Patent Publication Number: US-2023158291-A1

Title: Method and apparatus for tagging stimulation field models with associated stimulation effect types

Description:
CLAIM OF PRIORITY 
     This application is a continuation of U.S. patent application Ser. No. 16/902,064, filed on Jun. 15, 2020, which claims the benefit of priority under 35 U.S.C. § 119(e) of U.S. Provisional Patent Application Ser. No. 62/867,478, filed on Jun. 27, 2019, which are herein incorporated by reference in their entireties. 
    
    
     TECHNICAL FIELD 
     This document relates generally to medical devices and more particularly to a method and system for encoding stimulation effect types in data structure and presentation of stimulation field models (SFMs). 
     BACKGROUND 
     Neurostimulation, also referred to as neuromodulation, has been proposed as a therapy for a number of conditions. Examples of neurostimulation include Spinal Cord Stimulation (SCS), Deep Brain Stimulation (DBS), Peripheral Nerve Stimulation (PNS), and Functional Electrical Stimulation (FES). Implantable neurostimulation systems have been applied to deliver such a therapy. An implantable neurostimulation system may include an implantable neurostimulator, also referred to as an implantable pulse generator (IPG), and one or more implantable leads each including one or more electrodes. The implantable neurostimulator delivers neurostimulation energy through one or more electrodes placed on or near a target site in the nervous system. An external programming device is used to program the implantable neurostimulator with stimulation parameters controlling the delivery of the neurostimulation energy. 
     In one example, the neurostimulation energy is delivered in the form of electrical neurostimulation pulses. The delivery is controlled using stimulation parameters that specify spatial (where to stimulate), temporal (when to stimulate), and informational (patterns of pulses directing the nervous system to respond as desired) aspects of a pattern of neurostimulation pulses. The human nervous systems use neural signals having sophisticated patterns to communicate various types of information, including sensations of pain, pressure, temperature, etc. It may interpret an artificial stimulation with a simple pattern of stimuli as an unnatural phenomenon, and respond with an unintended and undesirable sensation and/or movement. Also, as the condition of the patient may change while receiving a neurostimulation therapy, the pattern of neurostimulation pulses applied to the patient may need to be changed to maintain efficacy of the therapy while minimizing the unintended and undesirable sensation and/or movement. While modern electronics can accommodate the need for generating sophisticated pulse patterns that emulate natural patterns of neural signals observed in the human body, the capability of a neurostimulation system depends on how the stimulation parameters can be determined for a patient. Such determination can be facilitated by analyzing effects of the stimulation parameters in activating target tissue in the patient. 
     SUMMARY 
     An example (e.g., “Example 1”) of a system for programming a stimulation device to deliver neurostimulation to tissue of a patient according to a stimulation configuration may include stimulation configuration circuitry, volume definition circuitry, stimulation effect circuitry, and recording circuitry. The stimulation configuration circuitry may be configured to determine the stimulation configuration. The volume definition circuitry may be configured to determine one or more stimulation field models (SFMs) each representing a volume of the tissue activated by the delivery of the neurostimulation according to the stimulation configuration. The stimulation effect circuitry may be configured to determine a stimulation effect type for each tagging point specified for the one or more SFMs and to tag the one or more SFMs at each tagging point with the stimulation effect type determined for that tagging point. The stimulation effect type for each tagging point is a type of stimulation resulting from the delivery of the neurostimulation according to the stimulation configuration as measured at that tagging point. The recording circuitry may be configured to generate SFM data representing the determined one or more SFMs with the stimulation effect type tagged at each tagging point. 
     In Example 2, the subject matter of Example 1 may optionally be configured to further include a presentation device and presentation circuitry. The presentation circuitry is configured to present the determined one or more SFMs with visual indication of the stimulation effect type for each tagging point on the presentation device using the generated SFM data. 
     In Example 3, the subject matter of Example 2 may optionally be configured such that the presentation device includes a display screen, and the presentation circuitry is configured to display on the display screen visually distinctive features assigned to various stimulation effect types. 
     In Example 4, the subject matter of Example 3 may optionally be configured such that the visually distinctive features include various degrees of shading. 
     In Example 5, the subject matter of Example 3 may optionally be configured such that the visually distinctive features include various degrees of opacity. 
     In Example 6, the subject matter of Example 3 may optionally be configured such that the visually distinctive features include various textures. 
     In Example 7, the subject matter of Example 3 may optionally be configured such that the visually distinctive features include various colors. 
     In Example 8, the subject matter of any one or any combination of Examples 1 to 7 may optionally be configured such that the stimulation effect circuitry is configured to determine a polarity of the stimulation effect type. 
     In Example 9, the subject matter of Example 8 may optionally be configured such that the stimulation effect circuitry is further configured to determine a neurostimulation pulse type of the stimulation effect type. 
     In Example 10, the subject matter of any one or any combination of Examples 1 to 9 may optionally be configured such that the stimulation effect circuitry is configured to determine a voltage profile for each tagging point being a voltage signal measured at the tagging point and representing the stimulation field at the tagging point. 
     In Example 11, the subject matter of Example 10 may optionally be configured such that the stimulation effect circuitry is further configured to extract one or more features as a representation of the stimulation effect type from at least one of the voltage profile or one or more derivatives of the voltage profile. 
     In Example 12, the subject matter of any one or any combination of Examples 1 to 11 may optionally be configured such that the stimulation effect circuitry is configured to determine the stimulation effect type for each SFM of the one or more SFMs. 
     In Example 13, the subject matter of any one or any combination of Examples 1 to 11 may optionally be configured such that the stimulation effect circuitry is configured to determine the stimulation effect type for each grid point in or on the one or more SFMs. 
     In Example 14, the subject matter of any one or any combination of Examples 1 to 11 may optionally be configured such that the stimulation effect circuitry is configured to determine the stimulation effect type for each voxel within the one or more SFMs. 
     In Example 15, the subject matter of any one or any combination of Examples 1 to 14 may optionally be configured to further include a programming control circuit and a user interface. The programming control circuit is configured to generate a plurality of stimulation parameters controlling delivery of the neurostimulation according to a stimulation configuration, the neurostimulation delivered through one or more electrodes of the plurality of electrodes. The user interface includes a stimulation control circuit that includes at least the stimulation configuration circuitry, the volume definition circuitry, the stimulation effect circuitry, and the recording circuitry. 
     An example (e.g., “Example 16”) of a method for programming a stimulation device to deliver neurostimulation to tissue of a patient according to a stimulation configuration is also provided. The method may include determining the stimulation configuration using a processor; determining one or more stimulation field models (SFMs) using the processor, determining a stimulation effect type for each tagging point using the processor, tagging the one or more SFMs at each tagging point specified for the one or more SFMs with the stimulation effect type determined for that tagging point using the processor, and generating SFM data using the processor. The one or more SFMs each represent a volume of the tissue activated by the delivery of the neurostimulation according to the stimulation configuration. The stimulation effect type for each tagging point is a type of stimulation resulting from the delivery of the neurostimulation according to the stimulation configuration as measured at that tagging point. The SFM data represent the determined one or more SFMs with the stimulation effect type tagged at each tagging point. 
     In Example 17, the subject matter of Example 16 may optionally further include displaying the determined one or more SFMs with visual indication of the stimulation effect type for each tagging point on a display screen and displaying visually distinctive features assigned to various stimulation effect types on the display screen. 
     In Example 18, the subject matter of displaying the visually distinctive features as found in Example 17 may optionally include displaying at least one of various degrees of shading, various degrees of opacity, various textures, or various colors. 
     In Example 19, the subject matter of determining the stimulation effect type as found in any one or any combination of Examples 16 to 18 may optionally include determining a polarity. 
     In Example 20, the subject matter of determining the stimulation effect type as found in any one or any combination of Examples 16 to 19 may optionally include determining a neurostimulation pulse type. 
     In Example 21, the subject matter of determining the stimulation effect type as found in any one or any combination of Examples 16 to 20 may optionally include determining a voltage profile for each tagging point being a voltage signal measured at the tagging point and representing the stimulation field at the tagging point. 
     In Example 22, the subject matter of determining the stimulation effect type as found in Example 21 may optionally further include extracting one or more features as a representation of the stimulation effect type from at least one of the voltage profile or one or more derivatives of the voltage profile. 
     In Example 23, the subject matter of determining the stimulation effect type as found in any one or any combination of Examples 16 to 22 may optionally include determining the stimulation effect type for each SFM of the one or more SFMs. 
     In Example 24, the subject matter of determining the stimulation effect type as found in any one or any combination of Examples 16 to 22 may optionally include determining the stimulation effect type for each grid point in or on the one or more SFMs or voxel within the one or more SFMs. 
     An example (e.g., “Example 25”) of a non-transitory computer-readable storage medium including instructions, which when executed by a system, cause the system to perform a method for programming a stimulation device to deliver neurostimulation to tissue of a patient according to a stimulation configuration is also provided. The method may include determining the stimulation configuration, determining one or more stimulation field models (SFMs) each representing a volume of the tissue activated by the delivery of the neurostimulation according to the stimulation configuration, determining a stimulation effect type for each tagging point specified for the one or more SFMs, tagging the one or more SFMs at each tagging point with the stimulation effect type determined for that tagging point, and generating SFM data representing the determined one or more SFMs with the stimulation effect type tagged at each tagging point. The stimulation effect type for each tagging point is a type of stimulation resulting from the delivery of the neurostimulation according to the stimulation configuration as measured at that tagging point. 
     This Summary is an overview of some of the teachings of the present application and not intended to be an exclusive or exhaustive treatment of the present subject matter. Further details about the present subject matter are found in the detailed description and appended claims. Other aspects of the disclosure will be apparent to persons skilled in the art upon reading and understanding the following detailed description and viewing the drawings that form a part thereof, each of which are not to be taken in a limiting sense. The scope of the present disclosure is defined by the appended claims and their legal equivalents. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawings illustrate generally, by way of example, various embodiments discussed in the present document. The drawings are for illustrative purposes only and may not be to scale. 
         FIG.  1    illustrates an embodiment of a neurostimulation system. 
         FIG.  2    illustrates an embodiment of a stimulation device and a lead system, such as may be implemented in the neurostimulation system of  FIG.  1   . 
         FIG.  3    illustrates an embodiment of a programming device, such as may be implemented in the neurostimulation system of  FIG.  1   . 
         FIG.  4    illustrates an embodiment of an implantable pulse generator (IPG) and an implantable lead system, such as an example implementation of the stimulation device and lead system of  FIG.  2   . 
         FIG.  5    illustrates an embodiment of an IPG and an implantable lead system, such as the IPG and lead system of  FIG.  4   , arranged to provide neurostimulation to a patient. 
         FIG.  6    illustrates an embodiment of portions of a neurostimulation system. 
         FIG.  7    illustrates an embodiment of an implantable stimulator and one or more leads of an implantable neurostimulation system, such as the implantable neurostimulation system of  FIG.  6   . 
         FIG.  8    illustrates an embodiment of an external programming device of an implantable neurostimulation system, such as the implantable neurostimulation system of  FIG.  6   . 
         FIG.  9    illustrates an embodiment of a system for analyzing effects of neurostimulation that can be implemented in an external programming device, such as the external programming device of claim  8 . 
         FIG.  10    illustrates another embodiment of a system for analyzing effects of neurostimulation that can be implemented in an external programming device, such as the external programming device of claim  8 . 
         FIG.  11    illustrates an embodiment of a method for representing and recording stimulation field models tagged with stimulation effect types. 
         FIG.  12    illustrates an embodiment of the method of  FIG.  11    showing another view of a stimulation field model. 
         FIG.  13    illustrates an embodiment of a method for analyzing effects of neurostimulation. 
     
    
    
     DETAILED DESCRIPTION 
     In the following detailed description, reference is made to the accompanying drawings which form a part hereof, and in which is shown by way of illustration specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention, and it is to be understood that the embodiments may be combined, or that other embodiments may be utilized and that structural, logical and electrical changes may be made without departing from the spirit and scope of the present invention. References to “an”, “one”, or “various” embodiments in this disclosure are not necessarily to the same embodiment, and such references contemplate more than one embodiment. The following detailed description provides examples, and the scope of the present invention is defined by the appended claims and their legal equivalents. 
     This document discusses, among other things, a method and system for providing information for analyzing effects of neurostimulation (also referred to as neuromodulation) including volumes of tissue activated and their underlying electric fields resulting from the neurostimulation. In various embodiments, the neurostimulation can be delivered using a neurostimulation system including an implantable device configured to deliver therapies such as deep brain stimulation (DBS), spinal cord stimulation (SCS), peripheral nerve stimulation (PNS), and vagus nerve stimulation (VNS) and one or more external devices configured to program the implantable device for its operations. The present subject matter can be implemented in such one or more external devices. While DBS is discussed as a specific example, the present subject matter can be applied to analysis of effects of stimulation for various types of neuromodulation therapies. 
     Based on stimulation parameters controlling the operation of a neurostimulation system, one or more stimulation field models (SFMs), also referred to as volumes of tissue activated (VTAs) or volumes of activation (VOAs), can be estimated and graphically presented. A graphically presented SFM allows for visual observation of how various stimulator and/or lead settings affect volumes of tissue activated in a patient. An example of creating an SFM based on stimulation parameters is discussed in U.S. Pat. No. 8,849,411, “USER-DEFINED GRAPHICAL SHAPES USED AS A VISUALIZATION AID FOR STIMULATOR PROGRAMMING”, assigned to Boston Scientific Neuromodulation Corporation, which is herein incorporated by reference in its entirety. In this document, the volume of tissue activated include the volume of tissue where neural activities and/or tissue properties are modulated by delivery of neurostimulation, including but not limited to eliciting and/or blocking of action potentials. 
     SFMs can be created and displayed to demonstrate effects of various stimulation effect types (resulting from applying the stimulation parameters) in a neurostimulation therapy. In this document, a “stimulation effect type” includes a type of stimulation underlying each SFM as effected from delivery of neurostimulation controlled by the stimulation parameters. The type of stimulation can include the type of the stimulation field effected from the delivery of neurostimulation and/or other one or more definable types of effect of the delivery of neurostimulation. For example, SFMs were created to demonstrate effects of cathodic stimulation in DBS. Later, new data suggested anodic stimulation could provide different effects, including possibly superior effects. This has created a need to study of effects of polarity of stimulation that covers a spectrum of polarities that can be provided by the stimulation parameters. While information such as active anodes and cathodes used in the electrode settings can be encoded (e.g., using “+” and “−” signs and/or colors) into a presentation that also shows the SFMs, currently the presented SFMs include only an overall effect that does not show attribution to stimulation effect types. When multiple stimulation effect types (e.g., anodic and cathodic stimulations) are applied, the resultant SFMs as currently presented do not show their underlying stimulation effect types. Such information is not encoded into the SFMs and hence, is lost when viewed outside of a programming context, for example when the information is desirable for discerning strength of the effects relative to the stimulation effect types. For example, it is possible to create two SFMs that are visually indistinguishable when displayed, with one created using cathodes only and the other created using anodes only. When using each of these two SFMs in subsequent analysis, it is advantageous to know which type of stimulation each volume is associated with. In this simple example, it is possible to associate other meta-data (e.g., polarity of the current on the lead) in order to determine where each type of stimulation is occurring. However, as further discussed later in this document, such a method does not allow for tagging of SFMs with sufficient resolution (e.g., multiple tagging points for each SFM) and complex stimulation effect types (e.g., a stimulation field with a spectrum of polarities). 
     The present subject matter can encode the underlying stimulation effect types in SFM data structure and display information to allow analysis and visual observation of the contribution of each stimulation effect type to the overall effect. One example of the stimulation effect types includes stimulation polarity. The stimulation polarity can be, for example, color-coded along a polarity spectrum (from anodic to cathodic). Information required for machine-learning prediction can be used to classify and smoothly color the displayed SFM surface and encoded as meta-data in specified SFM points or portions such as voxels. While the stimulation polarity is specifically discussed in this document as an example for illustrative purposes, the present subject matter can be applied for encoding any stimulation effect types into SFM data. Other examples of the stimulation effect types that can be encoded according to the present subject matter include stimulation pulse types (e.g., with or without a pre-pulsing phase, with or without a post-pulsing phase, and/or with passive or active recharge phases) and the goals of these stimulation pulse types (e.g., having effects similar to anodes or cathodes, and/or having effects to lower or raise thresholds of certain target or non-target neural elements)). In various embodiments, the present subject matter can be applied to encode any information related to an SFM in the data representing the SFM, to allow for observation and/or analysis of various factors affecting the SFM. 
       FIG.  1    illustrates an embodiment of a neurostimulation system  100 . System  100  includes electrodes  106 , a stimulation device  104 , and a programming device  102 . Electrodes  106  are configured to be placed on or near one or more neural targets in a patient. Stimulation device  104  is configured to be electrically connected to electrodes  106  and deliver neurostimulation energy, such as in the form of electrical pulses, to the one or more neural targets though electrodes  106 . The delivery of the neurostimulation is controlled by using a plurality of stimulation parameters, such as stimulation parameters specifying a pattern of the electrical pulses and a selection of electrodes through which each of the electrical pulses is delivered. In various embodiments, at least some parameters of the plurality of stimulation parameters are programmable by a user, such as a physician or other caregiver who treats the patient using system  100 . Programming device  102  provides the user with accessibility to the user-programmable parameters. In various embodiments, programming device  102  is configured to be communicatively coupled to stimulation device via a wired or wireless link. 
     In this document, a “user” includes a physician or other clinician or caregiver who treats the patient using system  100 ; a “patient” includes a person who receives or is intended to receive neurostimulation delivered using system  100 . In various embodiments, the patient can be allowed to adjust his or her treatment using system  100  to certain extent, such as by adjusting certain therapy parameters and entering feedback and clinical effect information. 
     In various embodiments, programming device  102  can include a user interface  110  that allows the user to control the operation of system  100  and monitor the performance of system  100  as well as conditions of the patient including responses to the delivery of the neurostimulation. The user can control the operation of system  100  by setting and/or adjusting values of the user-programmable parameters. 
     In various embodiments, user interface  110  can include a graphical user interface (GUI) that allows the user to set and/or adjust the values of the user-programmable parameters by creating and/or editing graphical representations of various waveforms. Such waveforms may include, for example, a waveform representing a pattern of neurostimulation pulses to be delivered to the patient as well as individual waveforms that are used as building blocks of the pattern of neurostimulation pulses, such as the waveform of each pulse in the pattern of neurostimulation pulses. The GUI may also allow the user to set and/or adjust stimulation fields each defined by a set of electrodes through which one or more neurostimulation pulses represented by a waveform are delivered to the patient. The stimulation fields may each be further defined by the distribution of the current of each neurostimulation pulse in the waveform. In various embodiments, neurostimulation pulses for a stimulation period (such as the duration of a therapy session) may be delivered to multiple stimulation fields. 
     In various embodiments, system  100  can be configured for neurostimulation applications. User interface  110  can be configured to allow the user to control the operation of system  100  for neurostimulation. For example, system  100  as well as user interface  100  can be configured for DBS applications. Such DBS configuration includes various features that may simplify the task of the user in programming stimulation device  104  for delivering DBS to the patient, such as the features discussed in this document. 
       FIG.  2    illustrates an embodiment of a stimulation device  204  and a lead system  208 , such as may be implemented in neurostimulation system  100 . Stimulation device  204  represents an embodiment of stimulation device  104  and includes a stimulation output circuit  212  and a stimulation control circuit  214 . Stimulation output circuit  212  produces and delivers neurostimulation pulses. Stimulation control circuit  214  controls the delivery of the neurostimulation pulses from stimulation output circuit  212  using the plurality of stimulation parameters, which specifies a pattern of the neurostimulation pulses. Lead system  208  includes one or more leads each configured to be electrically connected to stimulation device  204  and a plurality of electrodes  206  distributed in the one or more leads. The plurality of electrodes  206  includes electrode  206 - 1 , electrode  206 - 2 , . . . electrode  206 -N, each a single electrically conductive contact providing for an electrical interface between stimulation output circuit  212  and tissue of the patient, where N≥2. The neurostimulation pulses are each delivered from stimulation output circuit  212  through a set of electrodes selected from electrodes  206 . In various embodiments, the neurostimulation pulses may include one or more individually defined pulses, and the set of electrodes may be individually definable by the user for each of the individually defined pulses or each of collections of pulse intended to be delivered using the same combination of electrodes. In various embodiments, one or more additional electrodes  207  (each of which may be referred to as a reference electrode) can be electrically connected to stimulation device  204 , such as one or more electrodes each being a portion of or otherwise incorporated onto a housing of stimulation device  204 . Monopolar stimulation uses a monopolar electrode configuration with one or more electrodes selected from electrodes  206  and at least one electrode from electrode(s)  207 . Bipolar stimulation uses a bipolar electrode configuration with two electrodes selected from electrodes  206  and none electrode(s)  207 . Multipolar stimulation uses a multipolar electrode configuration with multiple (two or more) electrodes selected from electrodes  206  and none of electrode(s)  207 . 
     In various embodiments, the number of leads and the number of electrodes on each lead depend on, for example, the distribution of target(s) of the neurostimulation and the need for controlling the distribution of electric field at each target. In one embodiment, lead system  208  includes 2 leads each having 8 electrodes. 
       FIG.  3    illustrates an embodiment of a programming device  302 , such as may be implemented in neurostimulation system  100 . Programming device  302  represents an embodiment of programming device  102  and includes a storage device  318 , a programming control circuit  316 , and a user interface  310 . Programming control circuit  316  generates the plurality of stimulation parameters that controls the delivery of the neurostimulation pulses according to a specified stimulation configuration that can define, for example, stimulation waveform and electrode configuration. User interface  310  represents an embodiment of user interface  110  and includes a stimulation control circuit  320 . Storage device  318  stores information used by programming control circuit  316  and stimulation control circuit  320 , such as information about a stimulation device that relates the stimulation configuration to the plurality of stimulation parameters and information relating the stimulation configuration to a volume of activation in the patient. In various embodiments, stimulation control circuit  320  can be configured to support one or more functions allowing for programming of stimulation devices, such as stimulation device  104  including its various embodiments as discussed in this document, using SFMS and their underlying stimulation effect types, as discussed below with reference to  FIGS.  9 - 13   . 
     In various embodiments, user interface  310  can allow for definition of a pattern of neurostimulation pulses for delivery during a neurostimulation therapy session by creating and/or adjusting one or more stimulation waveforms using a graphical method. The definition can also include definition of one or more stimulation fields each associated with one or more pulses in the pattern of neurostimulation pulses. As used in this document, a “stimulation configuration” can include the pattern of neurostimulation pulses including the one or more stimulation fields, or at least various aspects or parameters of the pattern of neurostimulation pulses including the one or more stimulation fields. In various embodiments, user interface  310  includes a GUI that allows the user to define the pattern of neurostimulation pulses and perform other functions using graphical methods. In this document, “neurostimulation programming” can include the definition of the one or more stimulation waveforms, including the definition of one or more stimulation fields. 
     In various embodiments, circuits of neurostimulation  100 , including its various embodiments discussed in this document, may be implemented using a combination of hardware and software. For example, the circuit of user interface  110 , stimulation control circuit  214 , programming control circuit  316 , and stimulation control circuit  320 , including their various embodiments discussed in this document, may be implemented using an application-specific circuit constructed to perform one or more particular functions or a general-purpose circuit programmed to perform such function(s). Such a general-purpose circuit includes, but is not limited to, a microprocessor or a portion thereof, a microcontroller or portions thereof, and a programmable logic circuit or a portion thereof. 
       FIG.  4    illustrates an embodiment of an implantable pulse generator (IPG)  404  and an implantable lead system  408 . IPG  404  represents an example implementation of stimulation device  204 . Lead system  408  represents an example implementation of lead system  208 . As illustrated in  FIG.  4   , IPG  404  that can be coupled to implantable leads  408 A and  408 B at a proximal end of each lead. The distal end of each lead includes electrical contacts or electrodes  406  for contacting a tissue site targeted for electrical neurostimulation. As illustrated in  FIG.  1   , leads  408 A and  408 B each include 8 electrodes  406  at the distal end. The number and arrangement of leads  408 A and  408 B and electrodes  406  as shown in  FIG.  1    are only an example, and other numbers and arrangements are possible. In various embodiments, the electrodes are ring electrodes. The implantable leads and electrodes may be configured by shape and size to provide electrical neurostimulation energy to a neuronal target included in the subject&#39;s brain, or configured to provide electrical neurostimulation energy to a nerve cell target included in the subject&#39;s spinal cord. 
       FIG.  5    illustrates an embodiment of an IPG  504  and an implantable lead system  508  arranged to provide neurostimulation to a patient. An example of IPG  504  includes IPG  404 . An example of lead system  508  includes one or more of leads  408 A and  408 B. In the illustrated embodiment, implantable lead system  508  is arranged to provide Deep Brain Stimulation (DBS) to a patient, with the stimulation target being neuronal tissue in a subdivision of the thalamus of the patient&#39;s brain. Other examples of DBS targets include neuronal tissue of the globus pallidus (GPi), the subthalamic nucleus (STN), the pedunculopontine nucleus (PPN), substantia nigra pars reticulate (SNr), cortex, globus pallidus externus (GPe), medial forebrain bundle (MFB), periaqueductal gray (PAG), periventricular gray (PVG), habenula, subgenual cingulate, ventral intermediate nucleus (VIM), anterior nucleus (AN), other nuclei of the thalamus, zona incerta, ventral capsule, ventral striatum, nucleus accumbens, and any white matter tracts connecting these and other structures. 
     Returning to  FIG.  4   , the IPG  404  can include a hermetically-sealed IPG case  422  to house the electronic circuitry of IPG  404 . IPG  404  can include an electrode  426  formed on IPG case  422 . IPG  404  can include an IPG header  424  for coupling the proximal ends of leads  408 A and  408 B. IPG header  424  may optionally also include an electrode  428 . Electrodes  426  and/or  428  represent embodiments of electrode(s)  207  and may each be referred to as a reference electrode. Neurostimulation energy can be delivered in a monopolar (also referred to as unipolar) mode using electrode  426  or electrode  428  and one or more electrodes selected from electrodes  406 . Neurostimulation energy can be delivered in a bipolar mode using a pair of electrodes of the same lead (lead  408 A or lead  408 B). Neurostimulation energy can be delivered in an extended bipolar mode using one or more electrodes of a lead (e.g., one or more electrodes of lead  408 A) and one or more electrodes of a different lead (e.g., one or more electrodes of lead  408 B). 
     The electronic circuitry of IPG  404  can include a control circuit that controls delivery of the neurostimulation energy. The control circuit can include a microprocessor, a digital signal processor, application specific integrated circuit (ASIC), or other type of processor, interpreting or executing instructions included in software or firmware. The neurostimulation energy can be delivered according to specified (e.g., programmed) modulation parameters. Examples of setting modulation parameters can include, among other things, selecting the electrodes or electrode combinations used in the stimulation, configuring an electrode or electrodes as the anode or the cathode for the stimulation, specifying the percentage of the neurostimulation provided by an electrode or electrode combination, and specifying stimulation pulse parameters. Examples of pulse parameters include, among other things, the amplitude of a pulse (specified in current or voltage), pulse duration (e.g., in microseconds), pulse rate (e.g., in pulses per second), and parameters associated with a pulse train or pattern such as burst rate (e.g., an “on” modulation time followed by an “off” modulation time), amplitudes of pulses in the pulse train, polarity of the pulses, etc. 
       FIG.  6    illustrates an embodiment of portions of a neurostimulation system  600 . System  600  includes an IPG  604 , implantable neurostimulation leads  608 A and  608 B, an external remote controller (RC)  632 , a clinician&#39;s programmer (CP)  630 , and an external trial modulator (ETM)  634 . IPG  404  may be electrically coupled to leads  608 A and  608 B directly or through percutaneous extension leads  636 . ETM  634  may be electrically connectable to leads  608 A and  608 B via one or both of percutaneous extension leads  636  and/or external cable  638 . System  600  represents an embodiment of system  100 , with IPG  604  representing an embodiment of stimulation device  104 , electrodes  606  of leads  608 A and  608 B representing electrodes  106 , and CP  630 , RC  632 , and ETM  634  collectively representing programming device  102 . 
     ETM  634  may be standalone or incorporated into CP  630 . ETM  634  may have similar pulse generation circuitry as TPG  604  to deliver neurostimulation energy according to specified modulation parameters as discussed above. ETM  634  is an external device that is typically used as a preliminary stimulator after leads  408 A and  408 B have been implanted and used prior to stimulation with IPG  604  to test the patient&#39;s responsiveness to the stimulation that is to be provided by IPG  604 . Because ETM  634  is external it may be more easily configurable than IPG  604 . 
     CP  630  can configure the neurostimulation provided by ETM  634 . If ETM  634  is not integrated into CP  630 , CP  630  may communicate with ETM  634  using a wired connection (e.g., over a USB link) or by wireless telemetry using a wireless communications link  640 . CP  630  also communicates with IPG  604  using a wireless communications link  640 . 
     An example of wireless telemetry is based on inductive coupling between two closely-placed coils using the mutual inductance between these coils. This type of telemetry is referred to as inductive telemetry or near-field telemetry because the coils must typically be closely situated for obtaining inductively coupled communication. IPG  604  can include the first coil and a communication circuit. CP  630  can include or otherwise electrically connected to the second coil such as in the form of a wand that can be place near IPG  604 . Another example of wireless telemetry includes a far-field telemetry link, also referred to as a radio frequency (RF) telemetry link. A far-field, also referred to as the Fraunhofer zone, refers to the zone in which a component of an electromagnetic field produced by the transmitting electromagnetic radiation source decays substantially proportionally to 1/r, where r is the distance between an observation point and the radiation source. Accordingly, far-field refers to the zone outside the boundary of r=λ/2π, where λ is the wavelength of the transmitted electromagnetic energy. In one example, a communication range of an RF telemetry link is at least six feet but can be as long as allowed by the particular communication technology. RF antennas can be included, for example, in the header of IPG  604  and in the housing of CP  630 , eliminating the need for a wand or other means of inductive coupling. An example is such an RF telemetry link is a Bluetooth® wireless link. 
     CP  630  can be used to set modulation parameters for the neurostimulation after IPG  604  has been implanted. This allows the neurostimulation to be tuned if the requirements for the neurostimulation change after implantation. CP  630  can also upload information from IPG  604 . 
     RC  632  also communicates with IPG  604  using a wireless link  340 . RC  632  may be a communication device used by the user or given to the patient. RC  632  may have reduced programming capability compared to CP  630 . This allows the user or patient to alter the neurostimulation therapy but does not allow the patient full control over the therapy. For example, the patient may be able to increase the amplitude of neurostimulation pulses or change the time that a preprogrammed stimulation pulse train is applied. RC  632  may be programmed by CP  630 . CP  630  may communicate with the RC  632  using a wired or wireless communications link. In some embodiments, CP  630  is able to program RC  632  when remotely located from RC  632 . 
       FIG.  7    illustrates an embodiment of implantable stimulator  704  and one or more leads  708  of an implantable neurostimulation system, such as implantable system  600 . Implantable stimulator  704  represents an embodiment of stimulation device  104  or  204  and may be implemented, for example, as IPG  604 . Lead(s)  708  represents an embodiment of lead system  208  and may be implemented, for example, as implantable leads  608 A and  608 B. Lead(s)  708  includes electrodes  706 , which represents an embodiment of electrodes  106  or  206  and may be implemented as electrodes  606 . 
     Implantable stimulator  704  may include a sensing circuit  742  that is optional and required only when the stimulator needs a sensing capability, stimulation output circuit  212 , a stimulation control circuit  714 , an implant storage device  746 , an implant telemetry circuit  744 , a power source  748 , and one or more electrodes  707 . Sensing circuit  742 , when included and needed, senses one or more physiological signals for purposes of patient monitoring and/or feedback control of the neurostimulation. Examples of the one or more physiological signals include neural and other signals each indicative of a condition of the patient that is treated by the neurostimulation and/or a response of the patient to the delivery of the neurostimulation. Stimulation output circuit  212  is electrically connected to electrodes  706  through one or more leads  708  as well as electrodes  707 , and delivers each of the neurostimulation pulses through a set of electrodes selected from electrodes  706  and electrode(s)  707 . Stimulation control circuit  714  represents an embodiment of stimulation control circuit  214  and controls the delivery of the neurostimulation pulses using the plurality of stimulation parameters specifying the pattern of neurostimulation pulses. In one embodiment, stimulation control circuit  714  controls the delivery of the neurostimulation pulses using the one or more sensed physiological signals. Implant telemetry circuit  744  provides implantable stimulator  704  with wireless communication with another device such as CP  630  and RC  632 , including receiving values of the plurality of stimulation parameters from the other device. Implant storage device  746  stores values of the plurality of stimulation parameters. Power source  748  provides implantable stimulator  704  with energy for its operation. In one embodiment, power source  748  includes a battery. In one embodiment, power source  748  includes a rechargeable battery and a battery charging circuit for charging the rechargeable battery. Implant telemetry circuit  744  may also function as a power receiver that receives power transmitted from an external device through an inductive couple. Electrode(s)  707  allow for delivery of the neurostimulation pulses in the monopolar mode. Examples of electrode(s)  707  include electrode  426  and electrode  418  in IPG  404  as illustrated in  FIG.  4   . 
     In one embodiment, implantable stimulator  704  is used as a master database. A patient implanted with implantable stimulator  704  (such as may be implemented as IPG  604 ) may therefore carry patient information needed for his or her medical care when such information is otherwise unavailable. Implant storage device  746  is configured to store such patient information. For example, the patient may be given a new RC  632  and/or travel to a new clinic where a new CP  630  is used to communicate with the device implanted in him or her. The new RC  632  and/or CP  630  can communicate with implantable stimulator  704  to retrieve the patient information stored in implant storage device  746  through implant telemetry circuit  744  and wireless communication link  640 , and allow for any necessary adjustment of the operation of implantable stimulator  704  based on the retrieved patient information. In various embodiments, the patient information to be stored in implant storage device  746  may include, for example, positions of lead(s)  708  and electrodes  706  relative to the patient&#39;s anatomy (transformation for fusing computerized tomogram (CT) of post-operative lead placement to magnetic resonance imaging (MRI) of the brain), clinical effect map data, objective measurements using quantitative assessments of symptoms (for example using micro-electrode recording, accelerometers, and/or other sensors), and/or any other information considered important or useful for providing adequate care for the patient. In various embodiments, the patient information to be stored in implant storage device  746  may include data transmitted to implantable stimulator  704  for storage as part of the patient information and data acquired by implantable stimulator  704 , such as by using sensing circuit  742 . 
     In various embodiments, sensing circuit  742  (if included), stimulation output circuit  212 , stimulation control circuit  714 , implant telemetry circuit  744 , implant storage device  746 , and power source  748  are encapsulated in a hermetically sealed implantable housing or case, and electrode(s)  707  are formed or otherwise incorporated onto the case. In various embodiments, lead(s)  708  are implanted such that electrodes  706  are placed on and/or around one or more targets to which the neurostimulation pulses are to be delivered, while implantable stimulator  704  is subcutaneously implanted and connected to lead(s)  708  at the time of implantation. 
       FIG.  8    illustrates an embodiment of an external programming device  802  of an implantable neurostimulation system, such as system  600 . External programming device  802  represents an embodiment of programming device  102  or  302 , and may be implemented, for example, as CP  630  and/or RC  632 . External programming device  802  includes an external telemetry circuit  852 , an external storage device  818 , a programming control circuit  816 , and a user interface  810 . 
     External telemetry circuit  852  provides external programming device  802  with wireless communication with another device such as implantable stimulator  704  via wireless communication link  640 , including transmitting the plurality of stimulation parameters to implantable stimulator  704  and receiving information including the patient data from implantable stimulator  704 . In one embodiment, external telemetry circuit  852  also transmits power to implantable stimulator  704  through an inductive couple. 
     In various embodiments, wireless communication link  640  can include an inductive telemetry link (near-field telemetry link) and/or a far-field telemetry link (RF telemetry link). For example, because DBS is often indicated for movement disorders which are assessed through patient activities, gait, balance, etc., allowing patient mobility during programming and assessment is useful. Therefore, when system  600  is intended for applications including DBS, wireless communication link  640  includes at least a far-field telemetry link that allows for communications between external programming device  802  and implantable stimulator  704  over a relative long distance, such as up to about 20 meters. External telemetry circuit  852  and implant telemetry circuit  744  each include an antenna and RF circuitry configured to support such wireless telemetry. 
     External storage device  818  stores one or more stimulation waveforms for delivery during a neurostimulation therapy session, such as a DBS therapy session, as well as various parameters and building blocks for defining one or more waveforms. The one or more stimulation waveforms may each be associated with one or more stimulation fields and represent a pattern of neurostimulation pulses to be delivered to the one or more stimulation field during the neurostimulation therapy session. In various embodiments, each of the one or more stimulation waveforms can be selected for modification by the user and/or for use in programming a stimulation device such as implantable stimulator  704  to deliver a therapy. In various embodiments, each waveform in the one or more stimulation waveforms is definable on a pulse-by-pulse basis, and external storage device  818  may include a pulse library that stores one or more individually definable pulse waveforms each defining a pulse type of one or more pulse types. External storage device  818  also stores one or more individually definable stimulation fields. Each waveform in the one or more stimulation waveforms is associated with at least one field of the one or more individually definable stimulation fields. Each field of the one or more individually definable stimulation fields is defined by a set of electrodes through a neurostimulation pulse is delivered. In various embodiments, each field of the one or more individually definable fields is defined by the set of electrodes through which the neurostimulation pulse is delivered and a current distribution of the neurostimulation pulse over the set of electrodes. In one embodiment, the current distribution is defined by assigning a fraction of an overall pulse amplitude to each electrode of the set of electrodes. Such definition of the current distribution may be referred to as “fractionalization” in this document. In another embodiment, the current distribution is defined by assigning an amplitude value to each electrode of the set of electrodes. For example, the set of electrodes may include 2 electrodes used as the anode and an electrode as the cathode for delivering a neurostimulation pulse having a pulse amplitude of 4 mA. The current distribution over the 2 electrodes used as the anode needs to be defined. In one embodiment, a percentage of the pulse amplitude is assigned to each of the 2 electrodes, such as 75% assigned to electrode  1  and 25% to electrode  2 . In another embodiment, an amplitude value is assigned to each of the 2 electrodes, such as 3 mA assigned to electrode  1  and 1 mA to electrode  2 . Control of the current in terms of percentages allows precise and consistent distribution of the current between electrodes even as the pulse amplitude is adjusted. It is suited for thinking about the problem as steering a stimulation locus, and stimulation changes on multiple contacts simultaneously to move the locus while holding the stimulation amount constant. Control and displaying the total current through each electrode in terms of absolute values (e.g. mA) allows precise dosing of current through each specific electrode. It is suited for changing the current one contact at a time (and allows the user to do so) to shape the stimulation like a piece of clay (pushing/pulling one spot at a time). 
     Programming control circuit  816  represents an embodiment of programming control circuit  316  and generates the plurality of stimulation parameters, which is to be transmitted to implantable stimulator  704 , based on a specified stimulation configuration (e.g., the pattern of neurostimulation pulses as represented by one or more stimulation waveforms and one or more stimulation fields, or at least certain aspects of the pattern). The stimulation configuration may be created and/or adjusted by the user using user interface  810  and stored in external storage device  818 . In various embodiments, programming control circuit  816  can check values of the plurality of stimulation parameters against safety rules to limit these values within constraints of the safety rules. In one embodiment, the safety rules are heuristic rules. 
     User interface  810  represents an embodiment of user interface  310  and allows the user to define the pattern of neurostimulation pulses and perform various other monitoring and programming tasks. User interface  810  includes a display screen  856 , a user input device  858 , and an interface control circuit  854 . Display screen  856  may include any type of interactive or non-interactive screens, and user input device  858  may include any type of user input devices that supports the various functions discussed in this document, such as touchscreen, keyboard, keypad, touchpad, trackball, joystick, and mouse. In one embodiment, user interface  810  includes a GUI. The GUI may also allow the user to perform any functions discussed in this document where graphical presentation and/or editing are suitable as may be appreciated by those skilled in the art. 
     Interface control circuit  854  controls the operation of user interface  810  including responding to various inputs received by user input device  858  and defining the one or more stimulation waveforms. Interface control circuit  854  includes stimulation control circuit  820 , which represents an example of stimulation control circuit  320 . 
     Stimulation control circuit  820  can determine the stimulation configuration and determine one or more stimulation field models (SFMs) each representing a volume of tissue activated by delivering neurostimulation according to the stimulation configuration. In various embodiments, such a volume may be estimated for a set of stimulation parameters based on modeling of electrodes and tissue. Examples of such modeling and volume estimation are discussed in U.S. Pat. No. 8,190,250 B2, entitled “SYSTEM AND METHOD FOR ESTIMATING VOLUME OF ACTIVATION IN TISSUE”, U.S. Pat. No. 8,706,250 B2, entitled “NEUROSTIMULATION SYSTEM FOR IMPLEMENTING MODEL-BASED ESTIMATE OF NEUROSTIMULATION EFFECTS”, U.S. Pat. No. 8,934,979 B2, entitled “NEUROSTIMULATION SYSTEM FOR SELECTIVELY ESTIMATING VOLUME OF ACTIVATION AND PROVIDING THERAPY”, U.S. Pat. No. 9,792,412 B2, entitled “SYSTEMS AND METHODS FOR VOA MODEL GENERATION AND USE”, all assigned to Boston Scientific Neuromodulation Corporation, which are incorporated by reference herein in their entirety. 
     In various embodiments, stimulation control circuit  820  can generate SFM data representing the one or more SFMs, visually present the one or more SFMs using presentation device  856  based on the SFM data, and store the SFM data in external storage device  818  to be used for analysis when needed. The one or more SFMs, without additional data, do not indicate a stimulation effect type (e.g., anodic or cathodic stimulation field) underlying each SFM. In other words, the activated volume itself does not indicate what stimulation effect type activates it. 
     The stimulation effect type includes a type of stimulation effected from delivery of neurostimulation according to the stimulation configuration. In one embodiment, the stimulation effect type underlying each SFM includes one or more features measurable from one or more voltage profiles representing the stimulation field at one or more points within the SFM. For example, the voltage profile for a point within the SFM being a voltage signal measured at the point and showing a pulse resulting from delivery of a neurostimulation pulse. In an example of an existing system, the SFM is not tagged with the underlying stimulation effect type (e.g., the one or more features measurable from one or more voltage profiles), and the visually presented SFM does not indicate the underlying stimulation effect type. Though the SFM can be associated with the stimulation configuration, the stimulation effect type is lost (not stored) and not visually indicated, if it is not recorded in association with the SFM. The present subject matter provides for SFM data representing SFMs each tagged with one or more underlying stimulation effect type, thereby allowing for presentation and analysis of the SFMs with indications of their underlying stimulation effect type(s). 
     In various embodiments, external programming device  802  can have operation modes including a composition mode and a real-time programming mode. Under the composition mode (also known as the pulse pattern composition mode), user interface  810  is activated, while programming control circuit  816  is inactivated. Programming control circuit  816  does not dynamically updates values of the plurality of stimulation parameters in response to any change in the one or more stimulation waveforms. Under the real-time programming mode, both user interface  810  and programming control circuit  816  are activated. Programming control circuit  816  dynamically updates values of the plurality of stimulation parameters in response to changes in the set of one or more stimulation waveforms, and transmits the plurality of stimulation parameters with the updated values to implantable stimulator  704 . 
       FIG.  9    illustrates an embodiment of a system for analyzing effects of neurostimulation that can include stimulation configuration circuitry  960 , volume definition circuitry  962 , stimulation effect circuitry  964 , and recording circuitry  966 . In various embodiments, this system can be implemented in an external programming device such as external programming device  802 . In the illustrated embodiment, this system is part of a stimulation control circuit  920 , which represents an example of stimulation control circuit  320  or  820 . 
     Stimulation configuration circuitry  960  can determine the stimulation configuration. Volume definition circuitry  962  can determine one or more SFMs each representing a volume of the patient&#39;s tissue activated by the delivery of the neurostimulation according to the stimulation configuration. Stimulation effect circuitry  964  can determine a stimulation effect type for each tagging point specified for the one or more SFMs and can tag the one or more SFMs at each tagging point with the stimulation effect type determined for that tagging point. The stimulation effect type for each tagging point is a type of stimulation resulting from the delivery of the neurostimulation according to the stimulation configuration as measured at that tagging point. Recording circuitry  966  can generate SFM data representing the determined one or more SFMs with the stimulation effect type tagged at each tagging point. The SFM data allow for analysis and/or presentation of the one or more SFMs with information on the stimulation effect type underlying each of the one or more SFMs. 
     In one embodiment, stimulation effect circuitry  964  determines a voltage profile for a tagging point. The voltage profile is a voltage signal measured at the tagging point and representative of the stimulation field at the tagging point. Stimulation effect circuitry  964  extracts one or more features as representation of the stimulation effect type from the voltage profile and/or one or more derivatives of the voltage profile. 
       FIG.  10    illustrates another embodiment of a system for analyzing effects of neurostimulation that can be implemented in an external programming device such as external programming device  802 . This system can include the system illustrated in  FIG.  9    (including stimulation configuration circuitry  960 , volume definition circuitry  962 , stimulation effect circuitry  964 , and recording circuitry  966 ) and presentation circuitry  1068 , presentation device  1056 , and storage device  1018 . In the illustrated embodiment, stimulation configuration circuitry  960 , volume definition circuitry  962 , stimulation effect circuitry  964 , recording circuitry  966 , and presentation circuitry  1068  are part of a stimulation control circuit  1020 , which represents another example of stimulation control circuit  320  or  820 . When the system is implemented in external programming device  802 , stimulation control circuit  1020  is implemented in stimulation control circuit  820 , presentation device  856  can be used as presentation device  1056 , and external storage circuit  818  can be used as storage device  1018 . 
     Stimulation control circuit  1020  can determine the stimulation configuration and analyze one or more effects of the stimulation configuration. In addition to the structure and functions of stimulation control circuit  920 , stimulation control circuit  1020  further includes presentation circuitry  1068 , which can present the one or more SFMs with visual indication of the stimulation effect type associated with each tagging point on presentation device  1056  using the SFM data produced by recording circuit  966 . In various embodiments, recording circuit  966  stores the SFM data in storage device  1018  for presentation and/or analysis. 
     In various embodiments, presentation circuitry  1068  presents on a display screen of presentation device  1056  visually distinctive features each assigned to a stimulation effect type. Examples of the visually distinctive features can include various degrees of shading (grayscale), various degrees of opacity, various textures (filling patterns), and various colors. In one embodiment in which the stimulation effect type includes polarity, presentation circuitry  1068  presents on the display screen the one or more SFMs with a continuum of grayscale, color, or other visual indicator representing the continuum of polarity for each tagging point using the SFM data, at a resolution determined by the resolution of grid points or voxels. 
       FIG.  11    illustrates an embodiment of a method for representing and recording stimulation field models tagged with stimulation effect types.  FIG.  11    illustrates an SFM display that can be shown on the display screen of presentation device  1056 . The SFM display shows a portion of a lead  1108  with visible electrodes  1106 - 1 ,  1106 - 2 ,  1106 - 3 ,  1106 - 4 , and  1106 - 5  and three SFMs (SFM 1 , SFM 2 , and SFM 3 ) resulting from delivering neurostimulation through active electrodes  1106 - 1 ,  1106 - 2 ,  1106 - 3 , and  1106 - 4 . Electrodes  1106 - 1  and  1106 - 2  are used as cathodes (labeled “−”), and electrodes  1106 - 3  and electrodes  1106 - 4  are used as anodes. The SFMs are displayed with various degrees of shading (grayscale) presenting their polarities as the stimulation effect type.  FIG.  12    illustrates an embodiment of the method of  FIG.  11    showing a transverse view of the SFM display showing a portion of a lead  1208  with visible electrodes  1206 - 1 ,  1206 - 2 , and  1106 - 3  and a resulting from delivering neurostimulation using electrodes  1106 - 1  and  1106 - 2  as anodes and  1106 - 3  as a cathode. 
     The various degrees of shading (grayscale) as illustrated in  FIGS.  11  and  12   , or any other visually distinctive features, represent the stimulation effect types underlying the SFMs. In various embodiments, the stimulation effect types can include a continuum of polarity (e.g., represented by a value of polarity between −1 (cathodic) to +1 (anodic)) and are presented in with the corresponding responses (volumes of tissue activated). 
     In one embodiment, stimulation effect circuitry  964  also tags phases of a neurostimulation pulse to each tagging point. Such phases of the neurostimulation pulse can further distinguish the stimulation effect types. A simple neurostimulation pulse has a single active phase that can be anodic (a) and cathodic (c). Substantially different SFMs can result from a neurostimulation pulse programmable for multiple active phases and can be desirable. In one example, a neurostimulation pulse can have 5 programmable phases (pre-phase, phase 1, interphase, phase 2, phase 3). A simple cathodic pulse can be programmed as (−,c,−,−,−), i.e.: no pre-pulse, cathodic phase 1, interphase neither anode nor cathode, no phase 2, passive phase 3. An anodic pre-pulse can be added by programming the pulse as (a,C,−,−,−), i.e.: an anodic pre-pulse, Cathodic phase 1 (capitalized letter indicating the main stimulation pulse), interphase neither anode nor cathode, no phase 2, passive phase 3. 
     In various embodiments, the tagging points can be SFMs (volumes, each volume is tagged once), grid points in or on the SFMs (potentially allowing each volume to be tagged more than once for a desirable resolution), or voxels within the SFMs (potentially allowing each volume to be tagged more than once for a desirable resolution). When the SFM is a 3-dimensional, the grid points can include points on the surface of the SFM, such as all or selected connecting points of a triangle mesh representing the surface of the SFM, or can include grid points within the SFM underlying its surface. A desired resolution in distribution of the stimulation effect types can be achieved by specifying grid points or voxels. The SFM data produced by recording circuitry  966  include data representing the stimulation effect type for each tagging point. It is noted that polarities of the electrodes cannot be used represent the stimulation effect type because they do not show the multiple polarities of the fields underlying the SFMs, the SFMs are disjoint from the lead, it is difficult to weight polarities of the electrodes to polarities of the SFM, and the polarities of the electrodes do not allow for grading the responses across space. 
     Referring to  FIG.  11   , after the tagging points are defined, stimulation effect circuitry  964  can determine the stimulation effect type for each tagging point and tag the SFMs at each tagging point with the stimulation effect type determined for that tagging point. In the illustrated embodiment, stimulation effect circuitry  964  determines a voltage profile for each tagging point, with two examples V 1  and V 2  shown under “voltage profiles” in  FIG.  11   . V 1  represents an example of a voltage profile determined for a tagging point within SFM 1 . V 2  represents an example of a voltage profile determined for a tagging point within SFM 2 . Stimulation effect circuitry  964  can then extract one or more features from each voltage profile and/or one or more derivatives of each voltage profile. Parameter(s) representing the extracted feature(s) is(are) representative of the stimulation effect type at the tagging point. As illustrated in  FIG.  11   , under “features”, N (N≥1) features are extracted from each voltage profile. Thus, features F 1 - 1 , F 1 - 2 , F 1 - 3 , . . . F 1 -N are extracted from V 1 , and features F 2 - 1 , F 2 - 2 , F 2 - 3 , . . . F 2 -N are extracted from V 2 . This is repeated for all the tagging points specified. In various embodiments, the number and type of the features to be extracted can be determine based on the desirability of information and cost (computational power). Examples of the features that can be extracted from the voltage profile are shown in Table 1. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Examples of Features Measured from a Voltage Profile. 
               
            
           
           
               
               
            
               
                 Parameter 
                 Description 
               
               
                   
               
               
                 MAX 
                 Maximum value of the voltage profile. 
               
               
                 MIN 
                 Minimum value of the voltage profile. 
               
               
                 STD 
                 Standard deviation of the voltage profile. 
               
               
                 CENTRAL 
                 Value at the central node of the voltage profile. 
               
               
                 MAXABS 
                 Maximum of the absolute values of the voltage profile. 
               
               
                 RANGE 
                 Difference between maximum and minimum values of the 
               
               
                   
                 voltage profile. 
               
               
                 AREAN 
                 The area under the negative portions of the voltage profile 
               
               
                   
                 with all points &gt;0 set to 0; expressed as a negative 
               
               
                   
                 number. 
               
               
                 AREAP 
                 The area under the positive portions of the voltage profile 
               
               
                   
                 with all points &lt;0 set to 0; expressed as a positive 
               
               
                   
                 number. 
               
               
                 AREAT 
                 Total area under the profile expressed as an absolute value. 
               
               
                 AREAD 
                 Net effective area under the profile. 
               
               
                 EXT 
                 Most extreme value (farthest from zero) of the profile. Note 
               
               
                   
                 that although its magnitude is the same as that of 
               
               
                   
                 MAXABS, it may have a sign difference (when MIN is 
               
               
                   
                 greater than MAX). 
               
               
                   
               
            
           
         
       
     
     In various embodiments, each parameter in Table 1 can be measured from the voltage profile (V) and/or one or more derivatives of the voltage profile (first derivative ΔV, second derivative Δ 2 V, third derivative Δ 3 V, fourth derivative Δ 4 V, . . . ). Stimulation effect circuitry  964  can measure any one or any combination of these parameters for each tagging point to represent the stimulation effect type. For example, stimulation effect circuitry  964  can measure for each tagging point a set of 10 parameters including MAX from Δ 2 V, CENTRAL from Δ 2 V, Δ 3 V, and Δ 4 V, MAXABS from V, AREAP from Δ 2 V, AREAD from Δ 2 V, and EXT from Δ 2 V, Δ 3 V, and Δ 4 V. 
     In various embodiments, recording circuitry  966  can group the SFM data based on the stimulation effect type tagged on the SFMs. This solves the problem of grouping the SFMs overlapping in common space for analysis, when their stimulation effect types differ. For example, it can be desirable to treat anodic and cathodic volumes differently when performing a sweet-spot analysis (for determining an optimal stimulation target site). Because the stimulation configuration alone does not indicate the resulting stimulation effect types, the present subject matter provides more information for improved analysis and selection of the stimulation configuration by tagging each SFM, or preferably each grid point or voxel within each SFM, with the stimulation effect type. 
       FIG.  13    illustrates an embodiment of a method  1370  for analyzing effects of neurostimulation. In one embodiment, method  1370  is performed using stimulation control circuit  1020 . For example, stimulation control circuit  1020  can include a processor programmed to perform selected or all the steps of method  1370 . Storage device  1010  can include a non-transitory computer-readable storage medium including instructions, which when executed by the processor, cause the processor to perform method  1370 . In various embodiments, method  1370  is performed for programming a stimulation device to deliver neurostimulation to tissue of a patient according to a stimulation configuration. 
     At  1371 , a stimulation configuration is determined. To programming the stimulation device, a plurality of stimulation parameters is generated for controlling delivery of the neurostimulation according to the stimulation configuration. The stimulation can then deliver the neurostimulation one or more electrodes of a plurality of electrodes in a lead system according to the stimulation configuration, which specifies stimulation waveforms and fields (electrode arrangements). 
     At  1372 , one or more SFMs are determined. The one or more SFMs each represent a volume of the patient&#39;s tissue activated by the delivery of the neurostimulation according to the stimulation configuration. 
     At  1373 , a stimulation effect type for each tagging point specified for the one or more SFMs is determined. The stimulation effect type for each tagging point can be a type of stimulation resulting from the delivery of the neurostimulation according to the stimulation configuration as measured at that tagging point. In one embodiment, the stimulation effect type includes a polarity. In another embodiment, the stimulation effect type includes a neurostimulation pulse type. In one embodiment, determining the stimulation effect type includes determining a voltage profile for each tagging point. The voltage profile is a voltage signal measured at the tagging point and representative of the stimulation field at the tagging point. Determining the stimulation effect type further includes extracting one or more features as a representation of the stimulation effect type from at least one of the voltage profile or one or more derivatives of the voltage profile. Examples of such one or more features can include the polarity of the voltage profile and/or the features in Table 1. In various embodiments, determining the stimulation effect type for each tagging point can include determining the stimulation effect type for each SFM. When a better resolution is desired, determining the stimulation effect type for each tagging point can include determining the stimulation effect type for each grid point or voxel within each SFM. 
     At  1374 , the one or more SFMs are tagged at each tagging point with the stimulation effect type determined for that tagging point. At  1375 , SFM data are generated. The SFM data represent the one or more SFMs with the stimulation effect type tagged at each tagging point in the one or more SFMs. Performance of method  1370  can stop at this point with the SFM data saved for later use. 
     Method  1370  can optionally include steps  1376  and/or  1377 , which are illustrated in  FIG.  13   . At  1376 , the one or more SFMs are presented with visual indication of the stimulation effect type for each tagging point in the one or more SFMs on a display screen. The stimulation effect type is visually indicated by displaying visually distinctive features assigned to various stimulation effect types on the display screen. For example, the visually distinctive features can include various degrees of shading (grayscale), various degrees of opacity, various textures, or various colors. At  1377 , the SFM data is analyzed using the stimulation effect type(s). For example, SFMs or portions of the SFMs may be grouped by the stimulation effect types for analysis. In one embodiment, a single device includes a processor programmed to perform method  1370  including all the illustrated steps. In other embodiments, two or more devices include processors programmed to perform method  1370 , with one device including a processor programmed to perform steps  1371 ,  1372 ,  1373 ,  1374 , and  1375 , and one or more other devices each including a processor programmed to perform steps  1376  and/or  1377 . 
     In various embodiments, method  1370  can be performed to collect SFM data for evaluating stimulation configurations based on analysis of SFMs tagged with stimulation effect types. For example, using multiple polarities can enhance selectivity in DBS and when using directional leads. When the trajectory or orientation of a test neural element in space affects its response to neurostimulation, tagging voxels with stimulation effect types can allow for a more refined analysis. 
     Some examples of performing steps  1376  and/or  1377  using the SFM data generated at  1375  in stimulation device programming are discussed below. In various embodiments, the SFM data generated using the present system and method meet the requirement of these examples, but are not limited by meeting such requirements. 
     In one example, while programming a stimulation device, the SFM(s) associated with the stimulation parameters are displayed with visual indicators (e.g., with colors or grayscale for polarity) of the stimulation effect type(s) underlying the SFM(s). The SFM(s) and the visual indicators are modified as the stimulation parameters are modified. 
     In another example, SFM data was saved from a previously programmed or planned stimulation. Using the same device that generated the SFM data or a different device to which the SFM data was exported to, the SFM(s) represented in the SFM data are displayed with visual indicators (e.g., with colors or grayscale for polarity) of the stimulation effect type(s) underlying the SFM(s). 
     In yet another example, SFMs from multiple previously programmed or planned stimulation can be combined by controlling the joining of the SFMs based on their underlying stimulation effect types (e.g., grouping by selecting only 100% cathodic regions, regions with over 60% cathodic effect, or regions of only mixed polarity effect). For example, 10 SFMs, including 6 SFMs with only the cathodic regions and 4 SFMs with only the mixed regions, can be combined to compare these subsets. Similarly, SFMS with regions of cathode effect and SFMs with regions of anode effect and depolarizing pre-pulse effect can be combined to compare these subsets. 
     In these two examples, some data are presented directly (e.g., automatically, such was the visual indicators using colors or grayscale for polarity), while other data can be presented in a different format and/or in response to a user command (e.g., presenting a pop-up textbox showing data measured from the voltage profile in response to the user clicking on a point on a surface of a displayed SFM). 
     In these examples, the visual indicators can be produced at the time of generating the SFM data and saved with the SFM data by the device that generates the SFM data, or at the time of presentation by another device to which the SFM data was exported to. Once the SFM data are generated at  1375  by one device, they can be processed by the same device or one or more other devices each capable of performing steps  1376  and/or  1377 . 
     It is to be understood that the above detailed description is intended to be illustrative, and not restrictive. Other embodiments will be apparent to those of skill in the art upon reading and understanding the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.