Abstract: A computer implemented system and method provides a volume of activation (VOA) estimation model that receives as input two or more electric field values of a same or different data type at respective two or more positions of a neural element and determines based on such input an activation status of the neural element. A computer implemented system and method provides a machine learning system that automatically generates a computationally inexpensive VOA estimation model based on output of a computationally expensive system.

Abstract: A method for generating a stimulation program for electrical stimulation of a patient includes providing, by a processor on a display, a first grid of first pixels and a representation of a portion of an electrical stimulation lead with electrodes; obtaining, by the processor, a user selection of a first set of the first pixels in the first grid for stimulation; generating, by the processor, a stimulation program based, at least in part, on the user-selected first set of first pixels for stimulation using at least one of the electrodes of the electrical stimulation lead; and initiating, by the processor, a signal that provides an implantable pulse generator with the stimulation program. In other methods, instead of a grid of pixels, user-selectable primitives or selectable-objects are used to determine a desired stimulation region and generate the stimulation program.

Abstract: An electrical stimulation lead includes a lead body having a distal end portion, a proximal end portion, and a longitudinal length; terminals disposed along the proximal end portion of the lead body; electrodes disposed along the distal end portion of the lead body; and conductors extending along the lead body and electrically coupling the terminals to the electrodes. The lead body includes an intermediate portion disposed between the proximal end portion and the distal end portion. The intermediate portion includes at least one separation element that extends longitudinally along the intermediate portion and the intermediate portion is deployable from an undeployed configuration to a deployed configuration responsive to operation of the at least one separation element.

Abstract: An electrical stimulation system for use with a plurality of electrodes implanted within a tissue region comprises a neurostimulator configured for delivering electrical stimulation energy to the plurality of electrodes in accordance with a set of stimulation parameters, thereby injecting a charge into the tissue region, a control device configured for receiving user input to modify the set of stimulation parameters, and controller/processor circuitry configured for, in response to the user input computing a charge injection metric value as a function of a physical electrode parameter and an electrical source parameter for a first set of the electrodes, wherein the electrode set comprises at least two electrodes, comparing the computed charge injection metric value to a safety threshold value, and performing a corrective action based on the comparison.

Abstract: A computer implemented system and method provides a volume of activation (VOA) estimation model that receives as input two or more electric field values of a same or different data type at respective two or more positions of a neural element and determines based on such input an activation status of the neural element. A computer implemented system and method provides a machine learning system that automatically generates a computationally inexpensive VOA estimation model based on output of a computationally expensive system.

Abstract: An implantable electrical stimulation lead includes a lead body; terminals disposed along the proximal portion of the lead body; electrodes disposed along the distal portion of the lead body, the electrodes including at least one segmented electrode; and an asymmetric marker disposed along the distal portion of the lead body and including a first ring and a longitudinal band extending longitudinally from the first ring. The asymmetric marker and lead body are formed of different materials that are distinguishable from each other in the radiological images to facilitate radiological determination of the rotational orientation of the lead when implanted. The marker may also include one or more of a longitudinal extension, a second ring, and non-straight longitudinal edges. The marker may also include the longitudinal band and longitudinal extension without a ring.

Abstract: A method for determining a set of stimulation parameters for an electrical stimulation lead or steering electrical stimulation includes receiving a target geometrical parameter describing a stimulation field; receiving a first programming state; determining a first stimulation parameter for the first programming state that achieves the target geometrical parameter within at least 10% of the target geometrical parameter; and outputting set of stimulation parameters to be received by an electrical stimulation device for delivery of electrical stimulation to a patient via an electrical stimulation lead, wherein the set of stimulation parameters comprises the first stimulation parameter and represents the first programming state. In other embodiments, the target geometrical parameter is determined from either i) a first set of stimulation parameters or ii) a starting programming state and starting first stimulation parameter.

Abstract: Method and systems for determining a set of stimulation parameters for an implantable stimulation device include receiving a set of stimulation parameters including at least one electrode for delivery of stimulation and a stimulation amplitude for each electrode; determining, using the set of stimulation parameters, an axial stimulation field for neural elements oriented axially with respect to a longitudinal axis of the lead; and outputting the first axial stimulation field for viewing by a user; receiving, by the computer processor. The methods and systems can be used to model other neural elements oriented non-orthogonally with respect to the longitudinal axis of the lead and determine a non-orthogonal stimulation field.

Abstract: An electrical stimulation system for use with a plurality of electrodes implanted within a tissue region comprises a neurostimulator configured for delivering electrical stimulation energy to the plurality of electrodes in accordance with a set of stimulation parameters, thereby injecting a charge into the tissue region, a control device configured for receiving user input to modify the set of stimulation parameters, and controller/processor circuitry configured for, in response to the user input computing a charge injection metric value as a function of a physical electrode parameter and an electrical source parameter for a first set of the electrodes, wherein the electrode set comprises at least two electrodes, comparing the computed charge injection metric value to a safety threshold value, and performing a corrective action based on the comparison.

Abstract: In various embodiments, the present system allows for custom definition of waveforms and waveform segments for neurotherapy. Such custom definition is achieved by using a waveform composer with a user interface that makes it possible for the user to perform the custom definition of potentially very complex patterns of neurostimulation waveforms by creating and editing graphical representations of relatively simple individual building blocks for each of the patterns.

Abstract: A computer implemented system and method provides a volume of activation (VOA) estimation model that receives as input two or more electric field values of a same or different data type at respective two or more positions of a neural element and determines based on such input an activation status of the neural element. A computer implemented system and method provides a machine learning system that automatically generates a computationally inexpensive VOA estimation model based on output of a computationally expensive system.

Abstract: An electrical stimulation system includes an electrical stimulation lead with at least one lead body, electrodes disposed along the distal end portion of the lead body(ies), terminals disposed along the proximal end portion of the lead body(ies), and conductors electrically coupling the terminals to the electrodes. The electrical stimulation system also includes a lead extension coupleable to the electrical stimulation lead. The lead extension includes a connector for receiving the proximal end portion of the electrical stimulation lead. The electrical stimulation system further includes a sheath defining a sheath lumen to slidingly receive a portion of the electrical stimulation lead or a portion of the lead extension or a portion of both the electrical stimulation lead and the lead extension. The sheath includes a flexible sheath body and an elongate RF shield disposed within the sheath body and extending along the sheath.

Abstract: An example of a system for delivering neurostimulation may include a display and an interface control circuit. The interface control circuit may be configured to define a stimulation waveform according to which the neurostimulation is delivered. The stimulation waveform is defined by waveform parameters including one or more user-adjustable parameters. The interface control circuit may include a parameter selector, an effect analyzer, and a parameter generator. The parameter selector may be configured to present values for each user-adjustable parameter on the display and allow the user to select a value for each user-adjustable parameter from the presented values. The effect analyzer may be configured to estimate an interactive effect of different stimuli of the neurostimulation. The parameter generator may be configured to select a rate rule based on the estimated interactive effect and to generate the values for each user-adjustable parameter according to the selected rate rule.

Abstract: An electrical stimulation system for use with a plurality of electrodes implanted within a tissue region comprises a neurostimulator configured for delivering electrical stimulation energy to the plurality of electrodes in accordance with a set of stimulation parameters, thereby injecting a charge into the tissue region, a control device configured for receiving user input to modify the set of stimulation parameters, and controller/processor circuitry configured for, in response to the user input computing a charge injection metric value as a function of a physical electrode parameter and an electrical source parameter for a first set of the electrodes, wherein the electrode set comprises at least two electrodes, comparing the computed charge injection metric value to a safety threshold value, and performing a corrective action based on the comparison.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation, and may include a region of interest (ROI) model representing a specified ROI including a neural target and divided into a plurality of sub-regions. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one neuronal network model.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The one or more neuronal network models may include a first pain model configured to allow for optimization of neurostimulation using paresthesia, the second pain model configured to allow optimization of neurostimulation using anatomy. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one or more of the first pain model or the second pain model.

Abstract: An example of a system for programming a neurostimulator may include storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks for a specified range of varying conditions using at least one neuronal network model.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one neuronal network model. The spatio-temporal pattern of neurostimulation may include a series of sub-patterns for treating an indication of the one or more indications for neuromodulation.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one neuronal network model.

Abstract: A computer implemented system and method provides a volume of activation (VOA) estimation model that receives as input two or more electric field values of a same or different data type at respective two or more positions of a neural element and determines based on such input an activation status of the neural element. A computer implemented system and method provides a machine learning system that automatically generates a computationally inexpensive VOA estimation model based on output of a computationally expensive system.