Abstract: An example device for detecting one or more parameters of a cardiac signal is disclosed herein. The device includes one or more electrodes and sensing circuitry configured to sense a cardiac signal via the one or more electrodes. The device further includes processing circuitry configured to determine an R-wave of the cardiac signal and determine whether the R-wave is noisy. Based on the R-wave being noisy, the processing circuitry is configured to determine whether the cardiac signal around a determined T-wave is noisy. Based on the cardiac signal around the determined T-wave not being noisy, the processing circuitry is configured to determine a QT interval or a corrected QT interval based on the determined T-wave and the determined R-wave.

Abstract: Medical apparatus includes a probe configured for insertion into a chamber of a heart of a patient and including one or more intracardiac electrodes. Interface circuitry acquires intracardiac electrogram signals from the intracardiac electrodes and electrocardiogram (ECG) signals from body-surface electrodes that are fixed to a body surface of the patient. A processor detects, in each of the heartbeats in the sequence, a P wave in the acquired ECG signals and identifies one or more of the heartbeats in the sequence as ectopic beats responsively to a morphology of the detected P wave in the heartbeats. The processor extracts electrophysiological parameters from the intracardiac electrogram signals acquired during the sequence of the heartbeats and generates a map of the extracted electrophysiological parameters while excluding from the map the intracardiac electrogram signals that were received during the ectopic beats.

Abstract: Systems and methods for detecting arrhythmias in cardiac activity are provided and include memory to store specific executable instructions. One or more processors are configured to execute the specific executable instructions for obtaining first and second far field cardiac activity (CA) data sets over primary and secondary sensing channels, respectively, in connection with a series of beats. The system detects candidate atrial features from the second CA data set, identifies ventricular features from the first CA data set and utilizes the ventricular features to separate beat segments within the second CA data set. The system automatically iteratively analyzes the beat segments by overlaying an atrial activity search window with the second CA data set and determines whether one or more of the candidate atrial features occur within the atrial activity search window.

Abstract: Computer implemented methods and systems for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains a far field cardiac activity (CA) data set that includes far field CA signals for beats. The method applies a feature enhancement function to the CA signals to form an enhanced feature in the CA data set. The method calculates an adaptive sensitivity level and sensitivity limit based on the enhanced feature from one or more beats within the CA data set and automatically iteratively analyzes a beat segment of interest by comparing the beat segment of interest to the current sensitivity level to determine whether one or more R-waves are present within the beat segment of interest.

Abstract: This invention generally relates to methods useful for measuring heart rate, respiration conditions, and oxygen saturation and a wearable device that incorporate those methods with a computerized system supporting data collection, analysis, readout and sharing. Particularly this present invention relates to a wearable device, such as a wristwatch or ring, for real time measuring heart rate, respiration conditions, and oxygen saturation.

Abstract: An example device for detecting one or more parameters of a cardiac signal is disclosed herein. The device includes one or more electrodes and sensing circuitry configured to sense a cardiac signal via the one or more electrodes. The device further includes processing circuitry configured to determine an R-wave of the cardiac signal and determine a previous RR interval of the cardiac signal and a current RR interval of the cardiac signal based on the determined R-wave. The processing circuitry is further configured to determine a search window based on one or more of the current RR interval or the previous RR interval, determine a T-wave of the cardiac signal in the search window, and determine a QT interval based on the determined T-wave and the determined R-wave.

Abstract: An apparatus for generating a prediction that a patient will experience a seizure by monitoring a patient's body temperature over time is provided. The apparatus may include a sensor to sense temperature. The apparatus may monitor, using the sensor, the body temperature of the patient and compare the body temperature over a first period of time and a second period of time. The apparatus may generate a prediction of whether the patient will experience a seizure following the second period of time based at least in part on a result of the comparing.

Abstract: Continuously monitoring heart rhythm can include grouping, using computer hardware, a plurality of inter-beat intervals (IBI) data for a user into a plurality of epochs, wherein each epoch includes a subset of the IBI data corresponding to a predetermined time span. For each epoch, a selected feature set selected from a plurality of feature sets is extracted based on a determination of temporal consistency of the epoch. A plurality of epoch classifications may be generated for the epochs using a selected feature processor, wherein each epoch classification indicates whether arrhythmia is detected for the epoch from which the epoch classification is generated. The selected feature processor is selected from a plurality of different feature processors on a per-epoch basis based on the selected feature set extracted from the epoch. An indication of arrhythmia may be output, via an output device of the computer hardware, based on the epoch classifications.

Abstract: A method for creating alarm signals based on time-series signal behavior determined from real-time discrete data obtained from a medical device. In one embodiment the method includes identifying patterns in preceding time-series measurement threshold breaches in clinical readings obtained from said medical device when associated with a particular patient, and initiating an alarm signal to a front-line clinician based on the preceding quantity of threshold breaches.

Abstract: Medical apparatus includes a probe configured for insertion into a chamber of a heart of a patient and including one or more intracardiac electrodes. Interface circuitry acquires intracardiac electrogram signals from the intracardiac electrodes and electrocardiogram (ECG) signals from body-surface electrodes that are fixed to a body surface of the patient. A processor detects, in each of the heartbeats in the sequence, a P wave in the acquired ECG signals and identifies one or more of the heartbeats in the sequence as ectopic beats responsively to a morphology of the detected P wave in the heartbeats. The processor extracts electrophysiological parameters from the intracardiac electrogram signals acquired during the sequence of the heartbeats and generates a map of the extracted electrophysiological parameters while excluding from the map the intracardiac electrogram signals that were received during the ectopic beats.

Abstract: An apparatus comprises an arrhythmia detection circuit configured to: receive a cardiac signal representative of cardiac activity of a subject; apply a first arrhythmia detection criteria to the received cardiac signal; apply, in response to the applied first arrhythmia detection criteria producing a positive indication of arrhythmia, a second arrhythmia detection criteria to the received cardiac signal, wherein the second arrhythmia detection criteria is more specific to detection of arrhythmia than the first detection criteria; detect, in response to the applied first and second arrhythmia detection criteria, a sensing event indicating one or both of the first and second arrhythmia detection criteria are susceptible to false indications of arrhythmia; and adjust, in response to a detected sensing event, sensitivity or specificity of one or both of the first and second arrhythmia detection criteria.

Abstract: An exercise intensity estimation apparatus includes an RS wave calculation unit configured to calculate an RS amplitude from a peak value of an R wave to a peak value of an S wave in an ECG waveform of a target person, a T wave calculation unit configured to calculate an amplitude of a T wave of the ECG waveform, a heart rate calculation unit configured to calculate a heart rate from the ECG waveform, an index calculation unit configured to calculate, as a first index indicating exercise intensity of the target person, the amplitude of the T wave normalized by the RS amplitude, and an index calculation unit configured to calculate, as a second index indicating the exercise intensity of the target person, a value obtained by multiplying the first index by the heart rate.

Abstract: A method is implemented by a computer, and includes: (a) acquiring at least one set of waveform data having a time duration from physiological information waveform data; (b) classifying a waveform included in the waveform data into a predetermined type of waveform; (c) determining validity of a classification result of the waveform; and (d) correcting the classification result in accordance with the validity of the classification result.

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: A method and system for low-distortion denoising of an ECG signal are disclosed. The method comprises determining at least one beat of the ECG signal for denoising using a beat selection logic and denoising the at least one beat using at least one ensemble averaging filter. The system includes a sensor to detect the ECG signal, a processor coupled to the sensor, wherein the processor includes a beat selection logic unit, and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to determine at least one beat of the ECG signal for denoising using a beat selection logic and to denoise the at least one beat using at least one ensemble averaging filter.

Abstract: A system is provided for isolating a hidden waveform representing hidden information from a composite waveform. The system comprises a processor; a memory configured to store instructions executable by the processor; and a comparator. The instructions cause the processor to estimate that portion of a received composite waveform that represents a first signal source and generate a waveform that represents an estimated first signal source. The comparator comprises a first input coupled to receive the composite waveform and a second input coupled to receive the generated waveform from the processor. The comparator is configured to subtract the generated waveform from the composite waveform and output a resulting estimated hidden waveform, representing the hidden information.

Abstract: Technology for transmitting and receiving a biosignal based on a pattern related to the biosignal and a feature point included in the biosignal. A biosignal transmitter includes a biosignal obtaining unit configured to obtain a biosignal comprising a plurality of unit signals, a parsing unit configured to parse the biosignal to extract a first unit signal of the plurality of unit signals, a pattern obtaining unit configured to obtain a pattern related to the biosignal based on the first unit signal, and a transmitting unit configured to transmit information related to a feature point of the first unit signal based on the first unit signal and the pattern.

Abstract: Disclosed herein is a framework for facilitating patient signal analysis based on vector analysis. In accordance with one aspect, a set of vectors is generated from a patient signal data waveform. The vectors may be directed from a common center to points of interest on the patient signal data waveform. The framework may further extract one or more vector parameters from the set of vectors, and determine one or more vector ratios based on the vector parameters to monitor changes in the patient signal data waveform.

Abstract: A method and system for autoregressive model based pigtail catheter motion prediction in a fluoroscopic image sequence is disclosed. Parameters of an autoregressive model are estimated based on observed pigtail catheter tip positions in a plurality of previous frames of a fluoroscopic image sequence. A pigtail catheter tip position in a current frame of the fluoroscopic image sequence is predicted using the fitted autoregressive model. The predicted pigtail catheter tip position can be used to constrain pigtail catheter tip detection in the current frame. The predicted pigtail catheter tip position may also be used to predict abnormal motion in the fluoroscopic image sequence.

Abstract: Disclosed herein is a framework for facilitating patient signal analysis based on vector analysis. In accordance with one aspect, a set of vectors is generated from a patient signal data waveform. The vectors may be directed from a common center to points of interest on the patient signal data waveform. The framework may further extract one or more vector parameters from the set of vectors, and determine one or more vector ratios based on the vector parameters to monitor changes in the patient signal data waveform.

Abstract: A wearable heart rate monitoring device includes an optical sensor configured to translate test light reflected from a wearer of the wearable heart rate monitoring device into a machine-readable heart rate signal. The wearable heart rate monitoring device also includes a motion sensor configured to translate motion of the wearable heart rate monitoring device into a machine-readable motion signal. The wearable heart rate monitoring device also includes a heart rate reporting machine, configured to determine a type of activity currently being performed by the wearer of the wearable heart rate monitoring device based at least in part on the machine-readable motion signal, and output an estimated heart rate based on at least the machine-readable heart rate signal and the type of activity.

Abstract: Methods and system are provided that identify motion data associated with consistent electrical and mechanical behavior for a region of interest of the heart. The methods and systems acquire electrical cardiac signals indicative of physiologic behavior of at least a portion of the heart over a plurality of cardiac cycles. The methods and systems acquires motion data indicative of mechanical behavior of a motion sensor over the plurality of cardiac cycles to form a motion data collection, the motion data indicative of mechanical behavior of the region of interest when the motion sensor is in contact with the region of interest. The designating ectopic beats within the cardiac cycles may be based on the electrical cardiac signals, the ectopic beats producing electrically inconsistent (EI) data within the motion data collection. The methods and systems identify mechanically inconsistent (MI) data within the motion data collection based on irregular changes in the motion data.

Abstract: Disclosed herein is a framework for facilitating patient signal analysis based on vector analysis. In accordance with one aspect, a set of vectors is generated from a patient signal data waveform. The vectors may be directed from a common center to points of interest on the patient signal data waveform. The framework may further extract one or more vector parameters from the set of vectors, and determine one or more vector ratios based on the vector parameters to monitor changes in the patient signal data waveform.

Abstract: A medical device and method for detecting a ventricular arrhythmia event is disclosed. The medical device includes input circuitry configured to receive an electrocardiogram (ECG) signal, processing circuitry coupled to the input circuitry and configured to identify at least one fiducial point of a first heartbeat signature and at least fiducial point of a second heartbeat signature of the ECG signal, and feature extraction circuitry coupled to the processing circuitry. The feature extraction circuitry is configured to determine at least one difference between the at least one fiducial point of the first heartbeat signal and the at least one fiducial point of the second heartbeat signal. Machine learning circuitry is coupled to the feature extraction circuitry and is configured to select a ventricular arrhythmia class based on the at least one difference.

Abstract: A patient monitoring system may generate an autocorrelation sequence for a physiological signal such as a photoplethysmograph signal. A series of peak values may be identified for the autocorrelation sequence. The peak values may be modified based on a historical distribution of a physiological parameter. A physiological parameter such as respiration rate may be determined based on the modified peak values.

Abstract: In one embodiment, ECG data collected during the long-term monitoring are compressed through a two-step compression algorithm executed by an electrocardiography monitor. Minimum amplitude signals may become indistinguishable from noise if overly inclusive encoding is employed in which voltage ranges are set too wide. The resulting ECG signal will appear “choppy” and uneven with an abrupt slope. The encoding used in the first stage of compression can be dynamically rescaled on-the-fly when the granularity of the encoding is too coarse. In a further embodiment, offloaded ECG signals are automatically gained as appropriate on a recording-by-recording basis to preserve the amplitude relationship between the signals. Raw decompressed ECG signals are filtered for noise content and any gaps in the signals are bridged. An appropriate signal gain is determined based on a statistical evaluation of peak-to-peak voltage (or other indicator) to land as many ECG waveforms within a desired range of display.

Abstract: A pericardial needle that punctures a pericardial membrane with cautery to attain access into a pericardial space of a heart by positioning a cautery needle tip adjacent to or in contact with a parietal pericardium of the heart such that the puncturing does not damage the heart muscle. The pericardial needle punctures the parietal pericardium when the heart muscle moves towards the pericardial needle, away from the pericardial needle, is at rest and/or is in synchronization with the systolic contraction period of the cardiac cycle of the heart. The synchronization may be provided based on a surface electrocardiogram, an arterial pressure, or a sensing pressure at the tip of the pericardial needle when the pericardial needle is adjacent into the parietal pericardium of the heart.

Abstract: A system and method for catheter placement using ECG is provided. In certain embodiments, the system and method can generate a patient specific window for tracking a characteristic of an ECG waveform, such as the amplitude of a P-wave. The patient specific window can be utilized in a system and method for assisting in the placement of a catheter within a patient. In other embodiments, a tip location algorithm can be used with an anti-thrombogenic catheter and an intravascular electrode assembly for maintaining a high resolution intravascular signal in an ECG based catheter tip placement system.

Abstract: One embodiment provides a garment for measuring biological information, a measurement system, a measurement device and a method of controlling thereof capable of measuring biological information with accuracy regardless of variations of each examinee. When an examinee wears a shirt, four limb electrodes are arranged at positions so that the electrodes cover the body surface other than around the clavicle. At that time, the four limb electrodes are assigned to positions so that they cover about the pelvis. Also, during the use of the shirt, chest electrodes cover from the body surface (around lower part of left side of the body) of a presternal region around the left thorax in a perpendicular direction of the body axis (a direction perpendicular to the length of the shirt) and the electrodes are assigned so as to cover from the body surface around the fourth rib to that around the sixth rib.

Abstract: The present invention provides an improved, Internet-based system that seamlessly collects cardiovascular data from a patient before, during, and after a procedure for EP or an ID. During an EP procedure, the system collects information describing the patient's response to PES and the ablation process, ECG waveforms and their various features, HR and other vital signs, HR variability, cardiac arrhythmias, patient demographics, and patient outcomes. Once these data are collected, the system stores them on an Internet-accessible computer system that can deploy a collection of user-selected and custom-developed algorithms. Before and after the procedure, the system also integrates with body-worn and/or programmers that interrogate implanted devices to collect similar data while the patient is either ambulatory, or in a clinic associated with the hospital. A data-collection/storage module, featuring database interface, stores physiological and procedural information measured from the patient.

Abstract: A pericardial needle that punctures a pericardial membrane to attain access into a pericardial space of a heart by advancing a sharp tip until the sharp tip is adjacent to or in contact with a parietal pericardium of the heart such that the puncturing does not damage the heart muscle. The pericardial needle punctures the parietal pericardium when the heart muscle moves towards the pericardial needle, away from the pericardial needle, is at rest and/or is in synchronization with the systolic contraction period of the cardiac cycle of the heart. The synchronization may be provided based on a surface electrocardiogram, an arterial pressure, or a sensing pressure at the tip of the pericardial needle when the pericardial needle is adjacent into the parietal pericardium of the heart.

Abstract: A system for detecting impending acute cardiac decompensation of a patient includes impedance circuitry, an activity sensor, and a processor system. The impedance circuitry measures a hydration signal of the patient, wherein the hydration signal corresponds to a tissue hydration of the patient. The activity sensor to measure an activity level of the patient, and the processor system includes a computer readable memory in communication with the impedance circuitry and the activity sensor, wherein the computer readable memory of the processor system embodies instructions to combine the hydration signal and the activity level of the patient to detect the impending acute cardiac decompensation.

Abstract: A biological signal measuring apparatus is provided. The biological signal measuring apparatus includes a receiving unit configured to receive a biological signal from each of unit measurers arrayed on a subject's skin, and configured to receive a noise signal that is a common component of electrical characteristics, and a noise filtering unit configured to filter noise from a first biological signal between first electrodes of a first unit measurer among the unit measurers, by using a second noise signal between second electrodes of a second unit measurer among the unit measurers. The biological signal corresponds to a difference between the electrical characteristics of electrodes of each of the unit measurers.

Abstract: A TWA measuring apparatus includes: a grouping section which is configured to group electrocardiogram waveforms of a subject in increments of a first beat number, to generate a plurality of first groups; a storage section which is configured to store the electrocardiogram waveforms; a testing section which is configured to test a statistical intergroup difference of measurement values of the electrocardiogram waveforms of the first groups; a heartbeat condition determining section which is configured to determine that a heartbeat condition is unstable, when a significant statistical difference exists between the first groups; and a TWA measuring section which is configured to measure variation in heartbeat by using the stored electrocardiogram waveforms, when it is determined that the heartbeat condition is unstable.

Abstract: A method and medical device for monitoring cardiac function in a patient that includes a plurality of electrodes to deliver cardiac pacing therapy, and a processor configured to determine a pacing threshold in response to initial delivery of the pacing therapy, determine whether there is a change in the pacing threshold during initial delivery of the pacing therapy, adjust a delivery parameter of the pacing therapy in response to determining the change in the pacing threshold during initial delivery of the pacing therapy, determine whether there is an increase in the pacing threshold during delivery of the adjusted pacing therapy, and determine hypokalemia in response to the increase in the pacing threshold during delivery of the adjusted pacing therapy being present.

Abstract: Systems and methods of detecting an impending cardiac decompensation of a patient measure at least two of an electrocardiogram signal of the patient, a hydration signal of the patient, a respiration signal of the patient or an activity signal of the patient. The at least two of the electrocardiogram signal, the hydration signal, the respiration signal or the activity signal are combined with an algorithm to detect the impending cardiac decompensation.

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: Various method embodiments of the present invention concern sensing patient-internal pressure measurements indicative of physiological exertion, identifying one or more steady state periods of physiological exertion based on the patient-internal pressure measurements, sensing extra-cardiac response data and cardiac response data corresponding to the one or more physiological exertion steady state periods, respectively comparing the extra-cardiac response data and the cardiac response data to extra-cardiac response information and cardiac response information associated with equivalent levels of physiological exertion intensity of the one or more steady state periods, and determining the likelihood that myocardial ischemia occurred during the one or more steady state periods based on the comparison of the extra-cardiac response data to the extra-cardiac response information and the cardiac response data to the cardiac response information.

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: Disclosed is a system for the detection of cardiac events that includes an implanted device called a cardiosaver, a physician's programmer and an external alarm system. The system is designed to provide early detection of cardiac events such as acute myocardial infarction or exercise induced myocardial ischemia caused by an increased heart rate or exertion. The system can also alert the patient with a less urgent alarm if a heart arrhythmia is detected. Using different algorithms, the cardiosaver can detect a change in the patient's electrogram that is indicative of a cardiac event within five minutes after it occurs and then automatically warn the patient that the event is occurring. To provide this warning, the system includes an internal alarm sub-system (internal alarm means) within the cardiosaver and/or an external alarm system (external alarm means) which are activated after the ST segment of the electrogram exceeds a preset threshold.

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: 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 estimates morphological features of heart beats from an ECG signal. Peaks of the R wave of the ECG are detected and classified using a parallel filtering structure. The first branch implements a bandpass filtering with cut off frequencies of about 10 Hz and 35 Hz, enhancing the signal-to-noise ratio (SNR) of the QRS complex. The second branch estimates morphological features of the heart beat from an alternating current (AC) replica of the ECG signal, that may be used to classify the beat and potentially detect arrhythmias.

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 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: 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: 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 medical device and associated method establish an occurrence of a premature atrial contraction. The device senses a ventricular signal. A control unit is configured to determine a metric of the ventricular signal during an interval following the premature atrial contraction and detect a change in cardiac stress tolerance in response to the determined metric.

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 sensing a cardiac signal over a plurality of cardiac cycles using a plurality of electrodes coupled to a sensing module, determining a template of a known cardiac signal in response to the cardiac signal sensed over the plurality of cardiac cycles, sensing an unknown cardiac signal over an unknown cardiac cycle, determining a fourth order difference signal corresponding to the template and a fourth order difference signal of the unknown cardiac signal, determining a first morphology match metric between the template fourth order difference signal and the fourth order difference signal of the unknown cardiac signal, and classifying the unknown cardiac signal in responsed to the determined first morphology match score.