Medtronic, Inc.

Bruce D Gunderson

Amisha Somabhai Patel

Mark L Brown

Chad A Bounds

Walter H Olson

Robert W Stadler

Karen J Kleckner

Kevin T Ousdigian

Marshall S Stanton

Avram Scheiner

Eduardo N Warman

Jian L Cao

Troy Edward Jackson

Charles Dennis Swerdlow

Julian Sanchez

Jennifer P Miller

Ya-Jian Cheng

ShaileshKumar V Musley

Donald James Ruzin

Jeffrey M Gillberg

James D Reinke

Xiaohong Zhou

William John Havel

Li Ping Wang

Catherine R Condie

David Arthur Casavant

Edwin G Duffin

Kevin A Wanasek

Gautham Rajagopal

Mirko De Melis

Ravi Xavier

Sara M Hoeppner

Goran Jancevski

Robert F Collins

Gillberg M Jeffrey

Jay M Wilcox

Li Wang

Donald Ruzin

Tony E Jackson

A medical device system that includes accelerometer circuitry configured to generate signals including a sagittal axis signal, a vertical axis signal and a transverse axis signal, and processing circuitry configured to calculate a patient-specific functional status parameter associated with a Sit-To-Stand test from at least one of the sagittal axis signal, the vertical axis signal and the transverse axis signal.

Accelerometer signal change as a measure of patient functional status

This disclosure is directed to devices, systems, and techniques for monitoring a patient condition. In some examples, a medical device system includes processing circuitry configured to determine a plurality of pulse transit time (PTT) intervals, determine, based on an accelerometer signal, a posture of a patient from a plurality of postures corresponding to each PTT interval of the plurality of PTT intervals, classify each PTT interval of the plurality of PTT intervals based on the respective posture of the patient corresponding to the respective PTT interval, and monitor, based on the classified plurality of PTT intervals, a patient condition.

Performing one or more pulse transit time measurements based on an electrogram signal and a photoplethysmography signal

An example medical device system and method includes accelerometer circuitry configured to generate at least one signal, a memory, and processing circuitry coupled to the accelerometer circuitry and the memory. The processing circuitry is configured to determine a first plurality of pulse transit times (PTTs), determine, based on the at least one accelerometer signal, a Sit-to-Stand transition, determine, based on the Sit-to-Stand transition occurring, a second plurality of PTTs after the Sit-to-Stand transition, and determine a likelihood that a person, such as a patient, may fall based on the first plurality of PTTs and the second plurality of PTTs.

Body stability measurement using pulse transit time

This disclosure is directed to techniques for recording and recognizing physiological parameter patterns associated with symptoms. A medical device system includes a medical device including an accelerometer configured to collect an accelerometer signal that indicates one or more patient movements that occur during a cough. Additionally, the medical device system includes processing circuitry configured to: determine whether the accelerometer signal satisfies a set of criteria corresponding to a cough pattern comprising a smooth increase from a baseline, then a sharp decrease, a peak within the sharp decrease, then a gradual return to the baseline; and identify a cough based on the determination that the accelerometer signal satisfies the set of criteria.

Cough detection using frontal accelerometer

A medical device system and method that includes accelerometer circuitry configured to generate at least one signal, a memory, and processing circuitry coupled to the accelerometer circuitry and the memory. The processing circuitry is configured to monitor a patient for a Sit-To-Stand transition based upon the at least one signal, detect the Sit-to-Stand transition, determine if the patient has been inactive for a predetermined period of time prior to the Sit-to-Stand transition, and if the patient has been inactive for at least the predetermined period of time prior to the Sit-to-Stand transition, determine a body stability score of the patient.

Body stability measurement

The disclosure describes an enhancement to lead monitoring techniques, which uses a sensing integrity counter (SIC). The techniques of this disclosure may enhance lead monitoring techniques by detecting possible sensing issues based on a significant increase in periodic, e.g., daily, SIC counts relative to previous periods. Some issues with sensing cardiac signals via implantable cardiac leads can result in an implantable medical device (IMD) measuring very short intervals between what appears to be sensed heart beats. Examples of issues include insulation breach, conductor fracture, or poor electrical connection, which may cause noise that appears to be an R-wave. The IMD may detect the noise, along with actual R-waves, and determine that there are relatively short (e.g., less than a threshold) intervals between the 'R-waves.' A significant increase in the number or frequency of very short intervals between R-waves may indicate the date/time of a significant sensing issue.

Detecting the onset of sensing issues using short intervals

An implantable medical device capable of sensing cardiac signals and delivering cardiac electrical stimulation therapies is enabled to detect a short circuit event. A signal is sensed by a sensing module coupled to electrodes. A controller detects a short circuit event in response to a slope of the sensed signal exceeding a short circuit threshold.

Identify insulation breach using electrograms

A user equipment that includes a touchscreen, and at least one processor configured to generate first timestamp data based upon detection of a first touch event on the touchscreen, and second timestamp data based upon detection of a second touch event on the touchscreen, for calculation by a medical device system of a patient-specific functional status parameter associated with a Sit-To-Stand performance test over a time segment inclusively bounded by a first time defined by the first timestamp data and a second time defined by the second timestamp data.

Mobile application to prompt physical action to measure physiologic response in implantable device

A medical device system and method for detecting dislodgement of a lead determines one or more characteristics of a cardiac signal received via the lead that are associated with dislodgement of the lead during atrial fibrillation, and detects dislodgement of the ventricular lead based on the determined characteristics. The medical device and system provides a lead dislodgment alert in response to detecting dislodgement. In some examples, an implantable medical device withholds delivery of a defibrillation therapy based on detecting dislodgement of the lead.

Detecting lead dislodgement during atrial fibrillation

Detecting dislodgement of a ventricular lead coupled to an implantable medical device comprises sensing a near-field cardiac EGM via a first electrode of the ventricular lead and a far-field cardiac EGM via a second electrode of the ventricular lead, identifying, R-waves in the near-field cardiac EGM and the far-field cardiac EGM. determining a near-field value of one or more R-wave amplitude metrics based on amplitudes of R-waves identified in the near-field cardiac EGM and a far-field value of the one or more R-wave amplitude metrics based on amplitudes of R-waves identified in the far-field cardiac EGM, detecting dislodgement of the ventricular lead based on at least one of the near-field value or the far-field value of the one or more R-wave amplitude metrics; and providing a lead dislodgment alert in response to detecting the dislodgement of the ventricular lead.

Detecting ventricular lead dislodgement

Examples described herein include a medical device system comprising an accelerometer circuitry configured to output a signal indicative of variations in accelerations along a single axis of movement of patient; and processing circuitry configured to receive the output signal from the accelerometer, and to rectify the output signal to generate a rectified signal, wherein rectification of the output signal comprises generating a rectified value for each of a plurality of moving windows imposed over the output signal, wherein generating the rectification value for each of the plurality of moving windows comprises determining a current value of the output signal for the window, determining a maximum value for a portion of the output signal enclosed by the window, and subtracting the current value from the maximum value; and analyze the rectified signal to detect the occurrence of a step taken by a patient based on the rectified signal.

Step detection using accelerometer axis

In some examples, processing circuitry of a medical device system determines, for each of a plurality of periods, a plurality of heart rates of a patient based on a cardiac electrogram signal, and identifies a first subset of the plurality of heart rates as nighttime heart rates and a second subset of the plurality of heart rates as resting heart rates. The processing circuitry determines a representative nighttime heart rate based on the first subset of the plurality of heart rates, determines a representative resting heart rate based on the second subset of the plurality of heart rates, and determines a nocturnal dip base on the representative nighttime heart rate and the representative resting heart rate. The processing circuitry compares at least one of the representative nighttime heart rate, the representative resting heart rate, and the nocturnal dip in heart rate to a respective threshold value, and determines whether to generate an alert indicating a change in the cardiac function of the patient based on the comparison.

Automatic heart rate diagnostics

An implantable medical device having a sensing module and a control module is configured to receive a cardiac electrical signal and sense events from the cardiac electrical signal received via electrodes carried by a medical electrical lead when the medical electrical lead is coupled to the implantable medical device. The control module coupled is configured to detect non-sustained tachyarrhythmia (NST) episodes based on sensed event intervals and determine if the sensed event intervals during the detected NST episode satisfy oversensing criteria. If the oversensing criteria are satisfied, the control module determines whether the detected NST episode satisfies non-lead related oversensing criteria and withholds a lead integrity alert when the NST episode meeting the oversensing criteria is determined to satisfy non-lead related oversensing criteria.

Reducing false positive lead integrity alerts

Growing community of inventors

Plymouth, MN, United States of America

Bruce D Gunderson