Medtronic, Inc.

3m Innovative Properties Company

Medtronic Monitoring, Inc.

Maneesh Shrivastav

Karen J Kleckner

Yong Kyun Cho

Saul E Greenhut

Tommy Dean Bennett

Mark K Erickson

Charles P Sperling

Jeffrey M Gillberg

Robert A Corey

Mark L Brown

Troy Edward Jackson

G Marco Bommarito

Teresa A Whitman

ShaileshKumar V Musley

Judy J Ma

Arun Kumar

Rothanak Chhoun

Stacie Vilendrer

Christina M Dimeo

Amelia Fish

Robert W Stadler

Jian L Cao

Randal C Schulhauser

Brian Bruce Lee

Scott R Stanskaski

Karin J Kleckner

Aspects of the present disclosure relate to a system including an image capture device and a computing device configured to receive a test image from the image capture device corresponding to a first surgical instrument, determine an identity type of the first surgical instrument using the test image in a machine vision technique, determine whether the first surgical instrument is flagged, and perform at least one operation in response to whether the first surgical instrument is flagged.

Sterilization process management

Embodiments describe a method of determining etiology of undiagnosed events comprising monitoring electrocardiogram signals and blood pressure of a patient via a medical device, capturing one or more of an ECG segment and a BP reading in response to a triggering event, classifying one or more of the ECG segment and BP reading as normal or abnormal, and determining etiology of undiagnosed symptomatic events based on the classification. Embodiments further describe a medical device comprising sensors for monitoring ECG signals and BP of a patient, circuitry for capturing one or more of ECG segments and BP readings of a patient in response to a triggering event, and a processor for communicating one of more of captured ECG segments and captured BP readings to a remote monitoring center directly or indirectly where the captured ECG segments and captured BP readings are classified as normal or abnormal.

System and methods of determining etiology of undiagnosed symptomatic events

A system and method of monitoring electrocardiogram (ECG) signals and detecting ischemic conditions. In particular, high-frequency components and low-frequency components are extracted from the monitored ECG signal. The high-frequency components are analyzed to detect reduced amplitude zones (RAZs), while the low-frequency components are utilized to detect premature ventricular contraction (PVC) beats. Potentially ischemic conditions are identified based on both RAZs and PVC beats detected.

Method and apparatus for detecting electrocardiographic abnormalities based on monitored high frequency QRS potentials

A method of determining a respiration parameter in a medical device in which pressure signals are sensed to generate corresponding sample points, and a breath detection threshold is continuously adjusted in response to the generated sample points to generate a current adjusted breath detection threshold. A current generated sample point is compared to the current adjusted breath detection threshold, and the continuous adjusting of the breath detection threshold is suspended and the breath detection threshold is equal to the most current adjusted breath detection threshold generated prior to the suspending in response to the comparing. A next sample point, generated subsequent to the suspending, is compared to the set breath detection threshold, and the respiration parameter is determined in response to the comparing of a next sample point to the set breath detection threshold.

Method and apparatus for determining a respiration parameter in a medical device

A medical device for determining a respiratory effort having a pressure sensor to sense pressure signals, a housing having system components positioned therein, and a microprocessor positioned within the housing, wherein the microprocessor detects an inspiration and an expiration in response to the pressure signals, detects a breath in response to the detected inspiration and the detected expiration, and determines the respiratory effort in response to the detected breath.

Method and apparatus for detecting respiratory effort in a medical device

A method of determining respiratory effort in a medical device in which pressure signals are sensed to generate corresponding sample points, an inspiration and an expiration are detected in response to the sensed pressure signals, a breath is detected in response to the detected inspiration and the detected expiration, and the respiratory effort is determined in response to the detected breath.

Method and apparatus for determining respiratory effort in a medical device

A medical device and associated method for detecting arrhythmias that includes electrodes for sensing cardiac electrical signals and a hemodynamic sensor for sensing a hemodynamic signal. An episode of cardiac electrical event intervals meeting cardiac arrhythmia detection criteria is detected from the sensed electrical signals. Cardiac mechanical events and/or cardiac mechanical event intervals are measured from the hemodynamic signal and used to withhold or confirm a cardiac arrhythmia detection of the episode.

Combined hemodynamic and EGM-based arrhythmia detection

A medical device and associated method for detecting arrhythmias that includes sensing cardiac electrical signals and cardiac hemodynamic signals, determining a long-term baseline hemodynamic measurement in response to a plurality of the sensed cardiac hemodynaic signals, detecting a period of increased metabolic demand in response to the sensed cardiac electrical signals, determining a sinus tachycardia baseline hemodynamic measurement in response sensing of cardiac hemododynamic signals during the detected period of increased metabolic demand, and detecting the arrhythmia and delivering therapy in response to one of only the sensed cardiac electrical signals and the sensed cardiac electrical signals in combination with one or both of the determined long-term baseline hemodynamic measurement and the sinus tachycardia baseline hemodynamic measurement.

A system and method for filtering a pressure signal in a medical device in which a sensor terminal senses the pressure signal, an electrode terminal receives cardiac electrical signals, a signal filtering system filters the sensed pressure signal in response to a determined heart rate to generate a heart-rate dependent frequency response, and a microprocessor derives a respiration signal in response to the heart rate dependent frequency response, and determines metrics of hemodynamic function in response to the derived respiration signal.

Filtering of a physiologic signal in a medical device

An implantable medical device system and method detect oversensing of cardiac signals. A cardiac signal including first events and second events is acquired. Cardiac events are sensed in response to the cardiac signal crossing a first threshold. A filtered cardiac signal is determined from the sensed cardiac signal, and a second threshold is determined from the filtered cardiac signal. A sensed cardiac event is classified either as a first event when the sensed cardiac event corresponds to a filtered cardiac signal peak crossing the second threshold or a second event when the sensed cardiac event corresponds to a filtered cardiac signal peak being less than the second threshold. Classification of sensed cardiac events as second events is used in determining oversensing.

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Blaine, MN, United States of America

Maneesh Shrivastav