Boston Scientific Neuromodulation Corporation

Neuropace, Inc.

University of Pennsylvania

Georgia Tech Research Corporation

Rosana Esteller

Tianhe Zhang

Jianwen Gu

Michael A Moffitt

Que T Doan

Ismael Huertas Fernandez

Felice Sun

Natalie A Brill

Brian Litt

George J Vachtsevanos

Pramodsingh Hirasingh Thakur

Joseph M Bocek

Bryan Allen Clark

Kyle Harish Srivastava

Elizabeth Mary Annoni

Jessica Block

Adam Lee

Rafael Carbunaru

Andrew James Haddock

Javier Ramón Echauz

Goran Nils Marnfeldt

Changfang Zhu

Deepa Mahajan

Bhaskar Sen

Jordi Parramon

David J Ternes

David L Perschbacher

Sridhar Kothandaraman

Michael X Govea

Pujitha Weerakoon

Kiran K Gururaj

David Michael Wagenbach

James John Kleinedler

Mahsa Malekmohammadi

Pranjali Borkar

Javier Ram&oacute;n Echauz

Qi An

Bradley Lawrence Hershey

Thomas W Stouffer

Raul Enrique Serrano Carmona

Adam Thomas Featherstone

Gezheng Wen

Javier Echauz

Matthew Lee Mcdonald

Luca A Annecchino

Thien Tich Doan

Adarsh Jayakumar

Venugopal Allavatam

Nataile A Brill

An example of a system for delivering neurostimulation and sensing one or more signals may include a programming control circuit and a parameter control circuit. The programming control circuit may be configured to control the delivery of the neurostimulation according to stimulation parameters and the sensing of a target neural signal including target neural responses according to sensing parameters. The parameter control circuit may be configured to determine the stimulation parameters and the sensing parameters and may include a recording analyzer. The recording analyzer may be configured to evaluate a sequence of test recording configurations each including a set of recording configuration parameters selected from the stimulation parameters and the sensing parameters and to determine one or more recording configurations suitable for detection of the target neural responses using an outcome of the evaluation.

Method and apparatus for optimizing neural sensing

Systems and methods for closed-loop control of electrostimulation while avoiding, or maintaining a substantially low level of, evoked neural activity are disclosed. A system comprises an electrostimulator to deliver a stimulation pulse train, a sensing circuit to sense evoked responses to respective pulses in the pulse train, and a controller to detect an evoked neural activity from an averaged evoked response by averaging evoked responses to respective pulses. The averaging operation can be controlled by a noise level of the averaged evoked response, or by a count of epochs (pulses) being used for averaging. Responsive to the evoked neural activity satisfying a detection criterion, the controller recursively adjusts stimulation parameters until the detection criterion is no longer satisfied. The electrostimulator delivers electrostimulation according to the recursively adjusted stimulation parameters.

Closed loop stimulation based on response avoidance

Methods and systems for testing and treating spinal cord stimulation (SCS) patients are disclosed. Patients are eventually treated with sub-perception (paresthesia free) therapy. However, supra-perception stimulation is used during 'sweet spot searching' during which active electrodes are selected for the patient. This allows sweet spot searching to occur much more quickly and without the need to wash in the various electrode combinations that are tried. After selecting electrodes using supra-perception therapy, therapy is titrated to sub-perception levels using the selected electrodes. Such sub-perception therapy has been investigated using pulses at or below 10 kHz, and it has been determined that a statistically significant correlation exists between pulse width (PW) and frequency (F) in this frequency range at which SCS patients experience significant reduction in symptoms such as back pain. Beneficially, sub-perception stimulation at such low frequencies significantly lowers power consumption in the patient's neurostimulator.

Paresthesia-free spinal cord stimulation occurring at lower frequencies and sweet spot searching using paresthesia

Methods and systems for providing electrical stimulation to a patient's spinal cord using electrode leads implanted in the patient's spinal column are described. Embodiments involve cycling between durations during which stimulation is actively applied and durations when no stimulation is applied. The stimulation can be configured such that pain relief washes in during the active stimulation duration and continues for some part of the duration when no stimulation is being applied. Eventually the pain relief may wash out. The washout time may be modeled, so that stimulation may be resumed before the pain relief washes out. The stimulation may be below the patient's perception threshold.

System and method for adaptive neural stimulation

This document discusses, among other things, systems and methods for providing pain relief to a patient. Recording circuitry may receive electrical signals corresponding to evoked compound action potentials in the patient that may be produced in response to external stimulation of a location where the patient is experiencing pain. The received electrical signals may be stored in a memory. Internal stimulation may then be applied to the patient and control circuitry may receive electrical signals corresponding to evoked compound action potentials in the patient that may be produced in response to the internal stimulation. The control circuitry may then adjust electrical parameters of the internal stimulation, such as to reduce a difference between the electrical signals corresponding to evoked compound action potentials produced in response to the internal stimulation and electrical signals corresponding to evoked compound action potentials produced in response to the external stimulation.

Systems and methods for determining neuromodulation parameters

An example of a system for delivering neurostimulation to a patient and controlling the delivery of neurostimulation using sensors may include a stimulation output circuit, a sensing circuit, and a control circuit. The stimulation output circuit may be configured to deliver the neurostimulation. The sensing circuit may be configured to receive sensed signals from the sensors and to process the sensed signals. The sensing circuit has adjustable settings controlling the processing of the sensed signals. The control circuit may be configured to control the delivery of the neurostimulation using the processed sensed signals and to control the settings of the sensing circuit according to a sequence of sensing blocks each including a set of sensing parameters.

Method and apparatus for sequencing sensing blocks for neuromodulation

An example method for delivering neurostimulation energy may include performing a training procedure by delivering the neurostimulation energy to a neural target of the patient when the patient is at one or more postures. Electrical activity is sensed from the spinal cord, such as an electrospinogram (ESG). A relationship is determined between the sensed electrical activity and neurostimulation intensity that reduces influence of noise in the sensed electrical activity caused by dynamically changing posture of the patient using mathematical or statistical modeling of the extracted features. Stimulation parameters are modulated according to the determined relationship.

Systems for noise-sensitive patient-specific adjustments of neuromodulation parameters

An example of a neurostimulation system may include a storage device for storing data representing physiological signals and a user interface including a user input, a display screen, and a presentation control circuit. The user input may be configured to receive a selection of signal(s) from the physiological signals and a selection of viewing mode from viewing modes including a metric mode and/or a presence mode. The metric mode allows for visualization of a signal property indicated by a parameter measured from the selected signal(s). The presence mode allows for viewing presence of a feature in the selected signal(s). The presentation control circuit may be configured to allow for the selection of the signal(s) and the viewing mode, to determine a segment of each of the selected signal(s) for presentation according to the selected viewing mode, and to present the determined segment on the display screen.

User interface for neural signal and biomarker visualization and assessment

Methods and systems for providing closed loop control of stimulation provided by an implantable stimulator device are disclosed herein. The disclosed methods and systems use a neural feature prediction model to predict a neural feature, which is used as a feedback control variable for adjusting stimulation. The predicted neural feature is determined based on one or more signals from an accelerometer configured in contact with the patient. The disclosed methods and systems can be used to provide closed loop feedback in situations, such as sub-perception therapy, when neural features cannot be readily directly measured.

Closed loop control in spinal cord stimulation therapy with non-detectable neural responses

Methods and systems for programming stimulation parameters for an implantable medical device for neuromodulation, such as spinal cord stimulation (SCS) are disclosed. The stimulation parameters define user-configured waveforms having at least a first phase having a first polarity and a second phase having a second polarity, wherein the first and second phases are separated by an interphase interval (IPI). By delivering user-configured waveforms with different IPIs, stimulation geometry, and other waveform settings, therapeutic asynchronous activation of dorsal column fibers can be obtained.

Stimulation configuration variation to control evoked temporal patterns

An initial set of parameters for operating one or more detection tools is automatically derived and subsequently adjusted so that each detection tool is more or less sensitive to signal characteristics in a region of interest. Detection tool(s) may be applied to physiological signals sensed from a patient (such as EEG signals) and may be configured to run in an implanted medical device that is programmable with the parameters to look for rhythmic activity, spiking, and power changes in the sensed signals, etc. A detection tool may be selected and parameter values derived in a logical sequence and/or in pairs based on a graphical representation of an activity type which may be selected by a user, for example, by clicking and dragging on the graphic via a GUI. Displayed simulations allow a user to assess what will be detected with a derived parameter set and then to adjust the sensitivity of the set or start over as desired.

Methods and systems for automatically identifying detection parameters for an implantable medical device

An example of a system for delivering neurostimulation energy to a patient using a plurality of electrodes may include a stimulation circuit and a sensing circuit. The stimulation circuit may be configured to deliver the neurostimulation energy using stimulation electrodes selected from the plurality of electrodes and to control the delivery of the neurostimulation energy. The sensing circuit may be configured to receive one or more neural signals from sensing electrodes selected from the plurality of electrodes and may include a signal processing circuit. The signal processing circuit may include a detection circuit and an analysis circuit. The detection circuit may be configured to detect one or more attributes of neural responses from the received one or more neural signals. The analysis circuit may be configured to analyze the detected one or more attributes of the neural responses for one or more indications of a neurodegenerative disease.

Neurostimulation system with neurodegenerative disease detection

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

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Santa Clarita, CA, United States of America

Rosana Esteller