Abstract: A method and system for mapping an anatomical structure includes sensing activation signals of intrinsic physiological activity with a plurality of mapping electrodes disposed in or near the anatomical structure, each of the plurality of mapping electrodes having an electrode location. A vector field map which represents a direction of propagation of the activation signals at each electrode location is generated to identify a signature pattern and a location in the vector field map according to at least one vector field template. A target location of the identified signature pattern is identified according to a corresponding electrode location.

Abstract: A computer-implemented method including, transmitting a high-spectrum energy wave towards a subject from a first sensor and transmitting a low-spectrum energy wave towards the subject from a second sensor. In response, modulation with a carrier sequence code results in a modulated evoked biological signal. The carrier sequence code has an autocorrelation function. The method includes demodulating the modulated evoked biological signal by calculating a convolution of the modulated evoked biological signal with the carrier sequence code resulting in an evoked biological signal spectrum. The evoked biological signal spectrum has a peak to sideband ratio as a function of the carrier sequence code. The method includes calculating deviations between each element of the sampled evoked biological signal and the peak to sideband ratio and filtering noise artifacts from the sampled evoked biological signal based on the deviations.

Abstract: A system for detecting an atrial tachyarrhythmia episode includes a medical device having sensing circuitry configured to receive a cardiac electrical signal from electrodes coupled to the medical device and a processor configured to detect an atrial tachyarrhythmia episode in response to a time duration of the cardiac electrical signal classified as an atrial tachyarrhythmia being greater than or equal to a first detection threshold. The processor is configured to determine if detection threshold adjustment criteria are met based on at least the detected first atrial tachyarrhythmia episode and adjust the first detection threshold to a second detection threshold different than the first detection threshold in response to the detection threshold adjustment criteria being met.

Abstract: Methods and devices for combining multiple signals from multiple sensing vectors for use in wearable or implantable cardiac devices. Signals from multiple vectors may be combined using weighting factors and/or by conversion to different coordinate systems than the original inputs, which may or may not be normalized to patient anatomy. Signals from multiple sensing vectors may be combined prior to or after several analytical steps or processes including before or after filtering, and before or after cardiac cycle detection. Cardiac cycle detection information may be combined across multiple sensing vectors before or after analysis of individual vectors for noise or overdetection. Cardiac cycle detection information may also be combined across multiple sensing vectors to identify noise and/or overdetection.

Abstract: A system including a sensor interface coupled to a processor. The sensor interface is configured to receive and process an analog electrocardiogram signal of a subject and provide a digitized electrocardiogram signal sampled over a first time period and a second time period that is subsequent to the first time period. The processor is configured to receive the digitized electrocardiogram signal, to analyze a frequency domain transform of the digitized electrocardiogram signal sampled over the first and second time periods and determine first and second metrics indicative of metabolic state of a myocardium of the subject during the first and second time periods, respectively, to compare the first and second metrics to determine whether the metabolic state of the myocardium of the subject is improving, and to indicate administration of an intervention to the subject in response to a determination that the metabolic state is not improving.

Abstract: A defibrillator and method for using a defibrillator which adopts an ECG analysis algorithm that can detect a cardiac arrhythmia in the presence of noise artifact induced by cardio pulmonary resuscitation (CPR) compressions. The apparatus and method offers guidance throughout a cardiac rescue protocol involving both defibrillation shocks and CPR that improves the effectiveness of the rescue, resulting in more CPR “hands-on” time, better treatment of refibrillation, and reduced transition times between CPR and electrotherapy.

Abstract: The present disclosure encompasses an “artifact score” derived from the signal characteristics of an acquired 12-lead ECG, (2) a “patient context score” derived from key elements of the patient's history, presentation, and prehospital emergency care, and (3) techniques for integrating these scores into an emergency medical care system.

Abstract: A method for assessing the electrical function of a heart, a method for determining a subject's need for the implantation of an implantable cardioverter defibrillator or the need for administration of an anti-arrhythmic agent, and apparatus for assessing the function of the heart and a computer program product. The methods and products involve analysis of ECG.

Abstract: There is described a technique using apparatus for recording and analyzing a surface electrocardiogram (ECG) for distinguishing a physiological signal from noise. The technique involves aligning and averaging multiple surface electrogram records taken for repeated pacing sequence with the same interval between pacing stimuli.

Abstract: A method and medical device for detecting a cardiac event that includes sensing a cardiac signal, determining RR-intervals in response to the sensed cardiac signal, detecting a cardiac event in response to the RR-intervals, iteratively sensing a predetermined number of P-waves in response to detecting the cardiac event, and confirming the cardiac event in response to the iteratively sensed P-waves.

Abstract: An apparatus for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

Abstract: Techniques for generating a user interface for monitoring biometric data. Embodiments generate a first portion of the user interface by plotting values of a first biometric parameter on a first graph structure with respect to a first interval of time and generate a second portion of the user interface by plotting values of a second biometric parameter on a second graph structure with respect to a second interval of time that overlaps with only a portion of the first interval of time. Upon receiving a user selection specifying a first position within the first graph structure, embodiments determine a third interval of time that is centered at a moment in time corresponding to the specified first position and update the second graph structure by plotting a third plurality of values of the second biometric parameter on the second graph structure, with respect to the third interval of time.

Abstract: A method and an apparatus for detecting cardiac arrhythmia and a recording medium using the method are provided. In the method, physiological signals of a human comprising a sequence of heart pulses are acquired, and an average of heartbeat intervals between pairs of consecutive heart pulses in the sequence of heart pulses is calculated. Each pair of consecutive heartbeat intervals is examined to identify premature ventricular contraction (PVC) candidates or atrial premature contraction (APC) candidates based on whether a difference between the pair of consecutive heartbeat intervals is larger than a product of a factor and the average of heartbeat intervals and whether an average of the pair of consecutive heartbeat intervals is within a predetermined range.

Abstract: Methods for storing data records associated with a medical monitoring event in a data structure. An implanted device obtains data and stores the data in the data record in a first data structure that is age-based. Before an oldest data record is lost, the oldest data record may be stored in a second data structure that is priority index-based. The priority index may be determined by a severity level and may be further determined by associated factors. The implanted device may organize, off-load, report, and/or display a plurality of data records based on an associated priority index. Additionally, the implanted device may select a subset or composite of physiologic channels from the available physiologic channels based on a selection criterion.

Abstract: A method and implantable medical device for determining a flutter event in response to a cardiac signal that includes sensing the cardiac signal, determining a sensing window in response to the sensed cardiac signal, the sensing window having a first portion and a second portion. A first derivative signal and a second derivative signal are determined in response to the sensed cardiac signal within the first portion and the second portion of the sensing window, and a sum of amplitudes of the second derivative signal within one or both of the first portion and the second portion of the sensing window is determined, and the flutter event is determined in response to the determined sum of amplitudes.

Abstract: Periodic electrical signal data, such as electrocardiogram signal data, is collected, analyzed, and transformed into compacted, multi-dimensional matrix that makes it easier for healthcare professionals to analyze the health condition of a patient. The electrical signal data, characterized by periodic deflection elements that collectively form a periodic signal complex, is analyzed to determine peaks of deflection elements, where peaks can vary greatly, but in ways not readily visible on standard electrocardiograms. The techniques create and display the multi-dimensional matrix from aligning identified peaks, so that the matrix can be readily overlayed with an automatically-identified signal pattern indicative of one or more of an arrhythmia, a precursor to an arrhythmia, a cardiac event, and/or a precursor to a cardiac even.

Abstract: A medical device such as an external defibrillator delivers electrical therapy using a special pulse sequence. The special pulse sequence includes a defibrillation shock that is automatically followed by a quick succession of automatic post-shock anti-tachycardia (APSAT) pacing pulses. Because of the pacing pulses, the defibrillation shock can be of lesser energy than an equivalent defibrillation shock of a larger energy. Accordingly, the external defibrillator can be made physically smaller and weigh less, without sacrificing the therapeutic effect of a larger external defibrillator that would deliver a defibrillation shock of higher energy. As such, the defibrillator is easier to configure for transporting, handling, and even wearing.

Abstract: A method can determine one or more origins of focal activation. The method can include computing phase for the electrical signals at a plurality of nodes distributed across a geometric surface based on the electrical data across time. The method can determine whether or not a given candidate node of the plurality of nodes is a focal point based on the analyzing the computed phase and magnitude of the given candidate node. A graphical map can be generated to visualize focal points detected on the geometric surface.

Abstract: An apparatus for determining information indicative of cardiac malfunctions includes a processing device (602) configured to detect whether the time-trend of a signal indicative of cardiovascular motion manifests an indicative phenomenon where the amplitude of a first heartbeat is greater than the amplitude of a second heartbeat and the temporary heartbeat rate is greater prior to the first heartbeat than prior to the second heartbeat. The processing device is further configured to produce an indicator of cardiac malfunction, e.g. an indicator of atrial fibrillation, in response to a situation in which the indicative phenomenon is detected to be present.

Abstract: A method and corresponding apparatus employ a time-varying spectral analysis approach for reconstructing an electrocardiogram (ECG) signal that includes motion artifacts. The motion artifacts are produced by motion of an ECG sensor relative to a sensing location. The time-varying spectral analysis based approach enables the ECG signal to be reconstructed with accuracy by suppressing the motion artifacts. Example applications for the method and corresponding apparatus include ECG-based heart rate monitoring in wearable devices for fitness tracking and health monitoring even during intense physical activities.

Abstract: Methods, systems, and devices for signal analysis in an implanted cardiac monitoring and treatment device such as an implantable cardioverter defibrillator. In some illustrative examples, detected events are analyzed to identify changes in detected event amplitudes. When detected event amplitudes are dissimilar from one another, a first set of detection parameters may be invoked, and, when detected event amplitudes are similar to one another, a second set of detection parameters may be invoked. Additional methods determine whether the calculated heart rate is “high” or “low,” and then may select a third set of detection parameters for use when the calculated heart rate is high.

Abstract: A system including a sensor interface coupled to a processor. The sensor interface is configured to receive and process an analog electrocardiogram signal of a subject and provide a digitized electrocardiogram signal sampled over a first time period and a second time period that is subsequent to the first time period. The processor is configured to receive the digitized electrocardiogram signal, to analyze a frequency domain transform of the digitized electrocardiogram signal sampled over the first and second time periods and determine first and second metrics indicative of metabolic state of a myocardium of the subject during the first and second time periods, respectively, to compare the first and second metrics to determine whether the metabolic state of the myocardium of the subject is improving, and to indicate administration of an intervention to the subject in response to a determination that the metabolic state is not improving.

Abstract: A system and method for mapping an anatomical structure includes sensing activation signals of physiological activity with a plurality of mapping electrodes disposed in or near the anatomical structure. Patterns among the sensed activation signals are identified based on a similarity measure generated between each unique pair of identified patterns which are classified into groups based on a correlation between the corresponding pairs of similarity measures. A characteristic representation is determined for each group of similarity measures and displayed as a summary plot of the characteristic representations.

Abstract: A method can include storing a plurality of data sets including values computed for each of a plurality of points for a given spatial region of tissue, the values in each of the data sets characterizing electrical information for each respective point of the plurality of points for a different time interval. The method can also include combining the values computed for each of a plurality of points in a first interval, corresponding to a first map, with the values for computed for each of the respective plurality of points in another interval and to normalize the combined values relative to a common scale. The method can also include generating a composite map for the given spatial region based on the combined values that are normalized.

Abstract: An apparatus (1) and method for detecting pulse-related parameters, such as pulse arrhythmia is presented. The apparatus (1) detects a series of pulses from a user, e.g. through a cuff-related measurement. Time differences, amplitude and pattern differences between multitudes of N pulses are determined. The apparatus investigates the degree of similarity of multiple pulse periods and/or pulse amplitudes and/or pulse pattern and subsequently generates a statistical set of similarity values based on a plurality of compared results. Basing on this, the apparatus generates a decision value based on the statistical sets of similarity values, and uses the decision value to determine whether or not the user discloses a normal pulse rhythm, atrial fibrillation, premature atrial or ventricular contractions, tachycardia, bradycardia and/or unspecified pulse arrhythmia. Further an artefact index is generated, informing the user whether a measurement was taken under sufficient artefact-free measurement conditions.

Abstract: An electrocardiogram (ECG) signal processing system is provided. The ECG signal processing system comprises an analog-to-digital converter (ADC) configured to convert an input analog ECG signal into a digital ECG signal, and a digital signal processing engine (DSPE) coupled to the ADC to receive the digital ECG signal. The DSPE is configured to decompose and reconstruct the digital ECG signal. A dynamic system clock source is coupled to the ADC and the DSPE for dynamic signal sampling, the dynamic system clock source clocking the ADC and the DSPE at a first frequency f1 to detect one or more first parameters of the input analog ECG signal and at a second frequency f2 to detect one or more second parameters of the input analog ECG signal.

Abstract: A method of automatically determining which type of treatment is most appropriate for a cardiac arrest victim, the method comprising transforming one or more time domain electrocardiogram (ECG) signals into a frequency domain representation comprising a plurality of discrete frequency bands, combining the discrete frequency bands into a plurality of analysis bands, wherein there are fewer analysis bands than discrete frequency bands, determining the content of the analysis bands, and determining the type of treatment based on the content of the analysis bands.

Abstract: A system for assessing a cardiac condition of a subject includes a sensor configured to record a plurality N of electrocardiographic signals from the subject to generate an ECG (electrocardiogram). The system further includes a processor configured to compute an RMS (root-mean-square) magnitude function from the recorded signals, and to measure from the RMS magnitude function an RMS variable that contains information about the cardiac condition of the subject. The ECG may be a standard 12-lead clinical ECG. The measured RMS variables may include RMS T-wave width, RMS RT recovery time, and RMS QT interval.

Abstract: Embodiments of the invention disclose a method and a system for signal analyzing and a processing module of the system. The signal analyzing system includes a plurality of first electrodes, a plurality of second electrodes, and a processing module. The first electrodes transmit a plurality of first input signals. The second electrodes transmit a plurality of second input signals. The processing module generates a body electrical signal according to at least one of the plurality of first input signals and at least one of the plurality of second input signals, generates a first filtered signal corresponding to the plurality of first input signals, generates a second filtered signal corresponding to the plurality of second input signals, and generates a lead signal according to the body electrical signal, the first filtered signal and the second filtered signal.

Abstract: Method of determining atrial fibrillation including determining if a patient's pulse beats form an irregular pattern and only if so, indicating the presence of an irregular pulse to the patient and obtaining an electrocardiogram for determining atrial fibrillation. Initially, a pulse is detected at regular time intervals of a first appendage of the patient when motionless using a pulse detector secured to the first appendage and pulse rhythms from a succession of time intervals are detected each corresponding to a respective interval of time between successive pulse beats of a sequence of the pulse beats. Then, an electrically conductive unit is attached to a second appendage of the patient, or a wearable electrocardiogram is attached to the patient, and electrocardiograms signals are detected simultaneously with pulse rhythms while the first appendage is motionless and analyzed to determine whether, in combination, they are indicative of atrial fibrillation.

Abstract: A method can determine one or more origins of focal activation. The method can include computing phase for the electrical signals at a plurality of nodes distributed across a geometric surface based on the electrical data across time. The method can determine whether or not a given candidate node of the plurality of nodes is a focal point based on the analyzing the computed phase and magnitude of the given candidate node. A graphical map can be generated to visualize focal points detected on the geometric surface.

Abstract: Medical devices and methods for making and using medical devices are disclosed. An example system for mapping the electrical activity of the heart includes a catheter shaft. The catheter shaft includes a plurality of electrodes including a first electrode and a second electrode. The system also includes a processor. The processor is capable of collecting a first signal corresponding to the first electrode and a second signal corresponding to the second electrode. Collecting the first and second signals occurs over a time period. The processor is also capable of generating a first time-frequency distribution corresponding to the first signal, identifying a first dominant frequency value occurring at a first dominant frequency and a first time point, generating a second time-frequency distribution corresponding to the second signal, identifying a second dominant frequency value occurring at a second dominant frequency and a second time point and determining an attraction point.

Abstract: Systems and methods are provided for predicting the onset of postoperative atrial fibrillation (AF) from electrocardiogram (ECG) data representing a patient. A signal processing component determines parameters representing the activity of the heart of the patient from the ECG data. A feature extraction component calculates a plurality of features useful in predicting postoperative AF from the determined parameters. A classification component determines an AF index for the patient from the calculated plurality of features. The AF index represents the likelihood that the patient will experience AF.

Abstract: An automated external defibrillator (AED) (10) having a treatment decision processor (28) is described which follows a “shock first” or a “CPR first” rescue protocol after identification of a treatable arrhythmia, depending upon an estimate of the probability of successful resuscitation made from an analysis of a patient parameter measured at the beginning of the rescue. The invention may also follow different CPR protocols depending on the estimate. The invention also may use the trend of the measured patient parameter to adjust the CPR protocol either during a CPR pause or after the initial CPR pause. The AED (10) thus enables an improved rescue protocol.

Abstract: In various method embodiments, a neural activity signal is sensed, a feature from the sensed neural activity signal is extracted, and a neural marker for the extracted feature is created. The neural marker includes information regarding the extracted feature. Various device embodiments comprise a port to receive a neural activity signal, and a feature extractor adapted to receive and process the neural activity signal to produce a neural marker that includes information for the neural activity signal. Various device embodiments comprise a display, a memory adapted to store a neural marker associated with a sensed neural activity signal, and a controller adapted to communicate with the memory and the display to provide a representation of the neural marker on the display.

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 can determine one or more origins of focal activation. The method can include computing phase for the electrical signals at a plurality of nodes distributed across a geometric surface based on the electrical data across time. The method can determine whether or not a given candidate node of the plurality of nodes is a focal point based on the analyzing the computed phase and magnitude of the given candidate node. A graphical map can be generated to visualize focal points detected on the geometric surface.

Abstract: A method and a system for determining changes in a body state of an individual including receiving a signal from a monitoring system, where the signal indicates a measurement of cardiac activity of the individual over a period of time and determining at least one signal feature, where the signal feature is a reoccurring event of the signal over the period of time. The method also includes determining a first interval between two successive signal features and determining a second interval between two successive first intervals. A derivative is calculated based on the second interval. Changes in the body state are identified based on the derivative.

Abstract: A method and medical device for detecting a cardiac event that includes sensing cardiac signals from a plurality of electrodes, the plurality of electrodes forming a first sensing vector sensing a first interval and a second sensing vector simultaneously sensing a second, determining, for each of the first interval and the second interval, whether each beat of the plurality of beats is one of a match beat and a non-match beat, determining whether each beat of the plurality of beats is one of a high confidence beat and a low confidence beat, determining, for each of the first interval and the second interval, the number of beats determined to be both a non-match beat and a high confidence beat is greater than a non-match threshold, and determining whether to deliver therapy for the cardiac event in response to identifying of each of the first interval and the second interval as being one of shockable and not shockable.

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: Real-time, short-term analysis of ECG, by using multiple signal processing and machine learning techniques, is used to determine counter shock success in defibrillation. Combinations of measures when used with machine learning algorithms readily predict successful resuscitation, guide therapy and predict complications. In terms of guiding resuscitation, they may serve as indicators and when to provide counter shocks and at what energy levels they should be provided as well as to serve as indicators of when certain drugs should be provided (in addition to their doses). For cardiac arrest, the system is meant to run in real time during all current resuscitation procedures including post-resuscitation care to detect deterioration for guiding care such as therapeutic hypothermia.

Abstract: A medical device includes a housing configured for implantation within a body of a patient, and detection circuitry disposed in the housing and coupled to an electrode arrangement. The detection circuitry is configured to sense cardiac signals from the patient. A processor is coupled to the detection circuitry. The processor is configured to compare the cardiac signals to an initial detection threshold, automatically generate an additional detection threshold in response to a predetermined number of the cardiac signals meeting or exceeding the initial detection threshold or a previously generated detection threshold, count each occurrence of a cardiac signal meeting or exceeding each of the respective detection thresholds, and record cardiac signal data only for a cardiac signal that meets or exceeds the highest of the detection thresholds.

Abstract: Methods for treating cardiac complex rhythm disorder in a patient can include receiving a plurality of electrical signals from a sensor system, wherein each electrical signal corresponds with a separate location on a cardiac wall of the heart of the patient, and wherein each electrical signal comprises an electrogram waveform; and ranking the electrical signals relative to each other based on at least a uniformity and a frequency of the electrogram waveform of each electrical signal.

Abstract: A method for the machine generation of a model for predicting patient outcome following the occurrence of an event. In one embodiment the method includes the steps of obtaining a physiological signal of interest, the physiological signal having a characteristic; obtaining a time series of a signal characteristic; dividing the time series into a plurality of window segments; converting the time series from time-space to beat-space; computing the power in various frequency bands of each window segment; computing the 90th percentile of the spectral energies across all window segments for each frequency band; and inputting the data into a machine learning program to generate a weighted risk vector.

Abstract: The system and method provide for electrocardiogram analysis and optimization of patient-customized cardiopulmonary resuscitation and therapy delivery. An external medical device includes a housing and a processor within the housing. The processor can be configured to receive an input signal for a patient receiving chest compressions and to select at least one filter mechanism and to apply the filter mechanism to the signal to at least substantially remove chest compression artifacts from the signal. A real time dynamic analysis of a cardiac rhythm is applied to adjust and integrate CPR prompting of a medical device. Real-time cardiac rhythm quality is facilitated using a rhythm assessment meter.

Abstract: A method and system for mapping an anatomical structure includes sensing activation signals of intrinsic physiological activity with a plurality of mapping electrodes disposed in or near the anatomical structure. The activation signals are used to determine a dominant frequency for each electrode from which a wavefront vector for each electrode is determined based on a difference between the dominant frequency at a first electrode location and the dominant frequency at neighboring electrodes. An anatomical map is generated based on the determined wavefront vectors.

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: An apparatus comprises a primary cardiac signal sensing circuit to sense a first cardiac signal, a secondary cardiac signal sensing to sense a second cardiac signal, and an arrhythmia detection circuit. The primary sensing circuit includes at least first and second implantable electrodes, and the secondary sensing circuit includes a third implantable electrode to deliver high-energy shock therapy. The arrhythmia detection circuit detects tachyarrhythmia using the primary sensing circuit, determines correspondence between events sensed with the primary sensing circuit and events sensed with the secondary sensing circuit, and deems whether a detected rhythm is indicative of noise or is indicative of an arrhythmia according to the determined correspondence.

Abstract: A method for correlating information across distinct domains without requiring feature co-occurrence. The disparate information collections are broken down into features, and a correlation index with correlation score is created. To determine the correlation between distinct domains, an information artifact collection is reduced to a representational set of features, these features are replaced with correlated features using the correlation index, and the new set of features is matched against the second information artifact collection using an appropriate comparison technique. The correlation method allows a single input artifact to be matched against an existing collection, resulting in a set of correlated artifacts from the disparate collection, each ranked by correlation score.

Abstract: A magnetocardiogram (MCG) system with reduced noise artifacts is produced by first creating high-resolution image representations of low-resolution measurements obtained with a magnetic field sensor unit. The high-resolution image representations are created by use of a PCA model that has been trained using a library of ideal, no-noise, high-resolution images. The Biot-Sarvart Law is then used to create a 3D model of a current impulse, given the high-resolution image representations. From the 3D current impulse model, ideal sensor unit measurements as they would have been obtained using a theoretical sensor unit observing the 3D current impulse model are synthesized.