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: Implantable cardiac devices and methods of their use. A method of operation in an implantable cardiac device may include steps for characterizing detected events as noise or not noise, identifying a set of consecutive noise events or a threshold quantity of noise events in a set period of time and declaring a noisy series to have occurred. In response to the declaration of a noisy series, the method initiates a baseline correction algorithm. Devices for performing such methods are also disclosed.

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 for sensing vector analysis in an implantable cardiac stimulus system. In an illustrative example, a first sensing vector is analyzed to determine whether it is suitable, within given threshold conditions, for use in cardiac event detection and analysis. If so, the first vector may be selected for detection and analysis. Otherwise, one or more additional vectors are analyzed. A detailed example illustrates methods for analyzing sensing vectors by the use of a scoring system. Devices adapted to perform these methods are also discussed, including implantable medical devices adapted to perform these methods, and systems comprising implantable medical devices and programmers adapted to communicate with implantable medical devices, the systems also being adapted to perform these methods. Another example includes a programmer configured to perform these methods including certain steps of directing operation of an associated implanted or implantable medical device.

Abstract: Systems, methods and non-transient software media for performing sensing vector selection in an implantable cardiac device by assessing biphasic or monophasic characteristics of the cardiac signal in vectors under analysis. A factor associated with the biphasic or monophasic nature of the cardiac signal, as seen from a given sensing vector, can be inserted into the assessment of which of several available sensing vectors is considered “best” for purposes of cardiac signal analysis. Additional factors may be considered beyond the biphasic or monophasic nature including the quantity of turning points or inflections and amplitude variability.

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: Implantable cardiac devices and methods of their use. A method of operation in an implantable cardiac device may include steps for characterizing detected events as noise or not noise, identifying a set of consecutive noise events or a threshold quantity of noise events in a set period of time and declaring a noisy series to have occurred. In response to the declaration of a noisy series, the method initiates a baseline correction algorithm. Devices for performing such methods are also disclosed.

Abstract: Methods and implantable devices for cardiac signal analysis. The methods and devices make use of waveform appraisal techniques to distinguish event detections into categories for suspect events and waveform appraisal passing events. When adjustments are made to the data entering analysis for waveform appraisal, the waveform appraisal thresholds applied are modified as well. For example, when the data analysis window for waveform appraisal changes in length, a waveform appraisal threshold is modified. Other changes, including changes in sensing characteristics with which waveform appraisal operates may also result in changes to the waveform appraisal threshold including changes in gain, sensing vector, activation of other devices, implantee posture and other examples which are explained.

Abstract: Methods and devices for sensing vector analysis in an implantable cardiac stimulus system. In an illustrative example, a first sensing vector is analyzed to determine whether it is suitable, within given threshold conditions, for use in cardiac event detection and analysis. If so, the first vector may be selected for detection and analysis. Otherwise, one or more additional vectors are analyzed. A detailed example illustrates methods for analyzing sensing vectors by the use of a scoring system. Additional examples include implantable devices, implantable device systems, and/or programmers for use in conjunction with implantable devices, each configured to perform such methods.

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 and implantable devices for cardiac signal analysis. The methods and devices make use of waveform appraisal techniques to distinguish event detections into categories for suspect events and waveform appraisal passing events. When adjustments are made to the data entering analysis for waveform appraisal, the waveform appraisal thresholds applied are modified as well. For example, when the data analysis window for waveform appraisal changes in length, a waveform appraisal threshold is modified. Other changes, including changes in sensing characteristics with which waveform appraisal operates may also result in changes to the waveform appraisal threshold including changes in gain, sensing vector, activation of other devices, implantee posture and other examples which are explained.

Abstract: Methods and implantable devices that address response to, or avoidance of, likely non-cardiac voltages including after potentials from external or internal stimulus. Also, methods of operation in implantable medical devices, the methods configured for identifying saturation of input circuitry and mitigating the effects of such saturation. Also, implantable cardiac stimulus or monitoring devices that include methods for identifying saturated conditions and mitigating the effects of such saturation.

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 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, 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: Devices and methods for analyzing cardiac signal data. An illustrative method includes identifying a plurality of detected events and measuring intervals between the detected events for use in rate estimation. In the illustrative embodiment, a set of intervals is used to make the rate estimation by first discarding selected intervals from the set. The remaining intervals are then used to calculate an estimated interval, for example by averaging the remaining intervals.

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 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: Implantable cardiac devices and methods of their use. A method of operation in an implantable cardiac device may include steps for characterizing detected events as noise or not noise, identifying a set of consecutive noise events or a threshold quantity of noise events in a set period of time and declaring a noisy series to have occurred. In response to the declaration of a noisy series, the method initiates a baseline correction algorithm. Devices for performing such methods are also disclosed.