Medtronic, Inc.

Jerry D Reiland

Shantanu Sarkar

Ryan D Wyszynski

Daniel L Hansen

Michael L Hudziak

Grant Alan Neitzell

Hyun J Yoon

Erin N Reisfeld

Charles R Gordon

Matthew P Hanly

Jon E Thissen

Gary J Pauly

Robert Michael Ecker

Michael B Terry

Ya-Jian Cheng

Paul R Solheim

Matthew J Hoffman

Kevin K Walsh

Niranjan Chakravarthy

Gautham Rajagopal

Eric M Christensen

Duane R Bigelow

Deborah Ann Jaye

Robert D Musto

Melani G Sullivan

Ashley L Galarneau

Evan S Johnson

Geert Morren

Gary Toering

Yuying Chao

Stephanie Chen

Matthew P Hanley

Hyan J Yoon

Ya_Jian Cheng

Techniques for determining whether a ventricular depolarization is a premature ventricular contraction (PVC) depolarization may include processing circuitry of a medical system identifying an interval from a maximum slope point to a minimum slope point for each of a plurality of ventricular depolarizations and, for each of the plurality of ventricular depolarizations as a current ventricular depolarization, determining that the intervals from the maximum slope point to the minimum slope point for the current ventricular depolarization, a preceding adjacent ventricular depolarization of the plurality of ventricular depolarizations, and a subsequent adjacent ventricular depolarization of the plurality of ventricular depolarizations satisfy one or more slope criteria. The processing circuitry determines that the current ventricular depolarization is a PVC depolarization based on the intervals from the maximum slope point to the minimum slope point satisfying the one or more slope criteria.

Premature ventricular contraction (PVC) detection

Techniques and devices for implementing the techniques for adjusting atrial arrhythmia detection based on analysis of one or more P-wave sensing windows associated with one or more R-waves. An implantable medical device may determine signal characteristics of the cardiac signal within the P-wave sensing window, determine whether the cardiac signal within the sensing window corresponds to a P-wave based on the determined signal characteristics, determine a signal to noise ratio of the cardiac signal within the sensing window, update the arrhythmia score when the P-wave is identified in the sensing window and the determined signal to noise ratio satisfies a signal to noise threshold.

Method and apparatus for atrial arrhythmia episode detection

Techniques for switching an implantable medical device (IMD) from a first mode to a second mode in relation to signals obtained from internal sensors are described. The internal sensors may include a temperature sensor and a biosensor. In some examples, processing circuitry of the IMD may make a first preliminary determination that the IMD is implanted based on a first signal from the temperature sensor. In response to the first preliminary determination being that the IMD is implanted, the processing circuitry may make a second preliminary determination that the IMD is implanted based on a second signal from the biosensor. The processing circuitry may switch the IMD from a first mode to a second mode based on both the first preliminary determination and the second preliminary determination being that the IMD is implanted.

Implantable medical device using internal sensors to determine when to switch operational modes

This disclosure is directed to devices, systems, and techniques for dynamically adjusting a bio impedance measurement range. An example device includes a plurality of electrodes. The device also includes sensing circuitry configured to sense a bio impedance and processing circuitry. The processing circuitry is configured to apply an excitation signal to the sensing circuitry and, based on the application of the excitation signal, determine a sensed bio impedance value within a bio impedance measurement range. The processing circuitry is also configured to determine whether the sensed bio impedance value is within a predetermined portion of the bio impedance measurement range for a predetermined period of time and based on the sensed bio impedance value being within the predetermined portion of the bio impedance measurement range for the predetermined period of time, adjust the excitation signal.

Dynamic bio impedance range adjustment for a medical device

This disclosure is directed to devices, systems, and techniques for identifying a respiration rate based on an impedance signal. In some examples, a medical device system includes a medical device including a plurality of electrodes. The medical device is configured to perform, using the plurality of electrodes, an impedance measurement to collect a set of impedance values, where the set of impedance values is indicative of a respiration pattern of a patient. Additionally, the medical device system includes processing circuitry configured to identify a set of positive zero crossings based on the set of impedance values, identify a set of negative zero crossings based on the set of impedance values, and determine, for the impedance measurement, a value of a respiration metric using both the set of negative zero crossings and the set of positive zero crossings.

Sensing respiration parameters based on an impedance signal

This disclosure is directed to techniques for identifying false detection of asystole in a cardiac electrogram that include determining whether at least one of a plurality of false asystole detection criteria are satisfied. In some examples, the plurality of false asystole detection criteria includes a first false asystole detection criterion including a reduced amplitude threshold for detecting cardiac depolarizations in the cardiac electrogram, and a second false asystole detection criterion for detecting decaying noise in the cardiac electrogram.

Identification of false asystole detection

A system and method for detecting and verifying bradycardia/asystole episodes includes sensing an electrogram (EGM) signal. The EGM signal is compared to a primary threshold to sense events in the EGM signal, and at least one of a bradycardia or an asystole is detected based on the comparison. In response to detecting at least one of a bradycardia or an asystole, the EGM signal is compared to a secondary threshold to sense events under-sensed by the primary threshold. The validity of the bradycardia or the asystole is determined based on the detected under-sensed events.

Method and apparatus for verifying bradycardia/asystole episodes via detection of under-sensed events

Techniques are disclosed for using a rate of wireless telemetry of an implantable medical device (IMD) to estimate a remaining longevity of a power source of the IMD. For example, the IMD sets a timer indicative of a remaining power capacity of the power source until a recommended replacement time (RRT) threshold. The IMD determines a power consumption of the IMD due to telemetry and updates, based on the power consumption of the IMD due to telemetry, the timer indicative of the remaining power capacity of the power source. The IMD determines, based on expiration of the timer indicative of the remaining power capacity of the power source, that the power source has reached the RRT threshold. In some examples, the IMD may output, to an external device and for display to a user, an indication that the power source has reached the RRT threshold.

Power source longevity

Techniques and devices for implementing the techniques for adjusting atrial arrhythmia detection based on analysis of one or more P-wave sensing windows associated with one or more R-waves. An implantable medical device may determine signal characteristics of the cardiac signal within the P-wave sensing window, determine whether the cardiac signal within the sensing window corresponds to a P-wave based on the determined signal characteristics, determine a signal to noise ratio of the cardiac signal within the sensing window, update the arrhythmia score when the P wave is identified in the sensing window and the determined signal to noise ratio satisfies a signal to noise threshold.

Growing community of inventors

Coon Rapids, MN, United States of America

Jerry D Reiland