Abstract: Apparatuses and methods for extracting, de-noising, and analyzing electrocardiogram signals. Any of the apparatuses described herein may be implemented as a (or as part of a) computerized system. For example, described herein are apparatuses and methods of using them or performing the methods, for extracting and/or de-noising ECG signals from a starting signal. Also described herein are apparatuses and methods for analyzing an ECG signal, for example, to generate one or more indicators or markers of cardiac fitness, including in particular indicators of atrial fibrillation. Described herein are apparatuses and method for determining if a patient is experiencing a cardiac event, such as an arrhythmia.

Abstract: An implantable device for analyzing a high frequency (HF) electrogram signal including an implantable electrode, a signal pickup configured to pick up an electrogram signal including a HF component, a signal filter connected to the signal pickup and configured to measure a HF component from the signal only during a specific portion of a cardiac cycle, and an analyzer for analyzing the HF component, wherein the signal pickup, the signal filter and the analyzer are included within an implantable container, and the analyzer is configured to analyze at least one time-varying parameter of the HF component, and the signal filter is configured to measure the signal by using a signal picked up from at least one electrode selected from a group consisting of (a) intracardiac, (b) subcutaneous, (c) a can of the implanted device, (d) a combination of two of the above. Related apparatus and methods are also described.

Abstract: System, assembly and method are provided to facilitate reconstruction of cardiac information representing a complex rhythm disorder associated with a patient's heart to indicate a source of the heart rhythm disorder. The complex rhythm disorder can be treated by application of energy to modify the source of the rhythm disorder.

Abstract: A neurostimulation system measures a cardiac parameter at various cardiac intervals and analyzes its restitution, including computing a restitution slope being a rate of change of the restitution parameter with respect to change in the cardiac interval. In various embodiments, the system uses the restitution slope to provide for adaptive control of neurostimulation. In various embodiments, one or more cardiac parameters such as action potential duration (APD), conduction velocity (CV), QT interval (QT), and/or T-wave morphology (TM) parameter are measured and analyzed for restitution of each parameter, which is then used to control the delivery of the neurostimulation.

Abstract: System, assembly and method are provided to facilitate reconstruction of cardiac information representing a complex rhythm disorder associated with a patient's heart to indicate a source of the heart rhythm disorder. The complex rhythm disorder can be treated by application of energy to modify the source of the rhythm disorder.

Abstract: A peak-relevant value device acquires a peak-relevant value (for example, the peak value of an R wave (R peak value)) every cycle from an electrocardiogram acquired. The frequencies of the peak-relevant value acquired as time-series data and the magnitudes for the respective frequencies are analyzed. A peak-relevant value LF calculating device calculates an LF component (peak-relevant value LF component) from the frequency component of the peak-relevant value. An interval acquiring device acquires the interval between characteristic points of the electrocardiographic complex from the electrocardiogram acquired and the frequencies of the feature point interval acquired as time-series data to acquire the magnitudes of the respective frequency component are analyzed.

Abstract: A method, system, and device for detection of an arrhythmia, and discrimination between different types of arrhythmia, for example to determine whether to administer an electric shock to the heart, the device comprising a wearable monitor with electrodes that detect the electrical activity of a beating heart, attached to an embedded monitoring system having an amplifier, a microprocessor, a data storage device, and a power supply, all disposed on a substrate having large distal end portions that attach to the electrodes and a narrow intermediate portion that attaches to the monitoring system.

Abstract: Systems and methods are provided for the study of the cardiac rhythm variability. These systems and methods include the recording of the electrocardiogram (EKG), with subsequent calculation of the duration of the beat-to-beat intervals (i.e., R-R intervals), drawing up of the rhythmograms, and additional systems and methods that include determination of, throughout all observation times within particular intervals included in the recording periods, the average values of the informational entropy of the beta-distribution (AE) of the R-R intervals, the differences between the maximum and minimum values of the informational entropy of the beta-distribution (MDE) of the R-R intervals, the root-mean-square deviations of the informational entropy of the beta-distribution (RMSDE) of the R-R intervals, and/or variation factors of the informational entropy of the beta-distribution (VFE) by means of calculation of the informational entropy of the beta-distribution of the R-R intervals.

Abstract: The present invention is directed to a method for determining onset of ventricular arrhythmias using bounded-input bounded-output stability of QT interval (QTI) dynamics. The method of the present invention includes two parts. A first part of the method determines the dependence of each QTI on several prior QTIs and RR intervals (RRI). This determination is represented as an autoregressive model with exogenous input (ARX). A second part of the method determines the BIBO stability of the ARX model in the z-domain. The metrics associated with the first and second parts of the method are then used to predict onset of arrhythmia.

Abstract: A method for predicting drowsiness is disclosed. By obtaining average heart beat rate values of a driver, and according to the characteristics of the heart beat rate values over a period of time, the method is utilized to determine whether the human being is going to sleep. The method comprises the following steps: detecting a heart beat rate of a driver; calculating a curve of the heart beat rate average during a time interval of X minutes; determining an accumulated length of duration during which the calculated linear regression slope values are smaller than the predetermined slope value Z; determining whether the accumulated length of duration is greater than a time threshold T to generate a drowsiness detecting result; and determining whether to raise an alarm based on the drowsiness detecting result.

Abstract: In accordance with an aspect of the present invention, a system and method allows for the assessment of health and mortality based on dynamic nonlinear calculations of self-similar fluctuation patterns in a time series of QT intervals and of other physiological signals, such as RR intervals, temperature, blood pressure, respiration, saturation of peripheral oxygen, intracardiac pressures, and electroencephalogram. In order to nonlinearly determine health and mortality, time series of QT intervals and of other physiological signals (e.g.. RR intervals) are simultaneously obtained, and entropy values are calculated for each signal over the same temporal interval. “EntropyX” is calculated from relative changes between moments and entropy of QT intervals and those of other physiological signals over seconds to days. The absolute and relative entropy values at a specific time point and/or subsequent changes in entropy over future time points can be used to determine a treatment plan for the subject.

Abstract: A heart monitor is disclosed. The monitor computes ST segment deviations and stores the results in heart rate based histograms. Periodically, the monitor analyzes the histogram data to determine heart rate dependent acute ischemia detection thresholds. If the statistical distribution associated with a heart rate range is insufficient, the threshold for that heart rate range is set as a function of the threshold for a neighboring heart rate range. Thresholds are also increased for heart rate ranges associated with statistical distributions that are sufficient but that have a relatively small number of entries.

Abstract: Disclosed herein is a framework for facilitating patient signal analysis. In accordance with one aspect, at least one region of interest within a cycle of a waveform of patient signal data is identified. The identified region of interest may be segmented into portions using amplitude percentage categories. A sequential morphological data series may be generated by compiling time intervals of the segmented portions. One or more sequential signal parameters may be calculated based on the sequential morphological data series. A report may then be generated based at least in part on the one or more sequential signal parameters.

Abstract: A method for graphical representation of a train of ECG complexes having an R wave and a T-P interval and having variable isoelectric baselines. The method involves aligning the complexes in terms of signal amplitude by obtaining a baseline, thereby to provide a graphical representation of said train of ECG complexes; and aligning said complexes temporally using corresponding predetermined points.

Abstract: A method for tracking cardiac conditions is disclosed. An electrical signal from a patient's heart is sensed. A heart signal parameter value and an associated heart rate value are computed from the electrical signal. Based on the heart rate value, one of a plurality of histograms stored in a histogram memory is updated with the heart signal parameter value. After a data collection time period has elapsed, a statistical value of the heart signal parameter is computed from the selected histogram. A detection threshold for abnormal values of the heart signal parameter is then computed based on the statistical value.

Abstract: Disclosed is an arrhythmia-diagnosing method and device for diagnosing arrhythmias, such as fibrillation or tachycardia. The arrhythmia-diagnosing method includes the following steps: measuring (a) the heart characteristic length, and the (b) frequency and (c) conduction velocity of the cardiac electrical wave; and (d) determining the occurrence or absence of an arrhythmia by using the three parameters measured in steps (a) to (c). With this invention, it is possible to predict and diagnose an electrical wave tornado, one of the causes of arrhythmia, by using a non-dimensional parameter, to identify patients at risk of death or brain death due to an arrhythmia and to reduce the mortality of patients suffering from arrhythmias significantly.

Abstract: A method of mapping cardiac electrical activity includes the acquisition of electrophysiological signals and using signal processing hardware to process such signals to identify lateness attributes thereof. If the lateness attribute exceeds a lateness threshold, then the corresponding point on the patient's heart can be designated as a therapy (e.g., ablation) target. It is also contemplated to use an upper bound on the lateness threshold, such that the corresponding point on the patient's heart is only designated as a therapy target if the lateness attribute both exceeds the lateness threshold and does not exceed the lateness bound. Both late activation (“Late-A”) and late potential (“Late-P”) attributes are contemplated.

Abstract: Described herein are implantable systems and devices, and methods for use therewith, that can be used to perform arrhythmia discrimination. A plurality of different sensing vectors are used to obtain a plurality of different IEGMs, each of which is indicative of cardiac electrical activity at a different ventricular region. The plurality of different IEGMs can include, e.g., an IEGM indicative of cardiac electrical activity at a first region of the patient's left ventricular (LV) chamber and an IEGM indicative of cardiac electrical activity at a second region of the patient's LV chamber. Additionally, the plurality of different IEGMs can further include an IEGM indicative of cardiac electrical activity at a region of a patient's right ventricular (RV) chamber. For each of the IEGMs, there is a determination of a corresponding localized R-R interval stability metric indicative of the R-R interval stability at the corresponding ventricular region. This can include, e.g.

Abstract: A medical device performs a method to classify a cardiac rhythm. Differences between cycle lengths in a first heart chamber are determined during an established time interval. Evidence of ectopy associated with irregular coupling intervals is detected from the signal during the established time interval. A rhythm classification output corresponding to a second heart chamber at the expiration of the established time interval is provided in response to the consecutive cycle length differences and the evidence of ectopy associated with irregular coupling intervals.

Abstract: A heart monitor is disclosed. The monitor computes ST segment deviations and stores the results in heart rate based histograms. Periodically, the monitor analyzes the histogram data to determine a normal range of ST deviation for a particular heart rate range. The monitor computes heart rate dependent ischemia detection thresholds based on the upper and lower boundaries of the normal range.

Abstract: A system include circuitry to receive information from a mobile device including ECG data representative of a beating heart, circuitry to analyze the ECG data using at least one pattern to detect a notable finding in the ECG data and circuitry to determine at least one pattern to send to the mobile device, based on the analysis of the ECG data. The system sends the at least one determined pattern to the mobile device.

Abstract: A patient QRS duration can be received or determined, such as using one or more patient physiological sensors. A portion of the QRS duration can be determined, such as a right or left ventricular activation time. In an example, the right ventricular activation time can be determined by identifying an onset of a QRS complex and an R-wave peak in the QRS complex. In an example, when the QRS duration exceeds a threshold duration, and the RV activation time does not exceed a second threshold duration, an indication of a cardiac conduction dysfunction can be provided, such as for discriminating between left bundle branch block and right bundle branch block.

Abstract: A medical device system performs a method determining presence of scar tissue. Torso-surface potential signals are received by a processor from multiple electrodes distributed on a torso of a patient. The processor extracts features of the potential signal from each electrode and stores values of the features in a non-transitory storage medium. The processor determines a scar indicator index for each of the electrodes from the stored features and identifies which ones of the electrodes have an affirmative scar indicator index. An overall scar burden index is determined as a proportion of the electrodes with an affirmative scar indicator index.

Abstract: The present invention is directed toward a detection architecture for use in implantable cardiac rhythm devices. The detection architecture of the present invention provides methods and devices for discriminating between arrhythmias. Moreover, by exploiting the enhanced specificity in the origin of the identified arrhythmia, the detection architecture can better discriminate between rhythms appropriate for device therapy and those that are not.

Abstract: An implantable cardioverter defibrillator (ICD) senses ventricular depolarizations (R-waves) in an electrogram signal to detect a ventricular tachycardia or fibrillation episodes. The EGM signal is also monitored in real time for characteristics that uniquely identify instances of T-wave oversensing. The ICD determines whether detection of a tachycardia or fibrillation episode is appropriate based upon counts of each of the unique characteristics evidencing T-wave oversensing.

Abstract: An implantable device and method for monitoring changes in the risk of arrhythmia induced by medications. The implantable device monitors risk of arrhythmia by analyzing an aspect of T-wave morphology to generate a metric of transmural dispersion of repolarization (“TDR”) as a proxy for the risk of arrhythmia. The implantable device generates an index of change in the risk of arrhythmia by comparing values of the metric of TDR obtained for different time periods. The implantable device generates a warning if the change in risk of arrhythmia is outside acceptable limits. The implantable device can also communicate with other devices to correlate changes in risk of arrhythmia with medications taken by the patient.

Abstract: A method for graphical representation of a train of ECG complexes having an R wave and a T-P interval and having variable isoelectric baselines. The method involves aligning the complexes in terms of signal amplitude by obtaining a baseline, thereby to provide a graphical representation of said train of ECG complexes; and aligning said complexes temporally using corresponding predetermined points.

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: A biological information displaying apparatus includes an analyzing unit and a display unit. The analyzing unit analyzes measured continuous biological information waveforms to detect abnormal biological information waveforms.

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: ECG data may be processed in a mobile device by receiving a stream of filtered ECG data samples comprising PQRST pattern cycles. An R point of a PQRST pattern in the filtered ECG data is determined. A portion of samples is selected from the filtered ECG data surrounding the R point. QRS duration of the PQRST pattern is then determined by processing the selected portion of samples using an application program executed by the mobile device.

Abstract: A system for heart performance characterization uses an interface to receive waveform signal data representing electrical activity of a patient heart over at least one heart beat cycle. The signal processor uses a signal peak and amplitude detector for, identifying a first signal portion of a first heart cycle of the signal data, identifying multiple different amplitude levels within the first signal portion, determining a first area under the waveform in the first signal portion corresponding to at least one particular amplitude level and deriving a parameter in response to the determined first area. The output processor generates an alert message if at least one of, (a) the derived parameter and (b) a difference between the derived parameter and a corresponding derived parameter for a different heart cycle for the same patient, exceeds a predetermined threshold value.

Abstract: A method for identifying a target arrhythmia, for example, atrial fibrillation, with very high specificity includes obtaining heart rhythm data such as EKG data, selecting and analyzing a segment of the data for arrhythmia, if an arrhythmia is found then reanalyzing the segment of data for a hidden regularity that would indicate the data is not the target arrhythmia. If no hidden regularity is found, then identifying the segment as the target arrhythmia.

Abstract: Systems and methods are provided to detect and analyze arrhythmia drivers. In one example, a system can include a wave front analyzer programmed to compute wave front lines extending over a surface for each of the plurality of time samples based on phase information computed from electrical data at nodes distributed across the surface. A trajectory detector can be programmed to compute wave break points for each of the wave front lines and to determine a trajectory of at least one rotor core across the surface. A stability detector can be programmed to identify at least one stable rotor portion corresponding to subtrajectories of the determined trajectory.

Abstract: A microprocessor configured to receive and process digitized signals derived from an analogue ECG signal is provided. An example microprocessor comprises a beat detection unit configured to receive the in-phase and quadrature phase band power signals, calculate a band power value and an adaptive threshold value, and compare said band power value with said adaptive threshold value to detect a QRS complex of the ECG signal indicative of a detected valid beat; and an R peak detection unit configured to receive the digital ECG signal and information about the detected valid beat, select a portion of the received ECG signal as a first time window around the detected valid beat; determine the location of a first R peak position; and perform a time domain search in a second time window around said first R peak position in order to refine the location of an R peak position.

Abstract: A health sensing device is described for placement on a user. The device may include a sensor, a filter, and a transmitter. The sensor is configured to sense one or more factors relating to an indicator of a health related condition or occurrence. The filter is configured to evaluate a signal from the sensor and determine if the indicator has been detected. The transmitter is arranged for initiating a transmission based on a signal from the filter. The sensor can include one or more microphone devices, accelerometers, and/or MEMS devices. A method of monitoring a user for a health related condition is also described.

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 systems are disclosed for analyzing three dimensional orthogonal ECG measurements to assess patient risk of a subsequent cardiac event based on evaluation of cardiac vector values in view of risk factors defined by the invention.

Abstract: A system comprises a cardiac signal sensing and a processing circuit. The cardiac signal sensing circuit senses a first cardiac signal segment that includes a QRS complex and a second cardiac signal segment that includes a fiducial indicative of local ventricular activation. The processor circuit includes a site activation timer circuit configured to determine a time duration between a fiducial of the QRS complex of the first cardiac signal segment and the fiducial of the second cardiac signal segment. The processor circuit is configured to generate, using the determined time duration, an indication of optimality of placement of one or more electrodes for delivering therapy and provide the indication to at least one of a user or process.

Abstract: The estimated contour positions of the atrium and ventricle are obtained from multi-channel electrocardiographic waveforms. Information useful to predict the possibility of the occurrence of fatal arrhythmia, such as the position of the maximum excitation propagation point, the distribution of the late potential(LP) as an index of depolarization abnormality, and the distribution of the RT dispersion as an index of repolarization abnormality are displayed together with the estimated contour positions.

Abstract: A method of analyzing myocardial instability includes obtaining a physiological parameter representative of myocardial behavior over a set of cardiac cycles and determining reversal points in the physiological parameter over the set of cardiac cycles. The method also includes identifying myocardial instability based on the reversal points in the physiological parameter. A reversal point may correspond to a value of the physiological parameter, during a current cardiac cycle, that exceeds or is less than the values of the physiological parameter during prior and subsequent cardiac cycles. Optionally, the method includes calculating differences between values of the physiological parameter for consecutive cardiac cycles and detecting the reversal points when a current difference exceeds or is less than differences for prior and subsequent cardiac cycles.

Abstract: An active implantable medical device (e.g., implantable pacemaker or defibrillator), for detection of QRS complexes in noisy signals. Functional units (12-16) collect, amplify, prefilter and convert from analog-to-digital an endocardial signal, and digital functional units (18) provide signal processing and analysis of the digitized signal, for delivery of an indicator corresponding to a signal peak detection representative of the presence of a QRS complex in the endocardial signal. A double threshold comparator (30) is employed, receiving as input (28) the digitized signal and outputting (40) the indicator of peak detection when, cumulatively: the amplitude (A) of the input signal exceeds a peak amplitude threshold (SA), and the peak amplitude threshold is exceeded for a period (W) greater than a peak width threshold (SW). The peak amplitude threshold (SA) is a variable adaptive threshold, according to a noise level calculated from the energy (RMS) of the input signal.

Abstract: A system for heart performance characterization and abnormality detection includes an interface for receiving signal data representing an electrical signal indicating electrical activity of a patient heart over multiple heart beat cycles. A signal processor uses the received signal data in calculating at least one of, (a) a first signal characteristic value substantially comprising a ratio of a time interval from S wave to T wave, to a time interval from Q wave to S wave and (b) a second signal characteristic value substantially comprising a ratio of a T wave base voltage from a peak of a T wave to a zero base reference voltage, to an R wave base voltage from a peak of an R wave to a zero base reference voltage. A comparator compares at least one of the first and second characteristic values with a threshold value to provide a comparison indicator.

Abstract: System, assembly and method are provided to facilitate reconstruction of cardiac information representing a complex rhythm disorder associated with a patient's heart to indicate a source of the heart rhythm disorder. The complex rhythm disorder can be treated by application of energy to modify the source of the rhythm disorder.

Abstract: Detecting cardiac ischemia by detecting local changes in high frequency ECG parameters. Local changes may be, for example, local reduction in RMS of high frequency components, for example, during a stress test.

Abstract: Techniques are described for distinguishing between treatable and non-treatable heart rhythms. A medical device that operates in accordance with the techniques analyzes characteristics over several cardiac event intervals to detect initiation of a sudden rate onset. After detection of the initiation of the sudden rate onset, the IMD analyzes a morphology of an EGM associated with a selected cardiac event within the first several beats after the initiation of sudden rate onset. In one example, the IMD analyzes the morphology of the EGM associated with the first cardiac event immediately subsequent to the initiation of the sudden rate onset. If the morphology of the EGM of the selected cardiac event is abnormal compared to template EGM, the rhythm is classified as treatable. Otherwise, the rhythm is classified as non-treatable.

Abstract: A heart monitor computes ST segment deviation as the difference in the value of an electrocardiogram signal at the ST and PQ points of a heartbeat. The ST point is found based on slope criteria and temporal criteria. The maximum (positive) slope of the QRS (maxQRS) is located. Within a preset window after the maxQRS point, the processor searches for a sample at which the second finite difference is less than a threshold that is a function of average QRS amplitude. If such a qualifying sample is found, the processor examines its location relative to the location of an adaptive window that is centered on a sample that is an adaptively determined distance from the peak of the R wave. If the qualifying point is within the adaptive window, it is chosen as the ST point. If the qualifying point is after the adaptive window, the ST point is set at the end of the adaptive window. Finally, if the qualifying point is before the adaptive window, the ST point is selected at the beginning of the adaptive window.

Abstract: A medical device and associated method for classifying an unknown cardiac signal operate to sense a cardiac signal over known cardiac cycles and generate a template of the known cardiac cycles. An unknown cardiac signal is sensed over an unknown cardiac cycle. A template alignment point and an unknown cardiac signal alignment point are identified by using a fourth order difference signal. The template and the unknown cardiac signal are aligned across an alignment window by aligning the template alignment point and the unknown cardiac signal alignment point. A morphology match metric measuring a similarity between the aligned template and the unknown cardiac signal is computed.

Abstract: In general, this disclosure is directed to signal processing based methods to reject undersensing in a signal indicative of cardiac activity, e.g., ECG. The undersensing may be due to very small signal amplitudes or due to a sudden increase in single peak amplitude resulting in an increased sensing threshold. The undersensing may result in falsely detecting a cardiac event, e.g., asystole or bradycardia. The techniques of this disclosure monitor the behavior of the signal to determine when a detected asystole is false.

Abstract: Disclosed herein are methods, systems, and apparatus for detecting an epilepsy event in a patient using a medical device. The medical device is capable of determining an occurring epilepsy event, for example a seizure or an increased risk of a seizure. The determination is performed by determining at least one NNXX value from the beat sequence of the patient's heart. The medical device may then take a responsive action, such as warning, logging the time of the seizure, computing and storing one or more seizure severity indices, and treating the epilepsy event.