Medtronic, Inc.

Robert S Raike

Scott R Stanslaski

Timothy R Abraham

Thomas Adamski

Christopher L Pulliam

Timothy J Denison

Rene A Molina

Jonathon E Giftakis

David E Linde

Thomas L Chouinard

Eric J Panken

Paul H Stypulkowski

Jadin C Jackson

Timothy Denison

Benjamin P Isaacson

Abbey Beuning Holt Becker

Michelle A Case

Mae Eng

Paula Andrea Elma Dassbach Green

Duane L Bourget

Jianping Wu

Yizi Xiao

Jeffrey Herron

Nicholas D Buse

Caleb C Zarns

Techniques are disclosed for delivering electrical stimulation therapy to a patient. In one example, a medical system delivers electrical stimulation therapy to a tissue of the patient via electrodes. The medical system determines a first change of a first sensed signal of the patient to movement by the patient and a second change of a second sensed signal of the patient to the movement by the patient. Based on the first change and the second change, the medical system selects one of the first sensed signal and the second sensed signal of the patient for controlling the electrical stimulation therapy. The medical system adjusts a level of at least one parameter of the electrical stimulation therapy based on the selected one of the first sensed signal and the second sensed signal.

Adaptive deep brain stimulation using movement desynchronization

Devices, systems, and techniques for identifying electrodes closest to a target region of tissue are described. In one example, a device includes sensing circuitry configured to sense electrical signals from a plurality of electrode combinations. Processing circuitry identifies a first electrode combination of a first subset of electrode combinations. Each electrode combination of the first subset of electrode combination includes electrodes located at different axial positions along a length of the medical lead. The processing circuitry identifies a second electrode combination of a second subset of electrode combinations. Each electrode combination of the second subset of electrode combinations includes electrodes located at a same axial position and different circumferential positions around a perimeter of the medical lead. The processing circuitry then determines a third electrode combination and controls delivery of electrical stimulation via the third electrode combination.

Directional sensing for programming guidance

A medical device for providing electrical stimulation to a brain of a patient includes one or more processors. The one or more processors are configured to determine a first set of parameters of a first electrical signal that is delivered via a first electrode configured to apply electrical stimulation to a first region of the brain and to determine a second set of parameters of a second electrical signal based on the first set of parameters. The second electrical signal is delivered via a second electrode configured to apply electrical stimulation to a second region of the brain. The one or more processors are further configured to deliver, with the first electrode, the first electrical signal having the first set of parameters and to deliver, with the second electrode, the second electrical signal having the second set of parameters.

Electrical stimulation therapy

Systems and methods that automatically adjust, or adapt, stimulation waveforms delivered to brain structures. Closed loop system embodiments can automatically be re-configured into a more suitable closed loop control system in response to measures of control system performance. Measures can be internal performance characteristics of the adaptive control system or external inputs provided by another subsystem. As these measures change in time, the robust adaptive system changes in response.

Robust adaptive brain stimulation

Techniques are disclosed for delivering electrical stimulation therapy to a patient. In one example, a medical system delivers electrical stimulation therapy to a tissue of the patient via electrodes. The medical system determines a first response of a first sensed signal of the patient to the electrical stimulation therapy and a second response of a second sensed signal of the patient to the electrical stimulation therapy. Based on the first response and the second response for controlling the electrical stimulation therapy, the medical system selects one of the first sensed signal and the second sensed signal of the patient. The medical system adjusts a level of at least one parameter of the electrical stimulation therapy based on the selected one of the first sensed signal and the second sensed signal.

Adaptive deep brain stimulation using frequency sub-bands

A medical device or system of medical devices can be configured to detect an indicator of a symptom in a patient; in response to detecting the indicator of the symptom in the patient, deliver to the patient a first stimulation therapy; and in response to determining that the indicator of the symptom has been present for more than a threshold amount of time after beginning to deliver the first stimulation therapy a second stimulation therapy different than the first stimulation therapy.

Multi-target adaptive neurostimulation therapy control

In some examples of selecting a target therapy delivery site for treating a patient condition, a relatively high frequency electrical stimulation signal is delivered to at least two areas within a first region (e.g., an anterior nucleus of the thalamus) of a brain of a patient, and changes in brain activity (e.g., as indicated by bioelectrical brain signals) within a second region (e.g., a hippocampus) of the brain of the patient in response to the delivered stimulation are determined. The target therapy delivery site, an electrode combination, or both, may be selected based on the changes in brain activity.

Identification of compromised components in a medical system

Techniques, systems, and devices are disclosed for delivering stimulation therapy to a patient. In one example, a medical device determines a first set of stimulation parameters that define entrainment stimulation pulses configured to entrain electrical activity in a patient. The medical device may control a stimulation generator to generate the entrainment stimulation pulses according to the first set of stimulation parameters. The medical device may further determine a second set of stimulation parameters that define at least one desynchronization stimulation pulse configured to disrupt at least a portion of the electrical activity entrained by the entrainment stimulation pulses. The medical device may subsequently control the stimulation generator to generate the desynchronization stimulation pulse(s) according to the second set of stimulation parameters.

Electrical stimulation modulation

Systems and methods that automatically adjust, or adapt, stimulation waveforms delivered to brain structures. Closed loop system embodiments can automatically be reconfigured into a more suitable closed loop control system in response to measures of control system performance. Measures can be internal performance characteristics of the adaptive control system or external inputs provided by another subsystem. As these measures change in time, the robust adaptive system changes in response.

Techniques are described determining electrodes that are proximate or distal to location of an oscillatory signal source in a patient based on current source densities (CSDs). Processing circuitry may determine, for one or more electrodes of a plurality of electrodes, respective time-varying measurements of CSDs, aggregate, for the one or more electrodes of the plurality electrodes, the respective time-varying measurements of the CSDs to generate respective average level values for the one or more electrodes of the plurality of electrodes, determine, for one or more electrodes of the plurality of electrodes, respective phase-magnitude representations of the time-varying measurements of the CSDs. The respective phase-magnitude representations are indicative of respective magnitudes and phases of a particular frequency component of respective time-varying measurements of the CSDs. The particular frequency component is a frequency component having a largest transform coefficient in a time-varying measurement of a CSD having a largest average level value.

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Minneapolis, MN, United States of America

Robert S Raike