient during sensing of those signals. As shown in the example of FIG. 14B, sensing configuration screen 1430 includes levels field 1434 and segments field 1436 that provide different views of signal quality for electrodes of the same lead. Sensing configuration screen 1430 is an example display showing information related to the signals that can be sensed by each electrode of a lead. Sensing configuration screen 1430 can display information sensed for different periods of time that may be selected by survey time selector 1432. In this manner, the user can select to view the sensing information for the electrodes at any given time for the patient. In addition, by viewing the different times of each survey, the user can view the relative signal quality for each electrode, frequency, and other information for each survey.

[0201] In each of levels field 1434 and segments field 1436, a signal indicator is provided for each electrode or electrode level. The signal indicator provides a signal quality representation that indicates the quality of the signal sensed by that respective electrode. The signal quality may be calculated based on one or more factors of the sensed signals, such as signal amplitude, power of a signal at a specific frequency (or frequency range), the presence of any artifacts, impedance measurement, etc. In the example of FIG. 14B, each signal indicator provides the quality as one of three dots, which 3 dots being the best quality, 2 dots being medium quality, and 1 dot being the lowest quality. Although 3 dots are shown in this example, fewer or greater number of dots (or other symbols) may be used to indicate the signal quality. The signal quality may be relative (e.g., calculated such that the lowest quality electrodes are 1 dot and the highest quality electrodes are 3 dot) or absolute (e.g., signal quality is set according to predetermined signal quality metrics). Frequency indicator 1438 shows the frequency selected for the sensed signals used to establish the signal quality for the electrodes.

[0202] In the example shown for FIG. 14B, a monopolar sensed signals are used to determine the signal quality. Monopolar signals are sensed between a lead electrode and a common electrode (e.g., the housing of the IMD). In other examples, bipolar signals may be sensed between different electrodes of the lead, and screen 1430 can indicate the type of sensed signals for the quality indicator. In addition, the medication status 1440 can be indicated on screen 1430 for when the signals were sensed. Possible status can include that the patient was “on meds” or taking medication, “off meds” or not taking medication at the time, or “indeterminate” which means that it was not indicated whether the patient was on or off medication or the patient was perhaps in a transitional phase where medication may be wearing off. The medication status may be determined based on user input and / or sensed signals that could indicate whether the patient was influenced by medication.

[0203] In some examples, the system may allow for re-determining signal quality for the signal indicators based on a different selected frequency of the sensed data, time domain data, orDocket No.: A0013259W001 / 1123-863W001 any other information. In some examples, user interface 500 can show a graph or other indicator of changes to the signal quality of each electrode over time. This “trend view” of the signal quality may indicate whether the signal quality has changed and may indicate which electrodes have been used for sensing signals and / or delivering stimulation and any patient events associated with that electrode. User interface 500 may identify one or more electrodes that have not been tried for sensing signals and / or delivering stimulation and / or flag one or more electrodes that have been removed from use (e.g., due to above-threshold impedance or other reason). In some examples, the change in signal quality for one or more electrodes over time may indicate that the lead has moved with respect to anatomy. User interface 500 may present an indicator of potential movement of the lead when signal quality of different electrodes change together corresponding to rotational and / or axial movement. If lead movement is detected, user interface 500 may prompt the user to again perform electrode selection, threshold determination, and / or any other therapy related information for subsequent therapy. In some examples, the system may not be able to determine signal quality for the electrodes for various reasons (e.g., artifacts, impedance levels, etc.). User interface 500 can then display a warning that the signal quality ratings cannot be performed for the electrodes. If there are artifact or impedance failures of one or more electrodes, user interface 500 can display a marking on affected electrodes for view by the user.

[0204] FIG. 14C is a conceptual diagram illustrating an example sensing configuration screen 150 displaying sensed signals for different electrodes selectable based on date data was sensed. As shown in the example of FIG. 14C, sensing configuration screen 1450 includes segments field 1452 that provides different views of signal quality for electrodes of the same lead. Sensing configuration screen 1430 is an example display showing information related to the signals that have been sensed by each electrode of a lead. Signal graph 1460 provides the LFP power vs. frequency (Hz) for each of the electrodes in segments field 1452 as respective separate traces. The selected frequency 1458 may be the current frequency that is used by the system to track LFP changes. The highlighted electrode in segments field 1452 corresponds to the solid trace of signal graph 1460. Sensing configuration screen 1430 can display information sensed for different periods of time that may be selected by survey time selector 1432. User interface 500 may receive selection of any trace and highlight the corresponding electrode or receive selection of any electrode and highlight the corresponding trace for that electrode. Slider 1462 can be moved in response to user input to any LFP frequency in graph 1460 to indicate the frequency at that location. User interface 500 can use this frequency as the selected frequency for subsequent sensing of LFP signals.Docket No.: A0013259W001 / 1123-863W001

[0205] Screen 1450 can display an indication of artifact 1454 and impedance failure 1456 for any affected electrodes to inform system status / programming. User interface 500 may display artifact 1454 for any electrode in which an artifact was identified in the sensed signal for that electrode. Similarly, user interface 500 may display impedance failure 1456 for any electrode in which the measured impedance for that electrode exceeds a predetermined threshold impedance for that electrode.

[0206] In some examples, user interface 500 may be configured to display previously sensed data in a trend view that can show what electrodes have been tried for sensing and / or stimulation and which have not. User interface 500 may provide a screen that displays all of the sensed signal information for the different electrodes collected for each time the process has been executed. User interface 500 can receive user input selecting any of these times the process was run in order to view how the signal quality may have changed over time. For example, this longitudinal information can inform the user of any changes to LFP power over time, peak frequencies over time, or any other changes to leads or lead locations that can affect therapy. In this manner, the user can make other changes to therapy to adjust for such changes. In some examples, the system may analyze multiple sets of sensed signal information from different times to identify when changes have occurred and notify the user of such changes. User interface 500 can then display the data supportive of the changes to the electrodes and / or suggest an action to take to improve sensing and / or therapy.

[0207] FIG. 14D is a conceptual diagram illustrating an example sensing configuration screen 1470 displaying delivered amplitudes from each electrode during stimulation in addition with other stimulation parameters. As shown in the example of FIG. 14D, user interface 500 includes sensing configuration screen 1470 that shows actual stimulation values 1474 used for various lead configurations 1472. Although stimulation parameters can be set by the clinician to deliver stimulation therapy, those parameter values may not be achieved in some situations for various reasons. In this manner, the actual delivered stimulation amplitudes (or other parameters) may be different from the programmed values. Actual stimulation values 1474 can display the actual delivered amplitude values from each electrode. Screen 1470 can show the requested amplitude values by selecting a toggle input. In some examples, screen 1470 can display the difference between the requested amplitude values and the actual delivered amplitudes. In this manner, user interface 500 can show directly any discrepancy between the values.

[0208] In some examples, screen 1470 can display any programming changes for any electrodes and dates for any of these changes. Screen 1470 may only display the configured electrodes used for stimulation. In other examples, screen 1470 can display the deliveredDocket No.: A0013259W001 / 1123-863W001 amplitudes for all electrodes. Differences between the requested stimulation amplitudes and actual delivered amplitudes indicate that the IMD has steered current to or away from those electrodes for various reasons. This steering may be due to impedance imbalances or other issues. Screen 1470 provides the delivered amplitudes for each electrode. In some examples, screen 1470 can display a total delivered amplitude from all active electrodes to indicate a total view of the difference in delivered amplitude. In some examples, the system can calculate the delivered amplitudes at different magnitudes, such as at the lower and upper amplitude limits for each electrode. These actual delivered amplitudes may deviate more at lower or higher magnitudes, and displaying these different delivered amplitudes can highlight these differences. In some examples, user interface 500 can display the delivered amplitudes as a pop-up window in response to the user selecting or hovering over that particular electrode.

[0209] User interface 500 can calculate and display the most used electrode combination and / or stimulation parameter values during a period of time (or for all time). User interface 500 can display the implant date, last programming date, or the time duration of therapy or implantation. In some examples, user interface 500 can display the information for the latest or total ambulatory period for the patient. In some examples, user interface 500 can provide an input that, when selected, causes the system to enter any of this information into the electronic health record for the patient. In this manner, this information can be stored for the patient. Alternatively, user interface 500 can support copying any of this information for pasting into the electronic health record.

[0210] FIG. 14E is a conceptual diagram illustrating an example screen 1480 that provides graphs of the time sensed LFP values were below, between, or above respective thresholds for a certain period of time. User interface 500 can provide a screen 1480 that presents data representing how the patient is doing in relation to one or more thresholds for sensed data. These thresholds may be set for monitoring purposes or as bounds for adaptive stimulation (e.g., aDBS). In this manner, for a given period of time (e.g., a specified time period or ambulatory period) with sensing data where one or more thresholds have been configured, user interface 500 can provide the time that sensed data for the patient was within, above, or below the one or more thresholds.

[0211] As shown in FIG. 14E, screen 1480 includes graphs 1482 and 1484 that show the percentage of LFP power that is above, below, and between the lower threshold and upper threshold. In addition, if the sensed data was not recorded, the percentage of time that the LFP signals were not sensed can also be indicated. Graph 1482 indicates the data for the left subthalamic nucleus (STN) (left hemisphere), and graph 1484 indicates the data for the right STN of the right hemisphere. Since no sensing thresholds have been established for the rightDocket No.: A0013259W001 / 1123-863W001STN, a pop-up window indicates that no data is available instead of showing data for the graph. In each of graphs 1482 and 1484, the amount of time for the LFP power with respect to the thresholds can be shown for multiple different groups of stimulation parameters, as shown as groups A, B, and C. In this manner, screen 1480 can show how the patient can response to each group of stimulation parameters. In some examples, graphs 1482 and 1484 can show the LFP power with respect to the thresholds for multiple different periods of time to indicate therapy and / or disease progression trends.

[0212] This time in threshold feature provided by screen 1480 can be useful to help clinicians understand with objective information how a patient may have been feeling during the selected ambulatory period. For example, if an Alpha-Beta signal is tracked for a Parkinson’s disease patient and a significant amount of time is spent above or below the thresholds, that may indicate the patient is having more symptoms or experiencing side effects at home. This time exceeding the thresholds can indicate to the clinician next steps, such as having a conversation with a patient and / or correlate the patient reported experience with objective data. This information can become particularly helpful when aDBS is configured for a patient. For aDBS, this time in threshold information can help clinicians understand if aDBS is appropriately adjusting stimulation for a patient and whether other adjustments may be needed. In some examples, the system may automatically determine that the time in threshold is insufficient (or the time above or below one or more thresholds exceeds an acceptable duration of time or percentage) and automatically send a notification to the clinician that therapy may need to be adjusted. A predetermined time within the thresholds, or some other preset duration, may be established for the system to determine that the time has been exceeded and a notification needs to be made. In some examples, the LFP power times with respect to thresholds is shown for the entire time of the selected period, but the LFP power time with respect to thresholds may only be shown for patient awake hours during the selected period in other examples.

[0213] In addition, or alternative, to the time in threshold information of screen 1480, the system may calculate the number of times that the LFP power crosses one or more thresholds. User interface 500 may display the number of times that the LFP power crossed each threshold in a numerical or graphical representation. User interface 500 may also deliver a notification that a predetermined number of threshold crossings occurred during a period of time. An excessive number of threshold crossings may indicate that stimulation parameters may not be effective at treating the patient, such as inadequate electrode combination, frequencies, pulse widths, thresholds, etc. In some examples, the time in threshold and / or threshold crossings may be associated with an indication of whether the patient was on medication or off medication during those threshold crossings or threshold exceeding durations. In some examples, user interface 500Docket No.: A0013259W001 / 1123-863W001 may display LFP power for different frequencies to determine whether the signal changes differently for different frequencies that may better capture patient symptoms or treatment. To indicate the stability of the LFP signal, user interface 500 can display an average LFP per day and plot that average LFP per day over time to indicate an LFP trend.

[0214] User interface 500 can display additional information calculated by the system. For example, user interface 500 may display an average stimulation amplitude used to deliver stimulation during selected time period as calculated by the system. The system may calculate a railing percentage calculation (e.g., the percentage of time an adaptive program is applying the upper limit of the stimulation parameter and / or the lower limit of the stimulation parameter (or within 10% or other variance of the limit). In this manner, user interface 500 can display an indication of the system operating near the limits of the therapy capability. In some examples, the system can calculate the amount of time the stimulation parameter is within a middle portion between a lower limit and upper limit which can indicate the amount of time therapy is routine or we within the bounds. The system may generation, and user interface 500 may display, a histogram of stimulation amplitudes used to deliver stimulation during an ambulatory period. The histogram of the stimulation amplitude can be indicative of the amount of time that the stimulation is railing against (e.g., meeting or getting close to) the parameter limit.

[0215] In some examples, additional LFP statistics can be calculated by the system and displayed by user interface 500. For example, user interface 500 can provide additional information for aDBS follow up. In response to a user opening an advanced statistic screen for a stimulation parameter set for aDBS, user interface 500 can provide advanced statistics regarding the LFP signals sensed by the IMD. Example advanced statistics can include the railing percentage calculation, LFP average per day, LFP trends, threshold crossings, or any other calculation that is determined or customized in response to user input. User interface 500 may flag a statistic in response to the statistic exceeding a predetermined threshold.

[0216] FIG. 15 is a conceptual diagram illustrating an example sensing configuration screen 1500 displaying signals detectable from different electrode combinations at different periods of time. As shown in the example of FIG. 15, screen 1500 may be substantially similar to screen 900 of FIG. 9. However, screen 1500 may provide sensing configurations for different periods of time to enable comparisons. Set selection button 1502 can, when selected, enable the user to select which time periods (or different sensing configurations) that are desired to compare. User interface 500 can then display the selected sensing configurations in respective graphs 1504 and 1506. For each graph, the side of the brain, the date created, and the sensed data from the electrode combinations are presented. Although not shown in FIG. 15, the user can also scroll down to see similar information for the right hemisphere for the same periods of time. UserDocket No.: A0013259W001 / 1123-863W001 interface 500 may be configured to compare three or more different sensing configurations in other examples.

[0217] FIG. 16 is a flowchart illustrating an example technique for receiving user input selecting desired tabs of the user interface to navigate to different screens of user interface 500. The example of FIG. 16 will be described with respect to system 400, but one or more devices within system 400 may perform one, some, or all of the features of the technique of FIG. 16. In addition, various processing circuitry of the one or more devices of system 400 may perform one or more of the features herein.

[0218] As shown in the example of FIG. 16, system 400 may control user interface 500 to present possible patients and their respective information (1600). An example screen that includes this information may be screen 502 of FIG. 5. System 400 can the receive, via user interface 500, selection of a desired patient from the list of patients (1602) and control user interface 500 to present patient information and selectable tabs (1604). For example, user interface 500 may display screen 602 of FIG. 6A as s starting point.

[0219] If user interface 500 does not receive selection of a new tab (e.g., one of tabs 606- 620) (“NO” branch of block 1606), system 400 can control user interface 500 to maintain presentation of the current screen (1604). If user interface 500 receives selection of a new tab (e.g., one of tabs 606-620) (“YES” branch of block 1606), system 400 can control user interface 500 to present the information, and screen, associated with the respective tab (1608).

[0220] FIG. 17 is a flowchart illustrating an example technique generating aggregate information for sensed data for a period of time. The example of FIG. 17 will be described with respect to system 400, but one or more devices within system 400 may perform one, some, or all of the features of the technique of FIG. 17. In addition, various processing circuitry of the one or more devices of system 400 may perform one or more of the features herein.

[0221] As shown in the example of FIG. 16, system 400 receives sensed LFP data for a patient over a period of time (1700). In other examples, the LFP data may be other sensed bioelectric signals or other sensed data from the patient. System 400 can then determine the average LFP values for a 24 hour period (1702). In other examples, the average LFP values may be the aggregate characteristic values for any bioelectric signal or other sensed data. The 24 hour period may be any repeatable period of time for this the aggregate values should be determined. System 400 can also determine the variance of LFP values for the 24 hour period (1704). The variance values may indicate how much the LFP values varied for each average.

[0222] In addition to sensed data, system 400 can determine the average stimulation parameter values for the same 24 hour value (1706). The average stimulation parameter values may be any aggregate values as described herein. System can also determine the medicationDocket No.: A0013259W001 / 1123-863W001 schedule that was in place for the 24 hour period (1708) and then control user interface 500 to generate and present a graph that includes all of the average LFP values, variance of LFP values, and average stimulation parameter values for the 24 hour period (1710). Examples of this type of graph include graphs 1010, 1020, and 1120. In some examples, user interface 500 can toggle any of this information on or off from the graph.

[0223] FIG. 18 is a flowchart illustrating an example technique for generating a DBS flag indicating the patient could receive DBS therapy based on sensed data for the patient. The example of FIG. 18 will be described with respect to system 400, but one or more devices within system 400 may perform one, some, or all of the features of the technique of FIG. 18. In addition, various processing circuitry of the one or more devices of system 400 may perform one or more of the features herein.

[0224] As shown in the example of FIG. 18, system 400 can receive sensed LFP data (or other sensed patient data) for the patient over a period of time (1800). System 400 can also receive medication information for the patient for that same period of time (1802). System 400 can analyze LFP data for signals treatable by delivery of DBS (1804). For example, system 400 can identify instances where LFP data indicated that medication was not controlling symptoms (e.g., LFP signals increasing above a threshold, LFP signals not changing in response to medication, or medication becoming ineffective too quickly). In some examples, system 400 may be configured to identify DBS candidacy without comparing the LFP data to medication schedules. In some examples, there may be various user defined criteria for whether or not the patient is a DBS candidate. These criteria may include a threshold symptom severity for one or more symptoms, threshold medication dosage (e.g., LEDD), frequency or number of times the patient has LFP amplitudes above or below a threshold, amount of time that the patient has LFP amplitudes above or below a threshold, or any other criteria.

[0225] If system 400 does not determine that DBS is appropriate (“NO” branch of block 1806), system 400 can control to receive sensed LFP data (1800). If system 400 determines that DBS may be appropriate for the patient (“YES” branch of block 1806), system 400 can control user interface 500 to present a DBS flag that indicates to the clinician that the patient may benefit from DBS therapy (1808). This DBS flag may be provided as part of the patient profile or as a separate notification transmitted to the clinician. In some examples, the DBS flag may be selectable via user interface 500. In response to receiving selection of the DBS flag, system 400 may control user interface 500 to initiate DBS programming and display a programming screen for the clinician to complete before DBS therapy can be delivered (1810). In other examples, system 400 may already have predetermined, or automatically generated, stimulation parameter values, and system 400 may automatically initiate DBS therapy in response to identifying that theDocket No.: A0013259W001 / 1123-863W001 patient may benefit from DBS. When the patient is ready for DBS therapy or some adjustment to therapy, system 400 may send a notification to the clinician that the patient is a DBS candidate and / or that one or more of the candidate thresholds have been exceeded or met.

[0226] FIGS. 19 and 20 are conceptual illustrations of an example user interface 500 for annotating or changing initial programming decisions. As shown in each of FIGS. 19 and 20, a representation of the lead and electrodes are shown with annotation boxes for each electrode. Each annotation box may include a name for the electrode, a therapeutic window (e.g., stimulation limits), which symptoms stimulation improves and by how much it improves, and any other notes desired by the clinician. Each annotation box may be configured to receive user input changing any values and / or adding additional notes. Green boxes may indicate preferred electrodes for stimulation and / or sensing. Red “X” on the electrode may indicate that electrode is not effective for sensing or stimulation or otherwise not usable.

[0227] Bipolar review may refer to the process of reviewing what signals are sensed from each electrode. The review process may include receiving sensed signal from each electrode (or electrode combination) that can be used together. The user can click on each annotation box to make changes to the notes and / or click on the associated electrode to make annotations. In this manner, user interface may enable clinicians to quickly document / display monopolar / bipolar review, which is the initial testing of programming configurations in the brain, determination of the therapeutic window (stimulation limits), and rating the symptom severity changes and side effects for the patient. This process may also enable the user to mark out (e.g., remove or block) an electrode that is either out of impedance range or is just a very bad electrode combination for the patient. In some examples, system 400 could automatically mark out any electrode combinations that are either open or short circuits from an already run impedance check to prevent the clinician from having to perform this process. This process can enable the user to quickly access previous results and also troubleshoot issues. User interface 500 may also present information regarding the results of this process.

[0228] The following examples are described herein.

[0229] Example 1. A digital health system comprising: processing circuitry configured to: receive sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determine aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time; generate a graph comprising the aggregate characteristic values for the repeatable duration; and control a user interface to display the graph.

[0230] Example 2. The digital health system of example 1, wherein the processing circuitry is configured to: determine a variance of the aggregate characteristic values for the repeatableDocket No.: A0013259W001 / 1123-863W001 duration during the period of time; and control the user interface to visually indicate the variance together with the average characteristic values.

[0231] Example 3. The digital health system of any of examples 1 or 2, wherein the processing circuitry is configured to: determine a medication schedule that medication is consumed by the patient during the repeatable duration; and control the user interface to display a medication icon at respective times on the graph that includes the average characteristic values.

[0232] Example 4. The digital health system of any of examples 1 through 3, wherein the processing circuitry is configured to: determine an aggregate parameter value for the repeatable duration that defined brain stimulation therapy was delivered during the period of time; and control the user interface to display the aggregate parameter value on the graph that includes the average characteristic values.

[0233] Example 5. The digital health system of any of examples 1 through 4, wherein the graph is a first graph, the aggregate characteristic values are first aggregate characteristic values, and the period of time is a first period of time, and wherein the processing circuity is configured to: receive second sensed data indicative of second bioelectric brain signals sensed during delivery of second brain stimulation therapy to a patient during a second period of time; determine second aggregate characteristic values of the second bioelectric brain signals for the repeatable duration during the second period of time; generate a second graph comprising the second aggregate characteristic values for the repeatable duration; and control the user interface to display the second graph adjacent to the first graph on a same screen of the user interface.

[0234] Example 6. The digital health system of any of examples 1 through 5, wherein the processing circuitry is configured to control the user interface to display a plurality of selectable tabs comprising a decision record, a timeline of at least a portion of the sensed data, medication information, a graph of spectral power for different electrode combinations, and a therapy setup page.

[0235] Example 7. The digital health system of any of examples 1 through 6, wherein the processing circuitry is configured to: receive symptom input regarding one or more patient symptom types over a period of time, wherein the one or more patient symptom types comprise at least one of a facial expression, a postural stability, or a posture; determine a medication schedule that medication is consumed by the patient; determine an ambulatory period for the patient during the period of time; and control the user interface to present a graph including the symptom input, medication schedule, and the ambulatory period over time.

[0236] Example 8. The digital health system of any of examples 1 through 7, wherein the processing circuitry is configured to receive, via the user interface, user input selecting a value for one or more stimulation parameters that define subsequent brain stimulation therapy; andDocket No.: A0013259W001 / 1123-863W001 control a medical device to deliver the subsequent brain stimulation therapy according to the value for the one or more stimulation parameters.

[0237] Example 9. The digital health system of any of examples 1 through 8, wherein the sensed bioelectric brain signals include a local field potential (LFP) signal, and wherein the aggregate characteristic values are indicative of aggregate powers of the LFP signal.

[0238] Example 10. The digital health system of any of examples 1 through 9, wherein the processing circuitry is configured to: receive a plurality of patient events; determine a heat map representing when the plurality of patient events each occurred during the repeatable duration; and control the user interface to display the heat map on the graph with the aggregate characteristic values.

[0239] Example 11. The digital health system of example 10, wherein the plurality of patient events comprises at least one first type of patient event and at least one second type of patient event, and wherein the processing circuitry is configured to: determine a first percentage of the first type of patient event to a total number of the plurality of patient events; determine a second percentage of the second type of patient event to the total number of the plurality of patient events; and control the user interface to display the first percentage of the first type of patient event and the second percentage of the second type of patient event.

[0240] Example 12. The digital health system of any of examples 1 through 11, wherein the processing circuitry is configured to: determine a histogram of power of the bioelectric brain signals over a range of the power of the bioelectric brain signals; and control the user interface to display the histogram of the power of the bioelectric brain signals.

[0241] Example 13. The digital health system of any of examples 1 through 12, wherein the processing circuitry is configured to: receive a user input indicating a percentile of the bioelectric brain signals; calculate, based on the percentile, a threshold for the bioelectric brain signals; and control the user interface to display the threshold.

[0242] Example 14. The digital health system of any of examples 1 through 13, further comprising a networked server comprising the processing circuitry, and wherein the networked server device is configured to control the user interface to be presented via a web browser application.

[0243] Example 15. The digital health system of any of examples 1 through 14, further comprising an implantable medical device, wherein the implantable medical device is configured to be implanted within the patient.

[0244] Example 16. A method comprising: receiving, by processing circuitry, sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determining, by the processing circuitry, aggregate characteristic values of the bioelectricDocket No.: A0013259W001 / 1123-863W001 brain signals for a repeatable duration during the period of time; generating, by the processing circuitry, a graph comprising the aggregate characteristic values for the repeatable duration; and controlling, by the processing circuitry, a user interface to display the graph.

[0245] Example 17. The method of example 16, further comprising: determining a variance of the aggregate characteristic values for the repeatable duration during the period of time; and controlling the user interface to visually indicate the variance together with the average characteristic values.

[0246] Example 18. The method of any of examples 16 or 17, further comprising: determining a medication schedule that medication is consumed by the patient during the repeatable duration; and controlling the user interface to display a medication icon at respective times on the graph that includes the average characteristic values.

[0247] Example 19. The method of any of examples 16 through 18, further comprising: determining an aggregate parameter value for the repeatable duration that defined brain stimulation therapy was delivered during the period of time; and controlling the user interface to display the aggregate parameter value on the graph that includes the average characteristic values.

[0248] Example 20. The method of any of examples 16 through 19, wherein the graph is a first graph, the aggregate characteristic values are first aggregate characteristic values, and the period of time is a first period of time, and wherein the method further comprises: receiving second sensed data indicative of second bioelectric brain signals sensed during delivery of second brain stimulation therapy to a patient during a second period of time; determining second aggregate characteristic values of the second bioelectric brain signals for the repeatable duration during the second period of time; generating a second graph comprising the second aggregate characteristic values for the repeatable duration; and controlling the user interface to display the second graph adjacent to the first graph on a same screen of the user interface.

[0249] Example 21. The method of any of examples 16 through 20, further comprising controlling the user interface to display a plurality of selectable tabs comprising a decision record, a timeline of at least a portion of the sensed data, medication information, a graph of spectral power for different electrode combinations, and a therapy setup page.

[0250] Example 22. The method of any of examples 16 through 21, further comprising: receiving symptom input regarding one or more patient symptom types over a period of time, wherein the one or more patient symptom types comprise at least one of a facial expression, a postural stability, or a posture; determining a medication schedule that medication is consumed by the patient; determining an ambulatory period for the patient during the period of time; andDocket No.: A0013259W001 / 1123-863W001 controlling the user interface to present a graph including the symptom input, medication schedule, and the ambulatory period over time.

[0251] Example 23. The method of any of examples 16 through 22, further comprising: receiving, via the user interface, user input selecting a value for one or more stimulation parameters that define subsequent brain stimulation therapy; and controlling a medical device to deliver the subsequent brain stimulation therapy according to the value for the one or more stimulation parameters.

[0252] Example 24. The method of any of examples 16 through 23, wherein the sensed bioelectric brain signals include a local field potential (LFP) signal, and wherein the aggregate characteristic values are indicative of aggregate powers of the LFP signal.

[0253] Example 25. The method of any of examples 16 through 24, further comprising a networked server comprising the processing circuitry, and wherein the networked server device is configured to control the user interface to be presented via a web browser application.

[0254] Example 26. A non-transitory computer-readable medium comprising instructions that, when executed, control processing circuitry to: receive sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determine aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time; generate a graph comprising the aggregate characteristic values for the repeatable duration; and control a user interface to display the graph.

[0255] The techniques described in this disclosure, including those attributed to IMD 106, programmer 104, or various constituent components, 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, including one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components, embodied in programmers, such as clinician or patient programmers, medical devices, or other devices.

[0256] In one or more examples, the functions described in this disclosure may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored, as one or more instructions or code, on a computer- readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media forming a tangible, non-transitory medium. Instructions may be executed by one or more processors, such as one or more DSPs, ASICs, FPGAs, general purpose microprocessors, or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,” as used herein may refer to one or more of any ofDocket No.: A0013259W001 / 1123-863W001 the foregoing structures or any other structure suitable for implementation of the techniques described herein.

[0257] In addition, in some respects, the functionality described herein may be provided within dedicated hardware and / or software modules. Depiction of 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 realized by separate hardware or software components. Rather, functionality 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. Also, the techniques may be fully implemented in one or more circuits or logic elements. The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including an IMD, an external programmer, a combination of an IMD and external programmer, an integrated circuit (IC) or a set of ICs, and / or discrete electrical circuitry, residing in an IMD and / or external programmer.

[0258] Various examples have been described. These and other examples are within the scope of the following claims.

Claims

Docket No.: A0013259W001 / 1123-863W001WHAT IS CLAIMED IS:

1. A digital health system comprising: processing circuitry configured to: receive sensed data indicative of bioelectric brain signals sensed during delivery of brain stimulation therapy to a patient; determine aggregate characteristic values of the bioelectric brain signals for a repeatable duration during the period of time; generate a graph comprising the aggregate characteristic values for the repeatable duration; and control a user interface to display the graph.

2. The digital health system of claim 1, wherein the processing circuitry is configured to: determine a variance of the aggregate characteristic values for the repeatable duration during the period of time; and control the user interface to visually indicate the variance together with the average characteristic values.

3. The digital health system of any of claims 1 or 2, wherein the processing circuitry is configured to: determine a medication schedule that medication is consumed by the patient during the repeatable duration; and control the user interface to display a medication icon at respective times on the graph that includes the average characteristic values.

4. The digital health system of any of claims 1 through 3, wherein the processing circuitry is configured to: determine an aggregate parameter value for the repeatable duration that defined brain stimulation therapy was delivered during the period of time; and control the user interface to display the aggregate parameter value on the graph that includes the average characteristic values.

5. The digital health system of any of claims 1 through 4, wherein the graph is a first graph, the aggregate characteristic values are first aggregate characteristic values, and the period of time is a first period of time, and wherein the processing circuity is configured to:Docket No.: A0013259W001 / 1123-863W001 receive second sensed data indicative of second bioelectric brain signals sensed during delivery of second brain stimulation therapy to a patient during a second period of time; determine second aggregate characteristic values of the second bioelectric brain signals for the repeatable duration during the second period of time; generate a second graph comprising the second aggregate characteristic values for the repeatable duration; and control the user interface to display the second graph adjacent to the first graph on a same screen of the user interface.

6. The digital health system of any of claims 1 through 5, wherein the processing circuitry is configured to control the user interface to display a plurality of selectable tabs comprising a decision record, a timeline of at least a portion of the sensed data, medication information, a graph of spectral power for different electrode combinations, and a therapy setup page.

7. The digital health system of any of claims 1 through 6, wherein the processing circuitry is configured to: receive symptom input regarding one or more patient symptom types over a period of time, wherein the one or more patient symptom types comprise at least one of a facial expression, a postural stability, or a posture; determine a medication schedule that medication is consumed by the patient; determine an ambulatory period for the patient during the period of time; and control the user interface to present a graph including the symptom input, medication schedule, and the ambulatory period over time.

8. The digital health system of any of claims 1 through 7, wherein the processing circuitry is configured to receive, via the user interface, user input selecting a value for one or more stimulation parameters that define subsequent brain stimulation therapy; and control a medical device to deliver the subsequent brain stimulation therapy according to the value for the one or more stimulation parameters.

9. The digital health system of any of claims 1 through 8, wherein the sensed bioelectric brain signals include a local field potential (LFP) signal, and wherein the aggregate characteristic values are indicative of aggregate powers of the LFP signal.Docket No.: A0013259W001 / 1123-863W00110. The digital health system of any of claims 1 through 9, wherein the processing circuitry is configured to: receive a plurality of patient events; determine a heat map representing when the plurality of patient events each occurred during the repeatable duration; and control the user interface to display the heat map on the graph with the aggregate characteristic values.

11. The digital health system of claim 10, wherein the plurality of patient events comprises at least one first type of patient event and at least one second type of patient event, and wherein the processing circuitry is configured to: determine a first percentage of the first type of patient event to a total number of the plurality of patient events; determine a second percentage of the second type of patient event to the total number of the plurality of patient events; and control the user interface to display the first percentage of the first type of patient event and the second percentage of the second type of patient event.

12. The digital health system of any of claims 1 through 11, wherein the processing circuitry is configured to: determine a histogram of power of the bioelectric brain signals over a range of the power of the bioelectric brain signals; and control the user interface to display the histogram of the power of the bioelectric brain signals.

13. The digital health system of any of claims 1 through 12, wherein the processing circuitry is configured to: receive a user input indicating a percentile of the bioelectric brain signals; calculate, based on the percentile, a threshold for the bioelectric brain signals; and control the user interface to display the threshold.

14. The digital health system of any of claims 1 through 13, further comprising a networked server comprising the processing circuitry, and wherein the networked server device is configured to control the user interface to be presented via a web browser application.Docket No.: A0013259W001 / 1123-863W00115. The digital health system of any of claims 1 through 14, further comprising an implantable medical device, wherein the implantable medical device is configured to be implanted within the patient.

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