Abstract: Cardiac systems and methods provide for discriminating between supraventricular tachyarrhythmia and ventricular tachyarrhythmia based on a determination that the patient's supraventricular rhythm exhibits rate dependency. One approach involves determining if a patient's supraventricular rhythm exhibits rate dependent morphology. If the patient's supraventricular rhythm is determined to exhibit rate dependent morphology, an implantable device classifies a detected tachyarrhythmia episode based on one or more templates selected from a plurality of rate-indexed templates stored in the device. Determining if the supraventricular rhythm exhibits rate dependent morphology may also include determining one or more rates at which the rate dependent morphology occurs.

Abstract: The present invention provides a system and method for representing quasi-periodic (“qp”) waveforms comprising, representing a plurality of limited decompositions of the qp waveform, wherein each decomposition includes a first and second amplitude value and at least one time value. In some embodiments, each of the decompositions is phase adjusted such that the arithmetic sum of the plurality of limited decompositions reconstructs the qp waveform. These decompositions are stored into a data structure having a plurality of attributes. Optionally, these attributes are used to reconstruct the qp waveform, or patterns or features of the qp wave can be determined by using various pattern-recognition techniques. Some embodiments provide a system that uses software, embedded hardware or firmware to carry out the above-described method. Some embodiments use a computer-readable medium to store the data structure and/or instructions to execute the method.

Abstract: The present invention provides a system and method for representing quasi-periodic (“qp”) waveforms comprising, representing a plurality of limited decompositions of the qp waveform, wherein each decomposition includes a first and second amplitude value and at least one time value. In some embodiments, each of the decompositions is phase adjusted such that the arithmetic sum of the plurality of limited decompositions reconstructs the qp waveform. These decompositions are stored into a data structure having a plurality of attributes. Optionally, these attributes are used to reconstruct the qp waveform, or patterns or features of the qp wave can be determined by using various pattern-recognition techniques. Some embodiments provide a system that uses software, embedded hardware or firmware to carry out the above-described method. Some embodiments use a computer-readable medium to store the data structure and/or instructions to execute the method.

Abstract: An implantable cardiac rhythm management (CRM) device delivers a chronic therapy while detecting an ischemic state. When the ischemic state indicates the occurrence of an ischemic event, the implantable CRM device delivers a post-ischemia therapy. The post-ischemia therapy and the chronic therapy are adjusted using feedback control with the ischemic state and parameters indicative of the effectiveness of the post-ischemic therapy and the effectiveness of the chronic therapy as inputs.

Abstract: Cardiac systems and methods provide for discriminating between supraventricular tachyarrhythmia and ventricular tachyarrhythmia based on a determination that the patient's supraventricular rhythm exhibits rate dependency. One approach involves determining if a patient's supraventricular rhythm exhibits rate dependent morphology. If the patient's supraventricular rhythm is determined to exhibit rate dependent morphology, an implantable device classifies a detected tachyarrhythmia episode based on one or more templates selected from a plurality of rate-indexed templates stored in the device. Determining if the supraventricular rhythm exhibits rate dependent morphology may also include determining one or more rates at which the rate dependent morphology occurs.

Abstract: In a method for determining a cardiac condition, a sensed physiologic signal for a period of time including multiple cardiac cycles is received. Using the received physiologic data, a heart beat frequency to be used as a reference frequency is determined. A plurality of harmonics of the received physiologic signal is extracted based on the reference frequency, wherein the harmonics correspond to a plurality of alternans frequencies. Amplitudes of at least some of the extracted harmonics are determined, and are used to determine an alternans indicator value.

Abstract: A system, method, or device determines whether noise is present on a sampled and/or digitized sensed intrinsic cardiac signal based on a moving count of turning/inflection points of the signal. If noise is detected, the manner in which the cardiac signal is acquired, or the manner in which the device operates in response to the acquired cardiac signal (or both) is altered to reduce the risk of erroneously detecting noise as a heart depolarization and, therefore, inappropriately triggering or withholding therapy.

Abstract: A system, method, or device determines whether noise is present on a sampled and/or digitized sensed intrinsic cardiac signal based on a moving count of turning/inflection points of the signal. If noise is detected, the manner in which the cardiac signal is acquired, or the manner in which the device operates in response to the acquired cardiac signal (or both) is altered to reduce the risk of erroneously detecting noise as a heart depolarization and, therefore, inappropriately triggering or withholding therapy.

Abstract: A method of analyzing an elecotrocardiogram (ECG) waveform, the method including obtaining a series of digital values representing the ECG waveform having a plurality of cycles, with each cycle having a T-wave feature. The method includes comparing a first prototype wavelet to a portion of the series of digital values representing a selected number of cycles of the ECG waveform, wherein the first prototype wavelet is defined by a first set of wavelet parameters having an initial set of first parameter values, and adjusting the initial set of first parameter values to obtain a matched prototype wavelet defined by the first set of wavelet parameters having a matched set of first parameter values for each of the T-wave features of the selected number of cycles, wherein each matched prototype wavelet substantially matches the corresponding T-wave feature.

Abstract: A method of analyzing a signal, the method including obtaining a series of digital values representative of a quasi-period waveform having a plurality of cycles, with each cycle having at least a first target feature. The method includes comparing a first prototype wavelet to a portion of the series of digital values representing at least the first target feature of a selected number of cycles of the quasi-periodic waveform, wherein the first prototype wavelet is defined by a first set of wavelet parameters. A matched set of first parameter values is determined for the first set of wavelet parameters which define a matched wavelet for each of the first target features of the selected number of cycles, wherein each matched wavelet substantially matches the corresponding first target feature.

Abstract: A physiological signal monitoring and analysis system including an implantable medical device and a signal processor. The implantable medical device is configured to monitor and record sample segments of at least one physiological signal of a patient at time separated recording intervals over a time period. The signal processor configured to measure values of at least one selected characteristic of the at least one physiological signal from the recorded sample segments, to determine trend information representing a trend in the at least one selected characteristic based on the measured values, and to assess a risk of a physiological event to the patient based on the trend information.

Abstract: Estimating a frequency of a sampled cardiac rhythm signal and classifying the rhythm. The received signal is sampled and transformed into a curvature series. A lobe in the curvature series corresponds to a characteristic point in the sampled series. Characteristic points are selected based on a time of a lobe in the curvature series and, in one embodiment, an amplitude of the signal at the time of the lobe. A frequency of the sampled series is estimated by autocorrelating a function of the series of the characteristic points. In one embodiment, the function is a time difference function. The rhythm is classified by plotting the timewise proximity of characteristic points derived from an atrial signal with characteristic points derived from a ventricular signal. Regions of the plot are associated with a particular rhythm and the grouping of the data corresponds to the classification.

Abstract: A system for implementing a cardiac device having adaptive treatment therapies utilizing a neural network based learning engine is disclosed. The system includes an implantable cardiac device module and an external data processing system for specifying the operating characteristics of the cardiac device module. Both the cardiac device module and the external processing system possess an artificial neural network to specify the operation of the cardiac device module as it provides adaptive treatment therapies. The external data processing system includes a complete neural network module that trains and validates the operation of the neural network to match the optimal treatment options with a received set of collected patient data. A runtime neural network module that provides real time operation of the neural network using collected patient data is located within the cardiac device module. The cardiac device module and the external processing module are connected via a communication link.

Abstract: Cardiac systems and methods provide for discriminating between supraventricular tachyarrhythmia and ventricular tachyarrhythmia based on a determination that the patient's supraventricular rhythm exhibits rate dependency. One approach involves determining if a patient's supraventricular rhythm exhibits rate dependent morphology. If the patient's supraventricular rhythm is determined to exhibit rate dependent morphology, an implantable device classifies a detected tachyarrhythmia episode based on one or more templates selected from a plurality of rate-indexed templates stored in the device. Determining if the supraventricular rhythm exhibits rate dependent morphology may also include determining one or more rates at which the rate dependent morphology occurs.

Abstract: Cardiac arrhythmias are classified based on the morphology of the arrhythmia episode beats. Templates are formed using morphological features of the cardiac beats of the episode. The arrhythmia episode is classified as a monomorphic tachyarrhythmia or polymorphic tachyarrhythmia based on the one or more templates. The arrhythmia episode may be classified based on a number templates formed from the arrhythmia episode. The templates are formed by determining a measure of similarity between morphological features of a cardiac beat to a template. The similarities can be determined based on a pairing rule that determines which beat morphologies are compared. Selection of therapy for treating the arrhythmia episode may depend on the historical success of a therapy at mitigating previous arrhythmias of the same type as the arrhythmia episode.

Abstract: A cardiac device system for implementing a cardiac device having adaptive treatment therapies utilizing a neural network based learning engine includes an implantable cardiac device module and an external data processing system for specifying the operating characteristics of the cardiac device module. Both the cardiac device module and the external processing system possess an artificial neural network to specify the operation of the cardiac device module as it provides adaptive treatment therapies. The external data processing system includes a complete neural network module that trains and validates the operation of the neural network to match the optimal treatment options with a received set of collected patient data. In contrast, a runtime neural network module that only provides real time operation of the neural network using collected patient data is located within the cardiac device module.

Abstract: An implantable cardiac rhythm management (CRM) device delivers a chronic therapy while detecting an ischemic state. When the ischemic state indicates the occurrence of an ischemic event, the implantable CRM device delivers a post-ischemia therapy. The post-ischemia therapy and the chronic therapy are adjusted using feedback control with the ischemic state and parameters indicative of the effectiveness of the post-ischemic therapy and the effectiveness of the chronic therapy as inputs.

Abstract: Cardiac monitoring and/or stimulation methods and systems provide for monitoring, diagnosing, defibrillation and pacing therapies, or a combination of these capabilities, including cardiac systems incorporating or cooperating with neuro-stimulating devices, drug pumps, or other therapies. Embodiments of the present invention relate generally to implantable medical devices employing automated cardiac activation sequence monitoring and/or tracking for arrhythmia discrimination. Embodiments of the invention are directed to devices and methods involving sensing a plurality of composite cardiac signals using a plurality of implantable electrodes. A source separation is performed using the sensed plurality of composite cardiac signals and the separation produces one or more cardiac signal vectors associated with one or more cardiac activation sequences that is indicative of ischemia. A change of the one or more cardiac signal vectors is detected using the one or more cardiac signal vectors.

Abstract: Cardiac monitoring and/or stimulation methods and systems that provide one or more of monitoring, diagnosing, defibrillation, and pacing. Cardiac signal separation is employed to detect, monitor, track and/or trend closed-loop cardiac resynchronization therapy using cardiac activation sequence information. Devices and methods involve sensing a plurality of composite cardiac signals using a plurality of electrodes, the electrodes configured for implantation in a patient. A source separation is performed using the sensed plurality of composite cardiac signals, producing one or more cardiac signal vectors associated with all or a portion of one or more cardiac activation sequences. A cardiac resynchronization therapy is adjusted using one or both of the one or more cardiac signal vectors and the signals associated with the one or more cardiac signal vectors.

Abstract: The present invention provides a system and method for representing quasi-periodic (“qp”) waveforms comprising, representing a plurality of limited decompositions of the qp waveform, wherein each decomposition includes a first and second amplitude value and at least one time value. In some embodiments, each of the decompositions is phase adjusted such that the arithmetic sum of the plurality of limited decompositions reconstructs the qp waveform. These decompositions are stored into a data structure having a plurality of attributes. Optionally, these attributes are used to reconstruct the qp waveform, or patterns or features of the qp wave can be determined by using various pattern-recognition techniques. Some embodiments provide a system that uses software, embedded hardware or firmware to carry out the above-described method. Some embodiments use a computer-readable medium to store the data structure and/or instructions to execute the method.