Pacesetter, Inc.

Laleh Jalali

Jay Snell

Bing Zhu

Gene A Bornzin

Katie Hoberman

Xiaoyi Min

Peter Boileau

Elizabeth Bacon

Euljoon Park

Jong Gill

Steve Koh

Jeffery D Snell

Eric Steven Fain

Rupinder Bharmi

Josh Reiss

Mohssen Fard

Systems and methods are provided for detecting the orientation and/or movement of a patient having an implantable cardiac stimulation device and evaluating whether a change in the patient's cardiac activity can be at least in part due to a change in the patient's orientation. In one particular embodiment, signals from an orientation sensor and/or a pressure sensor are evaluated to determine static positional orientation of the patient and determine based on the static orientation whether the patient's cardiac activity is abnormal.

Posture detection using pressure and other physiologic sensors

A method and system are provided for trending a coronary burden such as an ischemic burden or acute myocardial infarction (AMI) for a patient. Trending provides obtaining cardiac data over a period of time, identifying the onset and the termination of coronary episodes based on a ST segment variation within the cardiac data, recording coronary burden information, and presenting the coronary burden information to a user. The coronary burden information may include the number of coronary episodes occurring over a period of time, the time duration of the coronary episodes, and the maximum ST segment variations for the coronary episodes that occur over a period of time.

Methods and systems for trending ST segment changes over time

A method and system are provided for trending variation in coronary burden across multiple heart rate ranges. The method and system include obtaining cardiac signals having a segment of interest over a period of time where each cardiac signal has an associated heart rate that falls within at least one heart rate range. Segment variations of the segment of interest are determined and grouped based on the associated heart rates to produce distributions of segment variations that are associated with the heart rate ranges. Trending information is produced by automatically comparing the distributions of segment variations between different heart rate ranges.

Method and system for trending variation in coronary burden across multiple heart rate ranges

Techniques are described for adaptively adjusting detection thresholds for use in detecting cardiac ischemia and other abnormal physiological conditions based on morphological parameters derived from intracardiac electrogram (IEGM) signals, impedance measurements, or other signals. In one example, where ST segment elevation is used to detect cardiac ischemia, default detection thresholds are determined in advance from an examination of variations in ST segment elevations occurring within a population of patients. Thereafter, an individual pacemaker or other implantable medical device uses the default thresholds during an initial learning period to detect ischemia within the patient in which the device is implanted. During the initial learning period, the pacemaker also collects data representative of the range of variation in ST segment elevations occurring within the patient. The pacemaker then adaptively adjusts the thresholds based on the range of variation so as to improve detection specificity within the patient.

System and method for adaptively adjusting cardiac ischemia detection thresholds and other detection thresholds used by an implantable medical device

Techniques are described for efficiently detecting and distinguishing among cardiac ischemia, hypoglycemia or hyperglycemia based on intracardiac electrogram (IEGM) signals. In one example, a preliminary indication of an episode of cardiac ischemia is detected based on shifts in ST segment elevation within the IEGM. In response, the implanted device then records additional IEGM data for transmission to an external system. The external system analyzes the additional IEGM data to confirm the detection of cardiac ischemia using a more sophisticated analysis procedure exploiting additional detection parameters. In particular, the external system uses detection parameters capable of distinguishing hypoglycemia, hyperglycemia and hyperkalemia from cardiac ischemia, such as QTmax and QTend intervals. Alternatively, the more sophisticated analysis procedure may be performed by the device itself, if it is so equipped. Other examples described herein pertain instead to the detection of atrial fibrillation.

System and method for efficiently distinguishing among cardiac ischemia, hypoglycemia and hyperglycemia using an implantable medical device and an external system

A method and system are provided for tracking ST shift data. The system includes an implantable medical device having an input configured to receive cardiac signals. Each cardiac signal has an associated heart rate and includes a segment of interest. The implantable medical device further includes a processor configured to determine segment variations of the segment of interest in the cardiac signals. The processor determines a heart rate associated with each of the segment variations with each heart rate falling within a corresponding heart rate range. The implantable medical device also includes a memory configured to store a group of histograms for a corresponding group of heart rate ranges. The histograms store distributions for the segment variations within corresponding heart rate ranges.

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Moorpark, CA, United States of America

Laleh Jalali