Abstract: An apparatus includes a sensing circuit configured to generate a sensed physiological signal representative of cardiac activity of a subject, and an arrhythmia detection circuit. The arrhythmia detection circuit is configured to monitor information corresponding to ventricular depolarization (V-V) intervals using the sensed physiological signal; determine a V-V interval distribution; determine a heart rate density index (HRDI) as a portion of samples of the V-V interval distribution corresponding to a V-V interval occurring most often in the distribution; and generate an indication of atrial fibrillation (AF) using the HRDI.

Abstract: This document discusses, among other things, apparatus, systems, and methods to determine a first atrial fibrillation (AF) indication using received information about a heart over a first period, to cluster depolarization information about the heart over the first period, and to discriminate between an atrial fibrillation (AF) event and a non-AF event in the first period using the determined first AF indication the clustered depolarization information.

Abstract: An apparatus includes a sensing circuit configured to generate a sensed physiological signal representative of cardiac activity of a subject, and an arrhythmia detection circuit. The arrhythmia detection circuit is configured to monitor information corresponding to ventricular depolarization (V-V) intervals using the sensed physiological signal; determine a V-V interval distribution; determine a heart rate density index (HRDI) as a portion of samples of the V-V interval distribution corresponding to a V-V interval occurring most often in the distribution; and generate an indication of atrial fibrillation (AF) using the HRDI.

Abstract: Automated pre-implant screening for candidate recipients of implantable medical devices. A set of cutaneous electrodes placed on a patient transcutaneously capture a cardiac signal using a screening device coupled to the electrodes. A first beat rate may be determined by identifying individual R-waves, QRS complexes or cardiac cycles from the captured cardiac signal using the cutaneous electrodes. A second beat rate may be calculated using one of several different methods, for example, by optical measurement, by monitoring heart sounds, by a second electric cardiac signal analysis, or by using an implanted device. The rates are compared to one another and, if a match is identified, the patient is deemed well suited to receive a particular device.

Abstract: This document discusses, among other things, systems, devices, and methods for detecting stroke in a patient. A system may comprise a sensor circuit for sensing in a patient at first physiological signal and a second physiological signal or a functional signal. A stroke risk circuit may establish a physiological trend from at least the first physiological signal over time, and generate a stroke risk indicator using the physiological trend and the second physiological or functional signal. Indications of behavioral or cognitive impairment may also be used in stroke risk indicator generation. The system includes an output unit that outputs the stroke risk indicator to a user or a process.

Abstract: Methods and device for determining a pacing vector for delivering an electrostimulation therapy are described. An implantable medical device may be configured to determine an anode capture threshold and a cathode capture threshold for a first anode and cathode pair of electrodes, switch a polarity of the first anode and cathode pair of electrodes, and determine an anode capture threshold and a cathode capture threshold for the first anode and cathode pair of electrodes having the switched polarity. The implantable medical device may be further configured to compare a cathodal capture threshold for the anode and cathode pair having the switched polarity to the anodal capture threshold of the first anode and cathode pair of electrodes and select either an anode or a cathode for delivering an electrostimulation therapy based at least in part on the comparison. Other methods and systems are also contemplated and described.

Abstract: A system for monitoring a subject for an arrhythmia includes an external monitoring device (EMD) configured to be disposed outside of a subject's body. The EMD includes a first communication component configured to receive, from a medical device, a first physiological parameter signal and an indication of a detected trigger event associated with a first portion of the first physiological parameter signal. The trigger event is indicative of a potential arrhythmia. The EMD also includes an analysis component configured to (1) identify a second portion of the first physiological parameter signal, where the second portion satisfies a discard criterion, (2) discard the second portion, and (3) perform an arrhythmia confirmation evaluation using a third portion of the first physiological parameter signal.

Abstract: A system for lead integrity monitoring includes an implantable medical device (IMD) having a housing enclosing a control circuit; and a lead, having a first sensor. The lead is coupled to the housing and electrically coupled to the control circuit. The system also includes at least one processing device configured to identify a first lead failure alert based on a first set of information; obtain a second set of information generated by a second sensor; perform an evaluation of the first set of information in the context of the second set of information; and confirm or cancel the first lead failure alert based on the evaluation.

Abstract: 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.

Abstract: Implanted medical device data is received, where the data was sensed by a first lead portion and a sensor over a time period. The number of detected noise events sensed by the first lead portion is counted based on applying first noise detection criteria to the data sensed by the first lead portion. The number of detected noise events over the sensor is counted based on applying second noise detection criteria to the data sensed by the sensor. The mean number of detected noise events is calculated for the first lead portion and sensor based on the number of noise events sensed by the first lead portion and the number of noise events sensed by the sensor. Potential lead failure in the first lead is recorded if the number of detected noise events over the first lead is greater than the mean number of noise events by at least 5%.

Abstract: Embodiments of the disclosure include systems and methods for reducing false positives in detection of pauses. For example, embodiments include a sensing component configured to obtain values of a first physiological parameter and determine a cardiac pause based on the values of the first physiological parameter. Furthermore, embodiments include performing a validation check of the determined cardiac pause using at least one of: the values of the first physiological parameter or values of a second physiological parameter.

Abstract: Systems and methods for detecting a target physiologic event and storing physiologic information associated with the detected physiologic event are disclosed. A system can receive a physiologic signal obtained from a subject, and detect the target physiologic event using a first portion of the received physiologic signal. The system can confirm the target physiologic event using a second portion of the received physiologic signal. If the target physiologic event is confirmed, the system can store physiologic information associated with the confirmed target physiologic event in a memory.

Abstract: An apparatus includes a sensing circuit configured to generate a sensed physiological signal that includes physiological information of a subject, a detection circuit, and a control circuit. The detection circuit detects a physiological condition of a subject using the physiological signal. The control circuit stores sampled values of a segment of the physiological signal in temporary memory storage; and stores the sampled values in non-temporary storage in response to receiving an indication of continued detection of the physiological condition.

Abstract: Monitoring physiological parameter using an implantable physiological monitor in order to detect a condition predictive of a possible future pathological episode and collecting additional physiological data associated with the condition predictive of a possible future pathological episode. Monitoring another physiological parameter in order to detect a condition indicative of the beginning of a present pathological episode and collecting additional pathological data in response to the condition. Determining that the condition predictive of a future episode and the condition indicative of a present episode are associated and, in response thereto, storing all the collected physiological data.

Abstract: Various techniques are disclosed for quickly and efficiently determining cardiac pacing vectors that minimize phrenic nerve stimulation.

Abstract: 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.

Abstract: Methods and devices for combining multiple signals from multiple sensing vectors for use in wearable or implantable cardiac devices. Signals from multiple vectors may be combined using weighting factors and/or by conversion to different coordinate systems than the original inputs, which may or may not be normalized to patient anatomy. Signals from multiple sensing vectors may be combined prior to or after several analytical steps or processes including before or after filtering, and before or after cardiac cycle detection. Cardiac cycle detection information may be combined across multiple sensing vectors before or after analysis of individual vectors for noise or overdetection. Cardiac cycle detection information may also be combined across multiple sensing vectors to identify noise and/or overdetection.

Abstract: Methods and devices for combining multiple signals from multiple sensing vectors for use in wearable or implantable cardiac devices. A preferred sensing configuration may be selected at a given point in time, for example under clinical conditions. Signal quality for the preferred sensing configuration is then monitored, and if the signal quality degrades under selected conditions, re-analysis may be performed to select a different sensing vector configuration for at least temporary use. If signal quality increases for the preferred sensing configuration, temporary use of the different sensing vector configuration may cease and reversion to the preferred sensing configuration takes place if certain conditions are met. The conditions for reversion may depend in part of a history of sensing signal quality for the preferred sensing configuration.

Abstract: New and alternative approaches to the monitoring of cardiac signal quality for external and/or implantable cardiac devices. In one example, signal quality is monitored continuously or in response to a triggering event or condition and, upon identification of a reduction in signal quality, a device may reconfigure its sensing state. In another example, one or more trends of signal quality are monitored by a device, either continuously or in response to a triggering event or condition, and sensing reconfiguration may be performed in response to identified trends and events. In yet another example, a device may use a looping data capture mode to track sensing data in multiple vectors while primarily relying on less than all sensing vectors to make decisions and, in response to a triggering event or condition, the looped data can be analyzed automatically, without waiting for additional data capture to reconfigure sensing upon identification of the triggering event or condition.

Abstract: Methods and devices for combining multiple signals from multiple sensing vectors for use in wearable or implantable cardiac devices. Signals from multiple vectors may be combined using weighting factors and/or by conversion to different coordinate systems than the original inputs, which may or may not be normalized to patient anatomy. Signals from multiple sensing vectors may be combined prior to or after several analytical steps or processes including before or after filtering, and before or after cardiac cycle detection. Cardiac cycle detection information may be combined across multiple sensing vectors before or after analysis of individual vectors for noise or overdetection. Cardiac cycle detection information may also be combined across multiple sensing vectors to identify noise and/or overdetection.