Abstract: A system and method provide heart sound tracking, including an input circuit, configured to receive heart sound information, and a heart sound recognition circuit. The heart sound recognition circuit can be coupled to the input circuit and can be configured to recognize, within a particular heart sound of a particular heart sound waveform, a first intra heart sound energy indication and a corresponding first intra heart sound time indication using the heart sound information from the particular heart sound waveform and the heart sound information from at least one other heart sound waveform. The particular heart sound can include at least a portion of one of S1, S2, S3, and S4. Further, the first intra heart sound energy indication and the corresponding first intra heart sound time indication can correspond to the at least a portion of one of S1, S2, S3, and S4, respectively.

Abstract: Systems and methods include identifying a first portion and a second portion of a pulmonary artery pressure (PAP) signal during a cardiac cycle. A first timing interval between the first portion and the second portion is obtained and data related to the first timing interval is trended to provide a chronic physiological prognostic indicator. In an embodiment, a second timing interval is obtained from a third portion and a fourth portion of the PAP signal. Then, a function of the first and second timing intervals is trended to provide the chronic physiological prognostic indicator. In one instance, a ratio of the first interval to the second interval is calculated to provide an estimated right ventricle ejection fraction (RVEF) and the RVEF is trended.

Abstract: A system and method provide heart sound tracking, including an input circuit, configured to receive heart sound information, and a heart sound recognition circuit. The heart sound recognition circuit can be coupled to the input circuit and can be configured to recognize, within a particular heart sound of a particular heart sound waveform, a first intra heart sound energy indication and a corresponding first intra heart sound time indication using the heart sound information from the particular heart sound waveform and the heart sound information from at least one other heart sound waveform. The particular heart sound can include at least a portion of one of S1, S2, S3, and S4. Further, the first intra heart sound energy indication and the corresponding first intra heart sound time indication can correspond to the at least a portion of one of S1, S2, S3, and S4, respectively.

Abstract: In an example, a cardiac rhythm management system includes an implantable physiological data monitor, a processor, a memory, and a display. The implantable physiological data monitor can be configured to monitor a plurality of cardiac responses. The processor can be configured to classify the cardiac response into one of at least three classes including pace-dominant, fusion, and pseudo-fusion. The processor can also be configured to calculate statistical information regarding the classified cardiac responses. In this example, the pace-dominant, fusion, and pseudo-fusion classes correspond to a cardiac response resulting from a corresponding electrostimulation. The memory is configured to store the classified cardiac responses and calculated statistical information for future use by the processor or for display. The display is configured to display the statistical information stored in the memory for diagnostic and device programming purposes.

Abstract: The health state of a subject is automatically evaluated or predicted using at least one implantable device. In varying examples, the health state is determined by sensing or receiving information about at least one physiological process having a circadian rhythm whose presence, absence, or baseline change is associated with impending disease, and comparing such rhythm to baseline circadian rhythm prediction criteria. Other chronobiological rhythms beside circadian may also be used. The baseline prediction criteria may be derived using one or more past physiological process observation of the subject or population of subjects in a non-disease health state. The prediction processing may be performed by the at least one implantable device or by an external device in communication with the implantable device. Systems and methods for invoking a therapy in response to the health state, such as to prevent or minimize the consequences of predicted impending heart failure, are also discussed.

Abstract: A system and method for automatically adjudicating arrhythmia episode information is described, and includes an episode database having episode data regarding a plurality of different arrhythmia episodes and an adjudication processor configured to output characterization data characterizing the input episode data. The characterization data includes an arrhythmia classification. The system further includes an episode processor configured to process the characterization data and episode data, provide at least one report on the characterization data related to a plurality of the different arrhythmia episodes, and provide at least one programming recommendation or at least one alert.

Abstract: Systems and methods include accessing a plurality of cardiac indications. A heart rate variability metric is produced by analyzing the plurality of cardiac indications using a measurement from a class of nonlinear measurements. Nonlinear measurements include, but are not limited to, approximate entropy, X-Y scatter from a Poincaré plot, fractal dimension, and detrended fluctuation analysis, in various examples. Based on the heart rate variability metric, a cardiac ischemic state is detected.

Abstract: Systems and methods include obtaining a measure of cardiac contractility. A cardiac contractility variability is determined from the measure of cardiac contractility. Analyzing the cardiac contractility variability, an indication of cardio-vasculature health is provided.

Abstract: The health state of a subject is automatically evaluated or predicted using at least one implantable device. In varying examples, the health state is determined by sensing or receiving information about at least one physiological process having a circadian rhythm whose presence, absence, or baseline change is associated with impending disease, and comparing such rhythm to baseline circadian rhythm prediction criteria. Other chronobiological rhythms beside circadian may also be used. The baseline prediction criteria may be derived using one or more past physiological process observation of the subject or population of subjects in a non-disease health state. The prediction processing may be performed by the at least one implantable device or by an external device in communication with the implantable device. Systems and methods for invoking a therapy in response to the health state, such as to prevent or minimize the consequences of predicted impending heart failure, are also discussed.

Abstract: A system comprising a heart sound sensor to produce a heart sound signal representative of at least one heart sound. A signal analyzer circuit measures a baseline time interval between a first detected physiologic cardiovascular event and at least one second detected physiologic cardiovascular event. At least one of the first and second detected physiologic cardiovascular events includes a heart sound event obtained from the heart sound signal. The sensor analyzer circuit determines that an ischemic event occurred at least in part by detecting a specified measured subsequent change from the established baseline time interval. Other systems and methods are disclosed.

Abstract: An apnea classification system provides for apnea monitoring and differentiation based on several sleep apnea related parameters for diagnostic and therapeutic purposes. Monitoring of such sleep apnea related parameters allows the apnea classification system to differentiate among the different types of apnea. This information may then be used to determine the best method of therapy, or adjust current therapy parameters to more effectively treat a subject.

Abstract: In an example, physiologic information about a patient can be obtained and mapped to a first set of fuzzy logic membership functions, and a symptom status can be derived from the mapping of the physiologic information using a first fuzzy logic inference. In an example, the symptom status can be mapped to a second set of fuzzy logic membership functions, and a disease status can be derived from the mapping of the symptom status to the second set of fuzzy logic membership functions using a second fuzzy logic inference.

Abstract: An apnea classification system provides for apnea monitoring and differentiation based on several sleep apnea related parameters for diagnostic and therapeutic purposes. Monitoring of such sleep apnea related parameters allows the apnea classification system to differentiate among the different types of apnea. This information may then be used to determine the best method of therapy, or adjust current therapy parameters to more effectively treat a subject.

Abstract: A system and method automatically classifies a patient's heart function status, such as by using an implantable medical device (IMD) to determine a physiological response to activity, and using that information to perform the classification. For example, a physical activity sensor and a physiological sensor are used to automatically classify patients into heart function status classes, such as NYHA classes or ACC/AHA classes. Changes in a patient's classification can be used to monitor heart function status over time and to monitor therapy responsiveness.

Abstract: Systems and methods provide for sensing, during an event of tachycardia, hemodynamic signals concurrently from at least two spatially separated locations within a patient, and quantifying a spatial relationship between the hemodynamic signals. Hemodynamic stability or state of the patient during the tachycardia event is determine based at least in part on the quantified spatial relationship. One or more anti-tachycardia therapies to treat the tachycardia may be selected based at least in part on the determined stability or state of patient hemodynamics, and the selected one or more anti-tachycardia therapies may be delivered to treat the tachycardia. The hemodynamic signals may comprise at least two, or a mixed combination, of cardiac impedance signals, cardiac chamber pressure signals, arterial pressure signals, heart sounds; and acceleration signals.

Abstract: Method and systems related to monitoring right ventricular function during pacing by a cardiac rhythm management device are described. One or more pacing parameters are selected to provide cardiac resynchronization therapy. For example, the one or more pacing parameters may be selected to provide an optimal or improved therapy. The heart is paced using the selected pacing parameters. While pacing with the selected parameters, pressure is sensed via a pressure sensor disposed the pulmonary artery. The sensed pressure is analyzed to determine right ventricular function achieved during the pacing using the selected pacing parameters. A signal, such as an alert signal or control signal, is generated based on the right ventricular function achieved during the pacing.

Abstract: Optimizing cardiac preload based on measured pulmonary artery pressure involves varying, for each repetition of an acute burst protocol, a parameter of pacing applied to a patient's heart during the acute burst protocol. Pulmonary artery pressure is measured during the repetitions of the acute burst protocol. An optimum ventricular preload is determined based on the measured pulmonary artery pressure. Pacing therapy is provided using a value of the parameter that is selected based on the determination of optimum ventricular preload.

Abstract: An example method includes monitoring a first posture including a first lateral decubitus posture (LDP), recording a first LDP record based on the first LDP, computing a first posture trend based on the first LDP record and determining and providing a wellness indication based on the first posture trend.

Abstract: A system and method for remotely evaluating patient compliance status is presented. Compliance to a course of treatment is periodically checked through qualitative inquiry of a patient under remote management. Physiometry of the patient, that indicates emotional state, is remotely monitored contemporaneously with the qualitative state. Patient status is evaluated, including at least one of corroborating the compliance and identifying an emotional imbalance, based upon the indicated emotional state of the patient.

Abstract: A system and method provide heart sound tracking, including an input circuit, configured to receive heart sound information, and a heart sound recognition circuit. The heart sound recognition circuit can be coupled to the input circuit and can be configured to recognize, within a particular heart sound of a particular heart sound waveform, a first intra heart sound energy indication and a corresponding first intra heart sound time indication using the heart sound information from the particular heart sound waveform and the heart sound information from at least one other heart sound waveform. The particular heart sound can include at least a portion of one of S1, S2, S3, and S4. Further, the first intra heart sound energy indication and the corresponding first intra heart sound time indication can correspond to the at least a portion of one of S1, S2, S3, and S4, respectively.