Medtronic, Inc.

Other

David L Carlson

Jonathon E Giftakis

Jonathan C Werder

Nina M Graves

Touby Austin Drew

Eric J Panken

Mark G Frei

Ivan Osorio

Scott R Stanslaski

Timothy J Denison

Randy M Jensen

Mark Turner Rise

David E Linde

Gabriela C Molnar

Jianping Wu

Scott F Schaffner

William J Marks, Jr

Peng Cong

Benjamin P Isaacson

Keith Alan Miesel

Christopher L Pulliam

Gregory F Molnar

Duane L Bourget

Naresh C Bhavaraju

Thaddeus S Brink

Gabriela C Miyazawa

Pedram Afshar

Heather Diane Orser

Rene A Molina

Dale G Suilmann

Abbey Beuning Holt Becker

Kevin L Bright

Gregory J Loxtercamp

Nicholas D Buse

Kenneth J Gutzman

Chark Stanford

Ali H Shoeb

E Jonathon Giftakis

An example method includes determining, by an implantable medical device (IMD), an electrode of a plurality of electrodes of a lead to be used to deliver electrical stimulation to a patient at a particular time; selecting, by the IMD and based on the determined electrode, a set of electrodes of the plurality of electrodes; and sensing, by the IMD and via the selected set of electrodes, electrical signals of the patient at the particular time.

Dynamically optimized neural sensing

An example method for controlling delivery of electrical stimulation therapy includes maintaining, by one or more processors of a medical device configured to deliver electrical stimulation to a patient, a counter tied to a clock used by the medical device to deliver the electrical stimulation to the patient; and obtaining, by the one or more processors, one or more representations of sensed electrical signals for the patient that are referenced to counts of the counter. In this example, the method also includes identifying, based on the one or more representations of the sensed electrical signals for the patient, a count of the counter at which stimulation is to be delivered to the patient; and delivering, by the medical device and to the patient, electrical stimulation based on the identified count of the counter.

Precision delivery of electrical stimulation

An apparatus for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

Apparatus for data retention in an implantable medical device

Methods for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

Methods for data retention in an implantable medical device

Various embodiments concern identifying a biomarker in the presence of electrical stimulation. Various embodiments concern delivering electrical stimulation to a patient and sensing one or more signals while the electrical stimulation is being delivered, the one or more signals including data indicative of physiological activity. Various embodiments further include determining an intensity of the electrical stimulation and determining whether the data indicates the presence of a biomarker based on a variable threshold, the variable threshold being variable based on the intensity of the electrical stimulation. Various embodiments concern determining a relationship between stimulation intensity and a biomarker parameter to determine the variability of the variable threshold.

Method and apparatus for detecting a biomarker in the presence of electrical stimulation

This disclosure describes techniques for controlling spectral aggressors in a sensing device that uses a chopper amplifier to amplify an input signal prior to sampling the signal. In some examples, the techniques for controlling spectral aggressors may include generating a chopper-stabilized amplified version of an input signal based on a chopper frequency, sampling the chopper-stabilized amplified version of the input signal at a sampling rate to generate a sampled signal, and analyzing a target frequency band of the sampled signal. The chopper frequency and the sampling rate may cause spectral interference that is generated due to the chopper frequency to occur in the sampled signal at one or more frequencies that are outside of the target frequency band of the sampled signal. The techniques for controlling spectral aggressors may reduce the noise caused by the chopper frequency in the resulting sampled signal, thereby improving the quality of the signal.

Control of spectral agressors in a physiological signal monitoring device

This disclosure describes techniques for controlling spectral aggressors in a sensing device that uses a low power sleep mode to manage the power consumed by the device. In some examples, the techniques for controlling spectral aggressors may include configuring one or more of an algorithm processing rate for a processor, a buffering rate for the processor, a sampling rate for an analog-to-digital converter, an execution unit processing rate for the processor, and an algorithm subdivision factor for the processor such that spectral interference caused by a sleep cycle rate of the processor occurs outside of one or more target frequency bands of a sampled signal. The techniques of this disclosure may be used to reduce noise in a sensing system that uses a low power sleep mode to manage the power consumed by the device.

Control of spectral agressors in a physiological signal montoring device

Methods and apparatus for storing data records associated with a medical monitoring event in a data structure. These include initiating loop recording in an implantable medical device upon determination of a neurological event, wherein loop recording comprises storing a data record of a plurality of data records in a data structure, the plurality of data records representing information about determined neurological events. Methods and apparatus can further include determining a priority index for the plurality of data records based on severity levels of the determined neurological events and replacing older data records of the plurality of data records on the data structure with new data records according to the priority index, wherein the new data records selectively replace those data records in the data structure having the lowest associated priority index.

Techniques for data retention upon detection of an event in an implantable medical device

This disclosure describes a state machine framework for programming closed-loop algorithms that control the delivery of therapy to a patient by an implantable medical device (IMD). The state machine framework may use one or more programmable state parameters to define at least part of a structure of a state machine that generates one or more therapy decisions based on one or more sensed states of the patient. The state machine framework may include a state machine runtime environment that executes on an IMD and that is configurable to implement a variety of different state machines depending on programmable state parameters that are received from an external device. The techniques of this disclosure may, in some cases, allow IMD developers and/or users to program, change, and/or download new closed-loop control policy algorithms during the lifespan of the IMD without requiring new firmware code to be downloaded onto the IMD.

State machine framework for programming closed-loop algorithms that control the delivery of therapy to a patient by an implantable medical device

Apparatus and method detect a detection cluster that is associated with a neurological event, such as a seizure, of a nervous system disorder and update therapy parameters that are associated with a treatment therapy. The occurrence of the detection cluster is detected when the maximal ratio exceeds an intensity threshold. If the maximal ratio drops below the intensity threshold for a time interval that is less than a time threshold and subsequently rises above the intensity threshold, the subsequent time duration is considered as being associated with the detection cluster rather than being associated with a different detection cluster. Consequently, treatment of the nervous system disorder during the corresponding time period is in accordance with one detection cluster. Treatment therapy may be provided by providing electrical stimulation, drug infusion or a combination. Therapy parameters may be updated for each msuccessive group of applications of the treatment therapy or for each ndetection cluster.

Clustering of recorded patient neurological activity to determine length of a neurological event

Bioelectrical signals may be sensed within a brain of a patient with a plurality of sense electrode combinations. A stimulation electrode combination for delivering stimulation to the patient to manage a patient condition may be selected based on the frequency band characteristics of the sensed signals. In some examples, a stimulation electrode combination associated with the sense electrode combination that sensed a bioelectrical brain signal having a relatively highest relative beta band power level may be selected to deliver stimulation therapy to the patient. Other frequency bands characteristics may also be used to select the stimulation electrode combination.

Stimulation electrode selection

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Fridley, MN, United States of America

David L Carlson