Boston Scientific Neuromodulation Corporation

Lowe Graham Jones Pllc

Stephen Carcieri

Michael A Moffitt

Dean Chen

Hemant Bokil

Peter J Yoo

Richard Mustakos

G Karl Steinke

Sridhar Kothandaraman

Tianhe Zhang

Changfang Zhu

Chirag Shah

Juan Gabriel Hincapie Ordonez

Keith R Carlton

Jianwen Gu

Natalie A Brill

Dennis Allen Vansickle

Michael Andrew Caruso

Vikrant Venkateshwar Gunna Srinivasan

Micahel A Moffitt

Jordi Parramon

Rafael Carbunaru

Anne Margaret Pianca

Goran Nils Marnfeldt

Bradley Lawrence Hershey

John Rivera

Harold Haut

Ljubomir Manola

Emarit Ranu

An example of a system may include a processor and a memory device comprising instructions, which when executed by the processor, cause the processor to: access a patient metric of a subject; use the patient metric as an input to a machine learning algorithm, the machine learning algorithm to search a plurality of neuromodulation parameter sets and to identify a candidate neuromodulation parameter set of the plurality of neuromodulation parameter sets, the candidate neuromodulation parameter set designed to produce a non-regular waveform that varies over a time domain and a space domain; and program a neuromodulator using the candidate neuromodulation parameter set to stimulate the subject.

Machine learning to optimize spinal cord stimulation

A system and method for selecting leadwire stimulation parameters includes a processor iteratively performing, for each of a plurality of values for a particular stimulation parameter, each value corresponding to a respective current field: (a) shifting the current field longitudinally and/or rotationally to a respective plurality of locations about the leadwire; and (b) for each of the respective plurality of locations, obtaining clinical effect information regarding a respective stimulation of the patient tissue produced by the respective current field at the respective location; and displaying a graph plotting the clinical effect information against values for the particular stimulation parameter and locations about the leadwire, and/or based on the obtained clinical effect information, identifying an optimal combination of a selected value for the particular stimulation parameter and selected location about the leadwire at which to perform a stimulation using the selected value.

Point-and-click programming for deep brain stimulation using real-time monopolar review trendlines

An example of a system for delivering neurostimulation may include a programming control circuit and a stimulation control circuit. The programming control circuit may be configured to generate stimulation parameters controlling delivery of the neurostimulation according to a stimulation configuration. The stimulation control circuit may be configured to specify the stimulation configuration, and may include volume definition circuitry and stimulation configuration circuitry. The volume definition circuitry may be configured to determine one or more test volumes, determine a clinical effect resulting from the one or more test volumes each being activated by the neurostimulation, and determine a target volume using the determined clinical effect. The stimulation configuration circuitry may be configured to generate the specified stimulation configuration for activating the target volume.

Method and apparatus for clinical effects-based targeting of neurostimulation

Methods and systems can facilitate identifying effective electrodes and other stimulation parameters, as well as determining whether to use cathodic and anodic stimulation. Alternately, the methods and systems may identify effective electrodes and other stimulation parameters based on preferential stimulation of different types of neural elements. These methods and systems can further facilitate programming an electrical stimulation system for stimulating patient tissue.

Multi-mode electrical stimulation systems and methods of making and using

A system for adjusting neuromodulation parameters used by a neuromodulator operably connected to a plurality of electrodes to modulate a neural target, may comprise a translation trigger detector configured to determine that a translation trigger has occurred, a first parameter setting storage configured to store first parameter settings for use by the neuromodulator to modulate the neural target, and a neuromodulation parameter translator. The neuromodulation parameter translator may be operably connected to the translation trigger detector to automatically translate the first parameter settings into a second parameter settings in response to determining the translation trigger has occurred, and replace the first parameter settings with the second parameter settings, or store the second parameter settings in a second parameter setting storage. Automatically translating may include either automatically translating from cathodic parameter settings to anodic parameter settings, or automatically translating from anodic parameter settings to cathodic parameter settings.

Translation between cathodic and anodic neuromodulation parameter settings

A computer implemented system and method facilitates a cycle of generation, sharing, and refinement of volumes related to stimulation of anatomical tissue, such as brain or spinal cord stimulation. Such volumes can include target stimulation volumes, side effect volumes, and volumes of estimated activation. A computer system and method also facilitates analysis of groups of volumes, including analysis of differences and/or commonalities between different groups of volumes.

Systems and methods for stimulation-related biological circuit element analysis and use

Systems and methods for stimulation-related volume analysis of therapeutic effects and other clinical indications

Methods and systems can facilitate visualizing cathodic and anodic stimulation separately via displaying and modifying graphical representations of anodic and cathodic volumes of activation. Alternately, the methods and systems may separately visualize stimulation of different neural elements, such as nerve fibers and neural cells. These methods and systems can further facilitate programming an electrical stimulation system for stimulating patient tissue.

Systems and methods for visualizing and programming electrical stimulation

An example of a system for delivering neurostimulation may include a programming control circuit and a user interface. The programming control circuit may be configured to generate stimulation parameters controlling delivery of neurostimulation pulses according to one or more stimulation waveforms associated with areas of stimulation each defined by a set of electrodes. The neurostimulation pulses are each delivered to an area of stimulation. The user interface may include a display screen and an interface control circuit. The interface control circuit may be configured to define the one or more stimulation waveforms and the areas of stimulation, and may include a stimulation frequency module configured to display a stimulation rate table on the display screen. The stimulation rate table may present stimulation frequencies associated with each of the areas of stimulation for selection by a user.

Method and apparatus for programming neuromodulation devices

Methods and systems can facilitate visualizing cathodic and anodic stimulation separately. Alternately, the methods and systems may separately visualize stimulation of different neural elements, such as nerve fibers and neural cells. These methods and systems can further facilitate programming an electrical stimulation system for stimulating patient tissue.

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Los Angeles, CA, United States of America

Stephen Carcieri