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: 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/or device facilitating and selecting among multiple modes of filtering a cardiac electrical signal, in which one filtering mode includes additional high pass filtering of low frequency signals, relative to the other filtering mode. The selection filtering modes may include comparing sensed signal amplitude to one or more thresholds, using the multiple modes of filtering. In another example, an additional high pass filter is enabled, over and above a default or baseline filtering mode, and the detected cardiac signal is monitored for indications of possible undersensing, and/or for drops in amplitude toward a threshold, and the additional high pass filter may be disabled upon finding of possible undersensing or drop in signal amplitude.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In illustrative examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. New methods for organizing the use of morphology and rate analysis in an overall architecture for rhythm classification and cardiac signal analysis are also discussed.

Abstract: Methods and/or device facilitating and selecting among multiple modes of filtering a cardiac electrical signal, in which one filtering mode includes additional high pass filtering of low frequency signals, relative to the other filtering mode. The selection filtering modes may include comparing sensed signal amplitude to one or more thresholds, using the multiple modes of filtering. In another example, an additional high pass filter is enabled, over and above a default or baseline filtering mode, and the detected cardiac signal is monitored for indications of possible undersensing, and/or for drops in amplitude toward a threshold, and the additional high pass filter may be disabled upon finding of possible undersensing or drop in signal amplitude.

Abstract: In some examples, cardiac cycle detection may be used as an approach to cardiac activity tracking, with one or more second approaches to cardiac activity tracking also available for use. Additional rate measurement relying on different sources or analyses may require extra power consumption over the cycle detection methods. Therefore, new methods and devices are disclosed that selectively activate a second cardiac rate measurement. In some illustrative methods and devices, decisions are made as to whether and which previously collected data, if any, is to be discarded, replaced, or corrected upon activation of the second cardiac rate measurement. In some illustrative methods and devices, a cardiac cycle detection approach to cardiac activity tracking may be bypassed by a second cardiac rate measurement.

Abstract: Methods and devices for addressing difficulty with cardiac event sensing that can arise if the starting point of the cardiac cycle is not well aligned to the intended starting point of a detection profile used for sensing. As an improvement, illustrative methods and devices provide an addition to cardiac sensing operations by adjusting the starting point of a detection profile to align with a desired point in the cardiac signal.

Abstract: Methods, systems, and devices for signal analysis in an implantable cardiac device such as an implantable cardioverter defibrillator. In illustrative examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. Analysis of the apparent width of detected events is used to determine whether overdetection is occurring. If overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data.

Abstract: Methods, implantable medical devices and systems configured to perform analysis of captured signals from implanted electrodes to identify cardiac arrhythmias. In an illustrative embodiment, signals captured from two or more sensing vectors are analyzed, where the signals are captured with a patient in at least first and second body positions. Analysis is performed to identify primary or default sensing vectors and/or templates for event detection.

Abstract: In a subcutaneous implantable cardioverter/defibrillator, cardiac arrhythmias are detected to determine necessary therapeutic action. Cardiac signal information is sensed from far field electrodes implanted in a patient. The sensed cardiac signal information is then amplified and filtered. Parameters such as rate, QRS pulse width, cardiac QRS slew rate, amplitude and stability measures of these parameters from the filtered cardiac signal information are measured, processed and integrated to determine if the cardioverter/defibrillator needs to initiate therapeutic action.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In illustrative examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. New methods for organizing the use of morphology and rate analysis in an overall architecture for rhythm classification and cardiac signal analysis are also discussed.

Abstract: Methods, systems, and devices for signal analysis in an implantable cardiac device such as an implantable cardioverter defibrillator. In illustrative examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. Analysis of the apparent width of detected events is used to determine whether overdetection is occurring. If overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In illustrative examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. New methods for organizing the use of morphology and rate analysis in an overall architecture for rhythm classification and cardiac signal analysis are also discussed.

Abstract: Signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, detected events are analyzed to identify changes in detected event amplitudes. When detected event amplitudes are dissimilar from one another, a first set of detection parameters may be invoked, and, when detected event amplitudes are similar to one another, a second set of detection parameters may be invoked. Additional examples determine whether the calculated heart rate is “high” or “low,” and then may select a third set of detection parameters for use when the calculated heart rate is high.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. Several examples emphasize the use of morphology analysis using correlation to static templates and/or inter-event correlation analysis.

Abstract: Methods and devices providing multiple criteria for use in arrhythmia identification. Based on inputs including defined rules or parameters, one of a more conservative or more aggressive set of arrhythmia identification parameters can be selected. One or the other of the selectable sets of arrhythmia identification parameters may also be adaptive or modifiable during the use of the system, for example, in response to identified nonsustained episodes, the more conservative set of arrhythmia identification parameters can be modified to become still more conservative. Such modification of arrhythmia identification criteria allows reduced time to therapy when indicated, while allowing more deliberate decisions in other circumstances.

Abstract: Methods, implantable medical devices and systems configured to perform analysis of captured signals from implanted electrodes to identify cardiac arrhythmias. In an illustrative embodiment, signals captured from two or more sensing vectors are analyzed, where the signals are captured with a patient in at least first and second body positions. Analysis is performed to identify primary or default sensing vectors and/or templates for event detection.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some illustrative examples, detected events are analyzed to identify changes in detected event amplitudes. When detected event amplitudes are dissimilar from one another, a first set of detection parameters may be invoked, and, when detected event amplitudes are similar to one another, a second set of detection parameters may be invoked. Additional methods determine whether the calculated heart rate is “high” or “low,” and then may select a third set of detection parameters for use when the calculated heart rate is high.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some examples, captured data including detected events is analyzed to identify likely overdetection of cardiac events. In some illustrative examples, when overdetection is identified, data may be modified to correct for overdetection, to reduce the impact of overdetection, or to ignore overdetected data. Several examples emphasize the use of morphology analysis using correlation to static templates and/or inter-event correlation analysis.

Abstract: Methods, implantable medical devices and systems configured to perform analysis of captured signals from implanted electrodes to identify cardiac arrhythmias. In an illustrative embodiment, signals captured from two or more sensing vectors are analyzed, where the signals are captured with a patient in at least first and second body positions. Analysis is performed to identify primary or default sensing vectors and/or templates for event detection.