Boston Scientific Neuromodulation Corporation

Other

Changfang Zhu

Michael A Moffitt

Bradley Lawrence Hershey

Dongchul Lee

Que T Doan

Jordi Parramon

Sridhar Kothandaraman

Natalie A Brill

Stephen Carcieri

Kerry A Bradley

Rosana Esteller

Tianhe Zhang

Juan Gabriel Hincapie Ordonez

Hemant Bokil

Jianwen Gu

Ismael Huertas Fernandez

Christopher Ewan Gillespie

David K L Peterson

Dennis Zottola

Sarvani Grandhe

Dheerendra Raghavendra Kashyap

Rafael Carbunaru

Goran Nils Marnfeldt

G Karl Steinke

Dennis Allen Vansickle

Jessica Block

John Rivera

Justin Holley

Nazim Wahab

Bradley L Hershey

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 the neurostimulation according to a pulse sequence. The pulse sequence may include a series of neurostimulation pulses and be defined by sequence parameters and one or more modulation functions each modulating an adjustable parameter selected from the sequence parameters. The user interface may be configured to set the pulse sequence to a tonic pulse sequence by determining an initial value for each adjustable parameter and set the pulse sequence to a modulated pulse sequence by selecting one or more adjustable parameters, determining a modulation function for each selected adjustable parameter, and applying the determined modulation function to that selected adjustable parameter to modulate the tonic pulse sequence.

Method and apparatus for generating modulated neurostimulation pulse sequence

An electrical stimulation system includes at least one electrical stimulation lead, each of the at least one electrical stimulation lead including a plurality of stimulation electrodes; and a processor coupled to the lead and configured to perform actions, including: directing delivery of at least one electrical pulse through at least one of the stimulation electrodes of the at least one electrical stimulation lead to tissue of a patient; and directing discrete or intermittent measurement of an electrical characteristic of the tissue using at least one of the stimulation electrodes of the at least one electrical stimulation lead during, and after, delivery of the at least one electrical pulse to the tissue of the patient.

Methods and systems for discrete measurement of electrical characteristics

Methods, system, and computer-implementable algorithms are disclosed for determining time-varying pulses for a patient having an implantable stimulator device (ISD). At least one time-invariant tonic stimulation pulse parameter (e.g., amplitude, pulse width, or frequency) is modified by a modulation function to produce time-varying pulses (TVPs), and one or more measurements are taken to determine the effectiveness of the TVP. The measurements may be objective and taken from the patient, and/or subjective and determined based on feedback from the patient. In one example, objective measurements may comprise one or more features determined from an electrospinogram (ESG) signal detected by the ISD, which may include evoked compound action potentials The one or more measurements are used to determine a score for the TVP, which is useful in selecting a best TVP for use with the patient, or for adjusting the modulation function applied to the tonic stimulation parameters.

Assessment and adjustment of time-varying pulse patterns in a spinal cord stimulator system

An example of a system may include an electrode arrangement and a neuromodulation device configured to use electrodes in the electrode arrangement to generate a neuromodulation field. The neuromodulation device may include a neuromodulation generator, a neuromodulation control circuit and a storage. The storage may include a stochastically-modulated neuromodulation parameter set and the stochastically-modulated neuromodulation parameter set may include at least one stochastically-modulated parameter. The controller may be configured to control the neuromodulation generator using the stochastically-modulation parameter set to generate the neuromodulation field.

Neuromodulation using a parameter distribution

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

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 at least one of: patient input, clinician input, or automatic input, use the patient input, clinician input, or automatic input in a search method. The search method may be designed to evaluate a plurality of candidate neuromodulation parameter sets to identify an optimal neuromodulation parameter set and to program a neuromodulator using the optimal neuromodulation parameter set to stimulate a patient.

Automated program optimization

An Implantable Pulse Generator (IPG) is disclosed that is capable of sensing a degree to which recruited neurons in a patient's tissue are firing synchronously, and of modifying a stimulation program to promote desynchronicity and to reduce paresthesia. An evoked compound action potential (ECAP) of the recruited neurons is sensed as a measure of synchronicity by at least one non-active electrode. An ECAP algorithm operable in the IPG assesses the shape of the ECAP and determines one or more ECAP shape parameters that indicate whether the recruited neurons are firing synchronously or desynchronously. If the shape parameters indicate significant synchronicity, the ECAP algorithm can adjust the stimulation program to promote desynchronous firing.

Pulse generator system for promoting desynchronized firing of recruited neural populations

A neuromodulation system comprises a plurality of electrical terminals configured for being respectively coupled to a plurality of electrodes, a user interface configured for receiving input from a user that selects one of a plurality of different shapes of a modulating signal and/or selects one of a plurality of different electrical pulse parameters of an electrical pulse train, neuromodulation output circuitry configured for outputting an electrical pulse train to the plurality of electrical terminals, and pulse train modulation circuitry configured for modulating the electrical pulse train in accordance with the selected shape of the modulating signal and/or selected electrical pulse parameter of the electrical pulse train.

Neuromodulation using modulated pulse train

An example of a system to program a neuromodulator to deliver neuromodulation to a neural target using a plurality of electrodes may comprise a programming control circuit configured to determine target energy allocations for the plurality of electrodes based on at least one target pole to provide a target sub-perception modulation field, and normalize the target sub-perception modulation field, including determine a time domain scaling factor to account for at least one property of a neural target or of a neuromodulation waveform, and apply the time domain scaling factor to the target energy allocations.

Sub-perception calibration using time domain scaling

A method is disclosed for programming a patient's stimulator device using an external device. The method provides a Graphical User Interface (GUI) on the external device that allows the patient to select from a plurality of displayed stimulation modes to program stimulation provided by one or more electrodes of the stimulator device. The external device stores a model derived for the patient, which model comprises information indicative of a plurality of frequency/pulse width/amplitude coordinates predicted to provide optimal stimulation for the patient. Each stimulation mode corresponds with a subset of coordinates defined in accordance with the plurality of coordinates in the model. Selection of one of the stimulation modes limits programming the stimulator device with coordinates that are within the corresponding subset of coordinates.

Stimulation modes to adapt customized stimulation parameters for use in a spinal cord stimulation system

An example of a system for modulating neuroinflammation at a tissue site in a patient includes a neuromodulation output circuit, a memory, and a control circuit. The neuromodulation output circuit may be configured to deliver the neuromodulation. The memory may be configured to store a neuromodulation parameter set selected to modulate neural activity at the tissue site and a sensed biomarker parameter. The biomarker parameter may include a measure of a biomarker or a measure of a derivative of the biomarker. The biomarker may be indicative of the neuroinflammation at the tissue site. The control circuit may be configured to control the delivery of the neuromodulation using the neuromodulation parameter set and adjust one or more parameters of the neuromodulation parameter set using the biomarker parameter.

Neuromodulation for neuroinflammation treatments with parameters controlled using biomarkers

Methods for determining stimulation for a patient having a stimulator device are disclosed. A model is received at an external system indicative of a range or volume of preferred stimulation parameters, which model is preferably specific to and determined for the patient. The external system receives a plurality of pieces of fitting information for the patient, including information indicative of a symptom of the patient, information indicative of stimulation provided by the stimulator device during a fitting procedure, and/or phenotype information for the patient. The external system determines one or more sets of stimulation parameters for the patient using the pieces of fitting information. In one example, training data is applied to the pieces of fitting information to select the one or more sets of stimulation parameters from the range or volume of preferred stimulation parameters in the model.

Fitting algorithm to determine best stimulation parameter from a patient model in a spinal cord stimulation system

Methods and systems for providing neuromodulation to a patient are disclosed. The disclosed methods and systems use sensed neural responses to construct and optimize models of the neural elements recruited during the neuromodulation. The models are used to estimate neural recruitment associated with a therapeutic effect and/or with side-effects to stimulation. The models can be used to adjust neuromodulation in a closed-loop fashion.

Neural stimulation with decomposition of evoked compound action potentials

An example of a system may include electrodes on at least one lead configured to be operationally positioned for use in modulating a volume of neural tissue, where the neural tissue has an activation function. The system may further include a neural modulation generator configured to deliver energy using at least some electrodes to generate a modulation field within the volume of neural tissue. The neural modulation generator may be configured to use a programmed modulation parameter set to generate the modulation field. The programmed modulation parameter set having values selected to control energy delivery using the at least some electrodes to achieve an objective function specific to the activation function of the volume of neural tissue to promote uniformity of a response to the modulation field in the volume of neural tissue along a span of the at least one lead.

Growing community of inventors

Valencia, CA, United States of America

Changfang Zhu