Cardiac Pacemakers, Inc.

Jonathan Walter Krueger

Pramodsingh Hirasingh Thakur

Viktoria A Averina

David L Perschbacher

Deepa Mahajan

Maya Bhat

Krzysztof Z Siejko

Qi An

Yi Zhang

Robert J Sweeney

Julie A Thompson

Keith L Herrmann

Systems and methods for detecting an arrhythmic event and storing physiological information associated with the detected arrhythmic event are described. A system may include a first detector to detect an arrhythmic event from a physiological signal sensed from a subject, and generate a confidence indicator indicating a confidence level of the detection of the arrhythmic event. If the confidence indicator indicates a relatively high confidence of arrhythmia detection, the system may provide the detected arrhythmic event to a first process for storing the detected arrhythmic event or generating an alert. If the confidence indicator indicates a relatively low confidence of arrhythmia detection, the system may provide the detected arrhythmic event to at least a second process including confirming or rejecting the detected arrhythmic event.

Confidence of arrhythmia detection

Devices and methods for detecting an event using a variable threshold. A patient monitoring system can receive physiologic information and compare the information to an onset threshold. When the onset threshold is exceeded, the system shifts to a reset threshold that is different than the onset threshold. When the reset threshold is crossed, the system shifts back to the onset threshold.

Event detection using a variable threshold

Atrial fibrillation information can be determined from ventricular information or a ventricular location, such as using ventricular rate variability. An ambulatory medical device can receive indications of pairs of first and second ventricular rate changes of three temporally adjacent ventricular heart beats. A first count of instances of the pairs meeting a combined rate change magnitude characteristic and a second count of instances of the pairs in which both of the first and second ventricular rate changes are negative can be used to provide atrial fibrillation information.

Atrial fibrillation detection using ventricular rate variability

An example of a system may include a sensing circuit to sense a cardiac signal indicative of atrial and ventricular depolarizations and an atrial fibrillation (AF) detection circuit to detect AF. The AF detection circuit may include a detector and a detection enhancer. The detector may be configured to detect the ventricular depolarizations using the cardiac signal, measure ventricular intervals, and detect AF using the ventricular intervals. The detection enhancer may be configured to generate atrial detection windows each being a time interval prior to each of the detected ventricular depolarizations, compute an atrial activity score using a rolling average of portions of the cardiac signal within the atrial detection windows, and verify the detection of the AF using the atrial activity score and an atrial activity threshold. The atrial activity score is a measure of consistency between a relationship between the atrial depolarizations and the ventricular depolarizations.

Method and apparatus for enhancing ventricular based atrial fibrillation detection using atrial activity

Systems and methods for detecting a target cardiac condition such as events indicative of worsening heart failure are described. A system may include sensor circuits for sensing physiological signals and a signal processor for generating a predictor trend indicative of temporal change of the physiological signal. The predictor trend may be transformed into a sequence of transformed indices using a codebook that includes a plurality of threshold pairs each including onset and reset thresholds. The codebook may be constructed and updated using physiological data. The system may detect target cardiac condition using the transformed indices.

Detection of worsening heart failure

Devices and methods for detecting physiological target event such as events indicative of HF decompensation status are described. An ambulatory medical device (AMD) can measure bio-impedance, such as thoracic impedance, from a patient. The AMD can receive a specified threshold within a range or a distribution of impedance measurement, or a specified percentile such as less than 50percentile, and calculate a representative impedance value (Z) corresponding to the specified threshold or percentile using a plurality of thoracic impedance measurements. The representative impedance value can be calculated using an adaptation process, or using an estimated distribution of the impedance measurements. The AMD can include a physiologic event detector circuit that can generate a trend of representative impedance values over a specified time period, and to detect a target physiologic event such as indicative of HF decompensation using the trend of representative impedance values.

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New Richmond, WI, United States of America

Jonathan Walter Krueger