Cardiac Pacemakers, Inc.

Boston Scientific Neuromodulation Corporation

Boston Scientific Scimed, Inc.

Stephen B Ruble

Jason J Hamann

David J Ternes

Juan Gabriel Hincapie Ordonez

Pramodsingh Hirasingh Thakur

Weiying Zhao

Jeffrey E Stahmann

Quan Ni

Shantha Arcot-Krishnamurthy

Keith R Maile

Allan Charles Shuros

Craig Michael Stolen

Krzysztof Z Siejko

Ramesh Wariar

Manfred Franke

Jan Weber

Barun Maskara

Torsten Scheuermann

Barry Rudman

Imad Libbus

Andrew P Kramer

Qi An

Rafael Carbunaru

Anthony V Caparso

Bryan Allen Clark

Viktoria A Averina

Kristofer J James

Abhi Chavan

Kenneth L Baker

Arjun D Sharma

Robert Shipley

William Conrad Stoffregen

Rezwan Ahmed

Zhe Shen

Nicholas David Wold

Rahul Agarwal

Bradley Lawrence Hershey

Shibaji Shome

Stephen John Hahn

Bin Mi

Kevin John Stalsberg

Paul E Zarembo

Gary Thomas Seim

Scott R Vanderlinde

Eric A Mokelke

Kyle Harish Srivastava

Michael X Govea

Elizabeth Mary Annoni

David Blum

Amy Jean Brisben

Howard D Simms, Jr

Jonathan Bennett Shute

Paul F Emerson

Les Norman Peterson

Timothy Edward Meyer

Jack Gordon

Kevin J Mohsenian

Nicholas Wold

Jr Howard D Simms

Barry L Rudman

Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes a risk stratifier circuit configured to, in an absence of prior and present atrial arrhythmia, determine a composite risk of the patient developing a future atrial arrhythmia using a trained machine-learning model and a plurality of features of physiological information sensed from the patient and an arrhythmia monitor circuit configured to adjust an arrhythmia monitoring parameter based at least in part on the composite risk and to detect an atrial arrhythmia event using the adjusted arrhythmia monitoring parameter.

Systems and methods for predicting atrial arrhythmia

Systems, devices, and methods for monitoring and assessing blood glucose level in a patient are discussed. An exemplary system receives physiologic information from a patient using an ambulatory medical device. The physiologic information is correlated to, and different from, a direct glucose level measurement. The system determines a glucose index indicative of an abnormal blood glucose level using the received physiologic information by the two or more physiologic sensors. The system may use the glucose index to initiate or adjust a therapy, or to trigger a glucose sensor, separate from the two or more physiologic sensors, to directly measure blood glucose concentration.

Multi-sensor diabetes management system

An example of a method embodiment may include receiving a user programmable neural stimulation (NS) dose for an intermittent neural stimulation (INS) therapy, and delivering the INS therapy with the user programmable NS dose to an autonomic neural target of a patient. Delivering the INS therapy may include delivering NS bursts, and delivering the NS bursts may include delivering a number of NS pulses per cardiac cycle during a portion of the cardiac cycles and not delivering NS pulses during a remaining portion of the cardiac cycles. The method may further include sensing cardiac events within the cardiac cycles, and controlling delivery of the user programmable NS dose of INS therapy using the sensed cardiac events to time delivery of the number of NS pulses per cardiac cycle to provide the user programmable NS dose. The user programmable NS dose may determine the number of NS pulses per cardiac cycle.

Dosed delivery of autonomic modulation therapy

Systems and methods for assessing a cardiac arrhythmia risk of a patient, such as a risk for developing atrial fibrillation, are disclosed. An exemplary medical-device system includes an arrhythmia predictor circuit configured to receive physiologic information of a patient, and in an absence of atrial tachyarrhythmia in the patient, determine a risk of the patient developing future atrial tachyarrhythmia using the physiologic information. In accordance with the arrhythmia risk indication, the system can generate an alert, or initiate more aggressive monitoring of a patient identified as having a high atrial tachyarrhythmia risk.

A neurostimulation system provides for capture verification and stimulation intensity adjustment to ensure effectiveness of vagus nerve stimulation in modulating one or more target functions in a patient. In various embodiments, stimulation is applied to the vagus nerve, and evoked responses are detected to verify that the stimulation captures the vagus nerve and to adjust one or more stimulation parameters that control the stimulation intensity.

Methods and apparatus for adjusting neurostimulation intensity using evoked responses

According to various method embodiments, a person is indicated for a therapy to treat a cardiovascular disease, and the therapy is delivered to the person to treat the cardiovascular disease. Delivering the therapy includes delivering a vagal stimulation therapy (VST) to a vagus nerve of the person at a therapeutically-effective intensity for the cardiovascular disease that is below an upper boundary at which upper boundary the VST would lower an intrinsic heart rate during the VST.

Systems and methods for delivering vagal nerve stimulation

This document discusses, among other things, systems and methods for monitoring a patient at risk of epilepsy. A system comprises a sensor circuit that senses from the patient at least first and second physiological or functional signals. A wellness detector circuit can detect an epileptic event using the sensed physiological or functional signals, or additionally classify the epileptic event into one of epileptic seizure types. The system can generate a wellness indicator based on a trend of the physiological or functional signal during the detected epileptic event. The wellness indicator indicates an impact of the detected epileptic event on the health status of the patient. The system includes an output unit configured to output the detection of the epileptic event or the wellness indicator to a user or a process.

Methods and apparatus for monitoring epilepsy

A system includes an implantable medical device configured to sense a sync signal and sense physiological parameters to obtain a physiological signal. In response to sensing the sync signal, the implantable medical device is configured to generate a sync-stamped physiological signal. In certain embodiments, a method includes receiving a first physiological signal coupled with a sync signal; receiving a second physiological signal coupled with the sync signal; and, using the sync signal, synchronizing in time the first and second physiological signals.

Syncing multiple sources of physiological data

This document discusses, among other things, systems and methods to receive physiologic information of a patient, to receive pulse pressure information from the patient different than the received physiologic information, and to determine an indication of atrial fibrillation (AF) using the received physiologic information and the received pulse pressure information.

Pulse pressure variability

Methods and systems for selecting electrical stimulation parameters for an electrical stimulation device implanted in a patient can use an iterative process for identifying electrodes for stimulation, as well as suitable stimulation parameters. The process begins with an initial set of electrode combinations to identify regions of the nerve or other tissue for stimulation. This leads to selection of other electrode combinations to test, followed by the selection of multiple electrode groups (which can include three or more electrodes) for stimulation.

Methods and systems for selecting stimulation parameters for electrical stimulation devices

Intermittent delivery of ventricular pacing pulses synchronized to occur during an atrial diastole time period can be used to provide atrial stretch therapy and augment the production and release of atrial natriuretic hormone.

Ventricular pacing to augment atrial natriuretic hormone production

Embodiments of the disclosure include systems and methods for obtaining high-resolution data from implantable medical devices (IMDs) by triggering a limited-time system behavior change. For example, embodiments include utilizing study prescriptions for batching data obtained by an IMD, communicating the batched data to an external device, and reconstructing the batched data at the external device. Study prescriptions refer to sets of instructions, conditions, protocols, and/or the like, that specify one or more of an information gathering scheme and a communication scheme, and may be configured, for example, to obtain information at a resolution sufficient for performing a certain analysis (e.g., associated with a diagnostic model), while managing the resulting impact to device longevity and/or performance.

Obtaining high-resolution information from an implantable medical device

A medical device for reducing the volume of a left atrial appendage (LAA) may include an elongate shaft having a distal portion, and a volume-reducing means expandable from a collapsed to an expanded state, the volume-reducing means being releasably attached to the distal portion. The volume-reducing means may include an actuatable frame and an impermeable covering disposed over the frame. The volume-reducing means may be sized to fit within the LAA in the expanded state while maintaining an open fluid flow path from a distal region through the ostium of the LAA. A medical device may include a second volume-reducing means to be placed within and substantially occlude a distalmost region of the LAA. A method may include inserting a volume-reducing means into the LAA, expanding the volume-reducing means, and positioning the volume-reducing means such that an open fluid flow path is maintained through an entire cycle of the heart.

Centered balloon for the left atrial appendage

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Lino Lakes, MN, United States of America

Stephen B Ruble