Pacesetter, Inc.

Christopher Gloschat

Fujian Qu

Nima Badie

Dean P Andersen

Fady Dawoud

Aditya Goil

Mostafa Sadeghi

Kevin J Davis

Leyla Sabet

A system is provided that includes one or more electrodes configured to be implanted proximate to a sensing site, and a memory configured to store first and second sets of filter parameters that define first and second noise stop bands. The system also includes an implantable medical device (IMD) that has inputs configured to receive sensed signals, the sensed signals include frequency components associated with physiology activity and frequency components associated with noise. The IMD also includes a band-stop filter communicating with the sensing channel inputs. When executing program instructions, a processor switches the band-stop filter from the first set of filter parameters to the second set of filter parameters to shift from the first noise stop band to the second noise stop band based on the noise in the environment of the patient.

Method and system for filtering noise of an implantable medical device

Embodiments described herein can reduce a burden associated with analyzing EGM segments obtained from an IMD that monitors for arrhythmic episodes. Respective EGM data and respective classification data is obtained for each arrhythmic episode detected by the IMD during a period of time. A representative R-R interval or HR for each of the arrhythmic episodes is also obtained, wherein a manner for determining the representative R-R interval or HR depends on the type of the arrhythmic episode, such that for at least two different types of arrhythmic episodes the manners differ. One or more arrhythmic episodes is/are selected for which corresponding EGM segments are to be displayed for each type of arrhythmic episode, wherein the selecting is performed based on the representative R-R intervals or HRs that are determined for the plurality of arrhythmic episodes. Additional and alternative embodiments are also described herein.

Methods and systems for arrhythmia episode prioritization and improving arrhythmia detection and classification to reduce clinical review burden

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Salt Lake City, UT, United States of America

Christopher Gloschat