Cardiac Graphic Display System

Abstract

A method and system for displaying electromagnetic ("EM") source graphical information relating to the source and source location of patterns (abnormal or normal) of electrical activity of EM sources within the body is provided. A system for displaying cardiac graphic information regarding the origin and source location of cardiac disease to aid in the evaluation of cardiac disease is provided. The cardiac graphic display system provides an intracardiogram similarity ("ICS") graphic and a source location ("SL") graphic. The ICS graphic includes a grid with x- and y-axes representing patient cycles of a patient electrocardiogram, with intersections of patient cycle identifiers indicating similarities between patient cycles. The SL graphic provides a representation of the heart with source locations indicated. Source locations are identified based on similarities of patient cycles to library cycles of a library electrocardiogram of an electrocardiogram.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This international application is a continuation-in-part of U.S. patent application Ser. No. 16 / 710,286, entitled “HEART GRAPHIC DISPLAY SYSTEM,” filed on December 11, 2019 (Attorney Docket No. 129292-8018.US02), which is a continuation-in-part of U.S. patent application Ser. No. 16 / 436,460, entitled “HEART GRAPHIC DISPLAY SYSTEM,” filed on June 10, 2019 (Attorney Docket No. 129292-8018.US00), which is related to the following applications: U.S. Provisional Patent Application No. 62 / 663,049, filed on April 26, 2018, entitled “MACHINE LEARNING USING SIMULATED CARDIOGRAMS” (Attorney Docket No. 129292-8002.US00); U.S. Provisional Patent Application No. 62 / 760,561, filed on November 13, 2018, entitled “RECORD ABLATION PROCEDURE RESULTS IN A DISTRIBUTED LEDGER” (Attorney Docket No. 129292-8014.US00); U.S. Provisional Patent Application No. 62 / 760,561, filed on July 23, 2018, entitled “GENERATING SIMULATED ANATOMIES OF AN ELECTROMAGNETIC SOURCE” (Attorney Docket No. 129292-8020.US00); No. 16 / 042,984, filed on July 23, 2018, entitled “GENERATING A MODEL LIBRARY OF MODELS OF AN ELECTROMAGNETIC SOURCE” (Attorney Docket No. 129292-8003.US00); U.S. patent application Ser. No. 16 / 042,953, filed on July 23, 2018, entitled “GENERATING A MODEL LIBRARY OF MODELS OF AN ELECTROMAGNETIC SOURCE” (Attorney Docket No. 129292-8004.US01);No. 16 / 042,973, filed on July 23, 2018, entitled “USER INTERFACE FOR PRESENTING SIMULATED ANATOMIES OF AN ELECTROMAGNETIC SOURCE” (Attorney Docket No. 129292-8005.US00); U.S. Patent Application No. 16 / 042,993, filed on July 23, 2018, entitled “CONVERTING A POLYHEDRAL MESH REPRESENTING AN ELECTROMAGNETIC SOURCE” (Attorney Docket No. 129292-8006.US00); U.S. Patent Application No. 16 / 042,993, filed on July 23, 2018, entitled “GENERATING APPROXIMATIONS OF CARDIOGRAMS FROM DIFFERENT SOURCE CONFIGURATIONS” (Attorney Docket No. 129292-8006.US00); No. 16 / 043,011, filed on July 23, 2018, entitled “BOOTSTRAPPING A SIMULATION-BASED ELECTROMAGNETIC OUTPUT OF A DIFFERENT SOURCE CONFIGURATIONS” (Attorney Docket No. 129292-8007.US00); U.S. patent application Ser. No. 16 / 043,022, filed on July 23, 2018, entitled “BOOTSTRAPPING A SIMULATION-BASED ELECTROMAGNETIC OUTPUT OF A DIFFERENT ANATOMY” (Attorney Docket No. 129292-8008.US00); U.S. patent application Ser. No. 16 / 043,022, filed on July 23, 2018, entitled “IDENTIFYING AN ATTRIBUTE OF AN ELECTROMAGNETIC SOURCE CONFIGURATION BY MATCHING SIMULATED AND PATIENT DATA” (Attorney Docket No. 129292-8008.US00); No. 16 / 043,034 (Attorney Docket No. 129292-8009), entitled "METHOD FOR USE IN METHODS OF TRANSMITTING DATA" (ATTORNEY DOCKET NO. 129292-8009).No. 16 / 043,041, entitled “MACHINE LEARNING USING CLINICAL AND SIMULATED DATA,” filed on July 23, 2018 (Attorney Docket No. 129292-8010.US00); U.S. Patent Application No. 16 / 043,050, entitled “DISPLAY OF AN ELECTROMAGNETIC SOURCE BASED ON A PATIENT-SPECIFIC MODEL,” filed on July 23, 2018 (Attorney Docket No. 129292-8011.US00); U.S. Patent Application No. 16 / 043,050, entitled “DISPLAY OF AN ELECTRICAL FORCE GENERATED BY AN ELECTRICAL SOURCE WITHIN A PATIENT,” filed on July 23, 2018 (Attorney Docket No. 129292-8012.US00); No. 16 / 043,054, entitled "MACHINE LEARNING USING SIMULATED CARDIOGRAMS," filed on October 17, 2018 (Attorney Docket No. 129292-8002.US01); U.S. patent application Ser. No. 16 / 206,005, entitled "CALIBRATION OF SIMULATED CARDIOGRAMS," filed on November 30, 2018 (Attorney Docket No. 129292-8015.US00); U.S. patent application Ser. No. 16 / 206,005, entitled "IDENTIFY ABLATION PATTERN FOR USE IN AN ABLATION BODY," filed on January 14, 2019 (Attorney Docket No. 129292-8016.US01); No. 16 / 247,463 (Attorney Docket No. 129292-8016.US), entitled "ABLATION," each of which is incorporated herein by reference in its entirety. [Background technology]

[0002] Many cardiac disorders can cause symptoms, morbidity (syncope or stroke), and mortality. Common cardiac disorders with arrhythmia causes include inappropriate sinus tachycardia ("IST"), ectopic atrial rhythm, junctional rhythm, ventricular escape rhythm, atrial fibrillation ("AF"), ventricular fibrillation ("VF"), focal atrial tachycardia ("focal AT"), atrial micro-reentry, ventricular tachycardia ("VT"), atrial flutter ("AFL"), premature ventricular contractions ("PVC"), premature atrial contractions ("PAC"), atrioventricular nodal reentrant tachycardia ("AVNRT"), atrioventricular reentrant tachycardia ("AVRT"), persistent junctional returning tachycardia (PJRT), and junctional tachycardia ("JT"). The sources of arrhythmias can include electrical rotors (e.g., ventricular fibrillation), recurring electrical focal sources (e.g., atrial tachycardia), and anatomically-based reentry (e.g., ventricular tachycardia). These sources are important contributors to persistent or clinically significant pathology. Arrhythmias can be treated by ablation using different techniques, including radiofrequency energy ablation, cryoablation, ultrasound ablation, laser ablation, external sources, and targeted gene therapy, by targeting the source of cardiac disease. Because the source and location of the source of cardiac disease vary from patient to patient, targeted therapy requires identification of the source of arrhythmias, even for common cardiac diseases. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] U.S. Patent Application Serial No. 16 / 206,005 [Patent Document 2] U.S. Patent Application Serial No. 16 / 247,463 [Non-patent literature]

[0004] [Non-Patent Document 1] Krummen, D, et al., "Rotor Stability Separates Sustained Ventricular Fibrillation From Self-Terminating Episodes in Humans," Journal of the American College of Cardiology, Vol. 63, No. 23, 2014 [Non-Patent Document 2] Pan, J., Tompkins, W. J., "A Real-Time QRS Detection Algorithm," IEEE Reports on Biomedical Engineering (3):230 (1985) Summary of the Invention [Problem to be solved by the invention]

[0005] However, current methods of reliably identifying the source and source location of cardiac disease can be complex, cumbersome, and expensive. For example, one method uses an electrophysiology catheter with a multi-electrode basket catheter that is intravascularly inserted into the heart (e.g., the left ventricle) to collect from within the heart measurements of the heart's electrical activity, such as during an episode of induced VF. The measurements can then be analyzed to help identify possible source locations. Currently, electrophysiology catheters are expensive (and typically limited to one-time use) and can lead to serious complications, including cardiac perforation and cardiac tamponade. Another method uses an external body surface vest containing electrodes to collect measurements from the patient's body surface that can be analyzed to help identify arrhythmia source locations. Such body surface vests are expensive, complex and difficult to manufacture, and can interfere with the placement of defibrillation pads that are required after inducing VF and collecting measurements during the arrhythmia. Additionally, vest analysis requires a computed tomography ("CT") scan and cannot sense the ventricular and atrial septums, where approximately 20% of arrhythmia sources may originate. [Brief description of the drawings]

[0006] [Figure 1] FIG. 2 illustrates an ICS graphic in some embodiments. [Diagram 2] FIG. 1 illustrates a SL graphic in some embodiments. [Diagram 3] FIG. 1 is a block diagram illustrating components of an HTG system in some embodiments. [Figure 4] FIG. 1 is a flow diagram illustrating an ICS affinity map generation process in some embodiments. [Diagram 5] FIG. 11 is a flow diagram that illustrates the processing of the calculate similarity score component of the HGD system in some embodiments. [Figure 6] FIG. 11 is a flow diagram that illustrates the processing of the cycle identification component of the HGD system in some embodiments. [Figure 7] FIG. 2 is a block diagram illustrating the processing of the cycle normalization component of the HGD system in some embodiments. [Figure 8] FIG. 11 is a flow diagram that illustrates the processing of the extract segments component of the HGD system in some embodiments. [Figure 9] FIG. 1 is a flow diagram illustrating a source location graphic generation process for the HGD system in some embodiments. [Figure 10] FIG. 11 is a flow diagram that illustrates the processing of the calculate library similarity score component of HGD in some embodiments. [Figure 11] FIG. 13 is a flow diagram that illustrates the processing of the generate source location indicator component of the HGD system in some embodiments. [Figure 12] FIG. 11 is a flow diagram that illustrates the processing of the set pixel color component of the HGD system in some embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] A method and system are provided for displaying electromagnetic ("EM") source graphic information relating to the source and source location of patterns (abnormal or normal) of electrical activity of EM sources within a body. The body may be, for example, a human body, and the EM source may be the heart, brain, liver, lungs, kidneys, stomach, or another body part that generates an EM field, preferably measurable from outside the body and represented by EM measurements such as an electrocardiogram ("ECG") or electroencephalogram ("VCG") and an electroencephalogram ("EEG"). The EM graphic display system is described below primarily in the context of the EM source being the heart. The EM graphic system method and system described below for the heart can also be adapted to provide graphics of other EM sources of the body. For example, the identification of ECG cycles described below can also be adapted to identify cycles of EEG or cycles of EM measurements that represent the EM fields of the stomach. The graphics provide a visual indication that can be textual or non-textual (e.g., figures, animations, and computer-generated renderings).

[0008] In some embodiments, a method and system are provided for displaying cardiac graphic information related to the origin and origin location of cardiac disease to aid in the assessment of cardiac disease. In some embodiments, a cardiac graphic display ("HGD") system provides an intracardiogram similarity ("ICS") graphic and a origin location ("SL") graphic. The ICS graphic provides information regarding the similarity between cycles of an electrocardiogram (e.g., of a patient). FIG. 1 shows an example ICS graphic in some embodiments. The ICS graphic 100 includes a similarity map 110 that provides visual information regarding the similarity between pairs of patient cycles of a patient electrocardiogram of a patient. The x-axis and y-axis represent patient cycles (e.g., beats), and the intersection of a first patient cycle with a second patient cycle represents the similarity between the first patient cycle and the second patient cycle. The color of the area at the intersection of the patient cycles on the x-axis with the patient cycles on the y-axis represents a similarity score (e.g., based on Pearson's correlation coefficient or cosine similarity) indicating the similarity between these patient cycles. The similarity score can range from 0 to 1, with 1 being the similarity score for the same patient cycle. The ICS graphic legend 114 shows a range of colors representing similarity scores, with red representing the lowest similarity score and blue representing the highest similarity score. (Similarity scores can be represented by similarity indicators based on graphic characteristics other than color, such as using grayscale and polyhedra ranging from triangles to circles.) As an example, the intersection 111 of cycle 35 and cycle 22 is blue indicating a relatively high similarity between these patient cycles. The intersection 112 of cycle 35 and cycle 20 is red indicating a relatively low similarity between these patient cycles. The intersections along the diagonal are dark blue, representing the similarity of each patient cycle with itself, and thus a similarity score of 1. The similarity map can be thought of as corresponding to a symmetric matrix. A popup 113 identifies the x-axis and y-axis cycles of the intersection as the pointer hovers over the intersection, and the similarity scores of these cycles as the z-axis value.When the pointer selects a window or range of beats, a popup may also display in a window a statistical summary of the similarity scores, such as the similarity score mean and standard deviation, the number of significantly different similar cycle groups, a stability index, or an arrhythmia type classification. This ICS graphic may also be generated based on a library cycle from a library of ECGs (described below).

[0009] The source stability index (or stability feature) is a measure of cycle-to-cycle consistency of dominant arrhythmia sources localized to a particular region in the heart. The stability index can be based on the similarity scores of a series of consecutive cycles and can be represented by the standard deviation of all similarity scores above or below the identity diagonal of the ICS graphic within a user-defined time interval. A high mean and low standard deviation indicate a stable arrhythmia (e.g., focal tachycardia), whereas a low mean and high standard deviation indicate an unstable arrhythmia (e.g., rotor fibrillation). This measure can be a count of the number of off-diagonal clusters with high similarity to estimate the number of unique arrhythmia activation patterns and thus sources. Techniques for determining the stability of an arrhythmia source are described in Krummen, D., et al., "Rotor Stability Separates Sustained Ventricular Fibrillation From Self-Terminating Episodes in Humans," Journal of the American College of Cardiology, Vol. 63, No. 23, 2014, which is incorporated herein by reference.

[0010] ICS graphics are useful in identifying characteristic electrical activation dynamics that help to eliminate the driving mechanism of clinical arrhythmias. The persistence of similar patient cycles can indicate an effective target source stability index or arrhythmia type classification. Such similar patient cycles can indicate consistent periodic electrical activation dynamics in the heart. Electrical activation dynamics (i.e., how action potentials propagate through cardiac tissue) are influenced by many factors, including electrical properties of cardiac tissue, source location, source type (e.g., rotor or focal, fibrillation, tachycardia, flutter, etc.), and disease substrate (e.g., scar). Considering these factors, similarities between patient cycles do not necessarily indicate a rotor-based arrhythmia source, but can more generally indicate which electrical activation pattern in the electrocardiogram is more or less dominant or prevalent. Dominant electrical activation dynamics frequently seen in the electrocardiogram indicate the driving and sustaining mechanism of the arrhythmia.

[0011] Analysis of the ICS graphic can show multiple drivers as multiple groups of similar patient cycles. When multiple groups occur in a time-continuous sequence (groups of consecutive high similarity scores near the diagonal of identity of the similarity map), the analysis can suggest a transition in electrical activation dynamics from one group to the next. This transition can be due to a shift in source location or a change from one arrhythmia type to another (e.g., rotor-based VF can transition to local source VT). For example, with reference to FIG. 1, the intersection of x-axis cycles 22-29 with y-axis cycles 22-29 represents a group of similar patient cycles, and the intersection of x-axis cycles 33-40 with y-axis cycles 33-40 represents another group of similar cycles. The intersection of x-axis cycles 22-29 with y-axis cycles 33-40 indicates the similarity of these groups, also referred to as off-diagonal clusters. It is possible to have multiple distant arrhythmia sources or arrhythmia types within the heart that do not represent the movement of a single driver. In cases where multiple groups of similar patient cycles do not occur in the time-continuous sequence and the source locations estimated from the localization analysis are far apart, there may be indications of multiple driving mechanisms. For example, the group represented by x-axis cycles 22-29 and y-axis cycles 22-29, and the group represented by x-axis cycles 49-56 and y-axis cycles 49-56 are not present in the time-continuous sequence. In other cases, groups not present in the time-continuous sequence may be found to have the same arrhythmia pattern, thus suggesting a common driving mechanism. Such common driving mechanisms may be indicated by groups of high similarity on the off-diagonal portion of the similarity map. For example, the group represented by x-axis cycles 22-29 and y-axis cycles 49-56 shows similarity to the group represented by x-axis cycles 22-29 and y-axis cycles 22-29 and the group represented by x-axis cycles 49-56 and y-axis cycles 49-56, which are not present in the time-continuous sequence. When similarity between groups of similar cycles that are not present within a time-continuous sequence is low, the analysis can suggest multiple independent driving mechanisms.

[0012] In some embodiments, the ICS system can be used to display information indicative of inter-heart similarity (as opposed to intra-heart similarity) between cycles derived from electrocardiograms representing different hearts or the same heart at different times. For example, the ICS system can generate a similarity score for pairs of patient cycles and simulated cycles. The simulated cycles can be identified from simulated electrocardiograms derived from simulated EM measurements generated for simulated EM activations of the heart. The simulated EM activations can be generated using a computational model of the heart. The simulated electrocardiograms can be stored in a library of electrocardiograms. The ICS system generates a graphic indicative of the similarity score between such cycle pairs. This graphic can be similar to the graphic generated for intra-heart similarity. As another example, the ICS system can generate a similarity score indicative of inter-heart similarity based on different simulated electrocardiograms and different patient electrocardiograms. The different patient electrocardiograms can include patient electrocardiograms of the same patient or patient electrocardiograms of different patients collected at different times. The ICS system can generate a similarity score for the electrocardiogram pairs based on the inter-heart similarity. For example, if a similarity score between a patient electrocardiogram and a simulated electrocardiogram is to be generated, the simulated electrocardiogram can be selected based on cardiac similarity between the patient heart and the simulated heart used in generating the simulated electrocardiogram. The cardiac similarity can be based on physical characteristics (e.g., orientation, size and shape) and / or EM characteristics of the patient heart and the simulated heart. Similarly, patient electrocardiograms of different patients can also be selected based on cardiac similarity between the patient heart and the patient heart of the other patient, and the simulated electrocardiogram can be selected based on cardiac similarity between the two simulated hearts. Techniques for identifying cardiac similarity between a patient heart and a simulated heart are described in U.S. Application Serial No. 16 / 206,005, filed November 30, 2018, and entitled "CALIBRATION OF SIMULATED CARDIOGRAMS."

[0013] The SL graphic provides information about source locations identified by comparing patient cycles of a patient electrocardiogram to library cycles of an electrocardiogram library. Each library cycle is associated with a source location and a source type. FIG. 2 illustrates an example SL graphic in some embodiments. The SL graphic 200 includes a representation 210 of a heart (e.g., a ventricle) and source location indicators 221-224 derived from one or more patient cycles. To identify source locations or source types to be included in the SL graphic, the HGD system calculates a similarity score indicating the similarity between the library cycles and the patient cycles of the patient electrocardiogram of the patient. The HGD system then identifies several (i.e., one or more) source locations associated with the library cycles (referred to as target library cycles) based on the similarity scores. For example, the HGD system may identify source locations based on the highest similarity score of the library cycles associated with each source location, an average of the highest four similarity scores of the library cycles associated with each source location, and so on. The source locations associated with the library cycles having the highest similarity scores are likely to yield more information in aiding in the evaluation of cardiac disease. The HGD system then generates a SL graphic that includes a representation of a portion of the heart and a source location indicator and a source type indicator for each source location and source type of the target library cycle.

[0014] In some embodiments, the source location indicator and the source type indicator may have characteristics that vary based on the similarity scores associated with the source location indicator and the source type indicator. The source location indicator and the source type indicator may be centered on the source location. The source location indicator may be a circle with characteristics such as a size of the circle and a color of the circle. The size of the circle may be based on the similarity score associated with the target library cycle. A small size (i.e., radius) of the circle centered on the source location may indicate that the target library cycle associated with that source location and source type has a high similarity score. (The source location and source type associated with the target library cycle are considered to be relevant to the similarity score of the target library cycle.) A small size may indicate a high confidence in the relevance of the source location. The HGD system may assign a color to each source location indicator and source type indicator that indicates the relative ordering of the source location's similarity scores. For example, assuming four source location indicators are displayed, the source location indicator associated with the highest similarity score may be assigned the color red, and the remaining three source location indicators may be assigned the colors yellow, green, and blue in descending order of their associated similarity scores. The HGD system may set the center of the circle to the color assigned to the source location indicator, and the color assigned to the remainder of the circle may vary linearly from the color assigned to the center to the color indicating the lowest similarity score around the circumference of the circle. For example, the coloring of the circle may vary from red to blue, yellow to blue, green to blue, and solid blue. The source location indicators may be shapes other than circles, and may be based on a grayscale rather than a range of colors. The source location indicators may be selected from a list 230 of source location indicators. Each item in the list of source location indicators may be labeled with a cycle / beat number, cycle start and end times, similarity statistics, or a description of the source type.

[0015] In some embodiments, the HGD system can include source locations derived from multiple patient cycles in the SL graphic. For example, the HDG system can identify source locations for multiple patient cycles and include source location indicators for multiple patient cycles simultaneously on the SL graphic. Alternatively, the HDG system can generate a source location indicator for each patient cycle and output the source location indicators in sequence as they move through the patient cycle to present an animation of the source locations. When the SL graphic includes source locations for multiple patient cycles simultaneously, some of the source location indicators may overlap. In such a case, the HDG system can set a pixel in the overlapping portion to an average of the color of that pixel from the overlapping source location indicators. For example, if the color of a pixel is yellow in one source location indicator and blue in the other source location indicator, the color of the pixel in the LS graphic can be green. The cycle selection box 230 in FIG. 2 allows a user to select one or more patient cycles to be used to identify the source locations of the SL graphic.

[0016] In some embodiments, the HGD system can identify source locations for multiple patient cycles by generating an average of the similarity scores associated with each patient cycle for each source location. The HGD system then identifies source locations based on the average similarity scores. The color and size assigned to the source location indicator is based on the average similarity scores of the source locations.

[0017] 3 is a block diagram illustrating components of a HGD system in some embodiments. The HGD system 300 includes components for generating an ICS graphic, including an ICS graphic generation component 310, a similarity score calculation component 311, a cycle identification component 312, a cycle normalization component 313, and a cycle extraction component 314. The ICS graphic generation component generates an ICS graphic of a patient electrocardiogram by invoking a similarity score calculation component to calculate a similarity score for a patient cycle pair of a patient electrocardiogram, generating an ICS graphic based on the similarity score, and outputting the ICS graphic. The similarity score calculation component invokes a patient cycle identification component to identify patient cycles in the patient electrocardiogram, invokes a segment extraction component to extract relevant segments from the patient cycles and discard non-useful patient cycles, and then computes a similarity score for each patient cycle pair. The cycle identification component identifies the patient cycles and invokes a cycle normalization component to normalize the patient cycles.

[0018] The HGD system also includes components for generating an SL graphic, including an SL graphic generation component 320, a library similarity score calculation component 321, a source location indicator generation component 322, and a pixel color setting component 323. The SL graphic generation component invokes a library similarity score calculation component to calculate a similarity score for each pair of patient cycle and library cycle, invokes a source library indicator generation component to generate a source library indicator for each patient cycle, receives a selection of a patient cycle, invokes a pixel color setting component to fill the SL graphic based on the SL indicator associated with the received patient cycle, and then outputs the SL graphic. The library similarity score calculation component calculates a similarity score for each pair of patient cycle and library cycle, and sorts the source locations for each patient cycle based on the similarity score associated with the library cycle associated with the source location. The source location indicator generation component generates a source location indicator for each patient cycle, such as the source location associated with the highest similarity score for each source location or a subset of source locations. The pixel color setting component calculates pixel values ​​for overlapping areas of the source location indicators.

[0019] The patient electrocardiogram data store 340 includes patient electrocardiograms, such as electrocardiograms ("ECGs") or vectorcardiograms ("VCGs"). The electrocardiogram library 350 includes library cycles of library electrocardiograms. The library electrocardiograms can be simulated electrocardiograms and / or groups of patient electrocardiograms generated based on a computational model of the heart. The library cycles are identified similarly to identifying patient cycles. Each library cycle is associated with a corresponding source location or source type. The electrocardiogram library can be generated using techniques described in U.S. Patent Application No. 16,206,005, filed November 30, 2018, entitled "Calibration of Simulated Cardiograms," which is incorporated herein by reference.

[0020] A computer system (e.g., a network node or a group of network nodes) on which the HGD system and other described systems can be implemented can include a central processing unit, input devices, output devices (e.g., display devices and speakers), storage devices (e.g., memory and disk drives), network interfaces, graphic processing units, cellular radio link interfaces, and global positioning system devices, etc. Input devices can include keyboards, pointing devices, touch screens, gesture recognition devices (e.g., for air gestures), head and eye tracking devices, microphones for voice recognition, etc. Computer systems can include high performance computer systems, cloud-based servers, desktop computers, laptops, tablets, electronic readers, personal digital assistants, smartphones, gaming devices and servers, etc. For example, simulations and training can be performed using high performance computer systems, and classification can be performed by tablets. Computer systems can access computer readable media, including computer readable storage media and data transmission media. A computer readable storage medium is a tangible storage means that does not include a transitory propagating signal. Examples of computer-readable storage media include memory, such as primary memory, cache memory, secondary memory (e.g., DVD), and other storage. The computer-readable storage media may have recorded thereon or be encoded with computer-executable instructions or logic for executing the HGD system and other described systems. The data transmission media is used to transmit data via ephemeral propagating signals or carrier waves (e.g., electromagnetic forces) over wired or wireless connections. The computer system may include a secure cryptographic processor as part of the central processing unit that generates and securely stores keys and uses these keys to encrypt and decrypt data.

[0021] The HGD system and other described systems may be described in the general context of computer-executable instructions, such as program modules and components, executed by one or more computers, processors or other devices. Generally, program modules or components include routines, programs, objects, data structures, etc. that perform the tasks or implement data types of the HGD system and other described systems. Typically, the functionality of the program modules may be combined or distributed as desired in various examples. Aspects of the HGD system and other described systems may be implemented in hardware using, for example, application specific integrated circuits ("ASICs") or field programmable gate arrays ("FPGAs").

[0022] The components of the HGD system can be implemented using a client-server model. For example, a client system can help receive requests from a user for cardiac information, send the requests to a server, and receive an indication of a similarity score from the server. The client can then display graphics that can be generated by the user or generated by and received from the server based on the received indication of the similarity score. The server can be hosted in a data center (e.g., a cloud-based data center).

[0023] FIG. 4 is a flow diagram illustrating an ICS similarity map generation process in some embodiments. The ICS similarity map generation component generates a similarity map for an ICS graphic based on similarity between atrial or ventricular segments of patient cycles of a patient electrocardiogram ("CG"). The component calls the calculate similarity score component in block 401 to calculate a similarity score between patient cycles. The component adds labels or identifiers of the patient cycles to the x-axis and y-axis in block 402. In the similarity map 110 of FIG. 1, due to space limitations, labels such as "beat 1" and "beat 3" identify every other patient cycle, but not every cycle. The component selects the next patient cycle ("PC") pair in block 403. In decision block 404, if all patient cycles have already been selected, the component proceeds to block 407, otherwise the component proceeds to block 405. In block 405, the component selects a color based on the similarity score of the patient cycle pair. The component fills the intersections of the patient cycle pairs in block 406. For example, for pair patient cycle 22 and patient cycle 35, the component sets the intersections of (35,22) and (22,35) to the color blue to indicate a relatively high similarity score for these patient cycles. The component then loops to block 403 to select the next patient cycle pair. The component may add a color range legend to the ICS graphic in block 407 before outputting the ICS graphic. The component then terminates.

[0024] The similarity map can also be displayed as a three-dimensional graph with similarity scores on the z-axis, in which case the HGD system can rotate the three-dimensional graph to allow the graph to be viewed at different angles around the x-, y-, and z-axes.

[0025] FIG. 5 is a flow diagram illustrating the processing of the calculate similarity score component of the HGD system in some embodiments. The calculate similarity score component 500 is called to calculate a similarity score between patient cycles of a patient electrocardiogram. The component calls the identify cycle component in block 501 to identify patient cycles in the patient electrocardiogram. The component loops in blocks 502-506 to identify segments of the patient cycle and discards patient cycles that do not meet a usefulness criterion. Patient cycles may be unuseful based on various criteria such as being too short and / or too long. For example, the criterion may be that the patient cycle is longer than 500 ms and shorter than 1000 ms. The component selects the next patient cycle in block 502. In decision block 503, the component proceeds to block 507 if all patient cycles have already been selected, otherwise the component proceeds to block 504. In block 504, the component calls the extract segments component to extract the relevant patient cycle segments. If, in decision block 505, the extract segments component indicates the patient cycle is not useful, the component continues at block 506; otherwise, the component loops to block 502 to select the next patient cycle. The component discards the patient cycle in block 506 and loops to block 502 to select the next patient cycle. The component loops in blocks 507-509 to calculate similarity scores between the patient cycle pair. The component selects the next patient cycle pair in block 507. In decision block 508, the component ends if all patient cycles have already been selected; otherwise, the component continues at block 509. In block 509, the component calculates similarity scores for the patient cycle pair and then loops to block 507 to select the next patient cycle pair.

[0026] In some embodiments, the HGD system can identify cycles (periodic intervals of arrhythmic activity) in an ECG or VCG. Cycles can be delimited by consecutive crossings from negative to positive voltages ("positive crossings") or consecutive crossings from positive to negative voltages ("negative crossings") with respect to a spatial direction or set of directions that includes a reference frame or set of reference frames. The reference frames can correspond to anatomical axes (e.g., left to right in x, top to bottom in y, front to back in z), imaging axes (e.g., CT, MR, or x-ray coordinate frames), body-surface lead vectors, principal axes calculated by principal component analysis of measured or simulated EM source configurations and outputs, or user-defined directions of interest. For example, a three-second VCG can have three cycles, each delimited by the time of positive crossings along the x-axis. Alternatively, the cycles can be delimited by crossings along the y-axis or z-axis. Cycles can also be defined by negative crossings. Cycles can also be identified by processing by identifying the R peak and setting the end of the cycle to an estimate of the end of the T segment.

[0027] Figure 6 is a flow diagram that illustrates the processing of the cycle identification component of the HGD system in some embodiments. The cycle identification component 600 is called to identify cycles in a VCG and provides a normalized VCG of the cycles (nVCG[]). The component in Figure 6 identifies cycles based on negative crossings of the x-axis. In block 601, the component initializes an index j to 2 for indexing through the VCG and sets an index k to 0 for indexing through the identified cycles. In decision block 602, if index j is greater than the size of the VCG, the component has identified all cycles and provides the normalized nVCG and terminates, otherwise the component continues to block 603. In block 603, if the prior voltage on the x-axis of the VCG (VCG.V[j-1].x) is greater than or equal to zero and the indexed voltage on the x-axis of the VCG (VCG.V[j].x) is less than zero (i.e., a negative crossing of the x-axis), then a possible start of a cycle has been identified and the component proceeds to block 604 to identify the cycle, else the component proceeds to block 609. In block 604, the component sets the start of the indexed cycle (C[k].start) equal to index j. In decision block 605, if at least one cycle has already been identified then the end of the previous cycle is known and the component increments index k and proceeds to block 606, else the component increments index k and proceeds to block 609. In block 606, the component sets the end of the previous cycle to index j-1. In block 607, the component extracts the VCG of the previous indexed cycle bounded by the start and end of the previous cycle (eVCG). The component invokes the cycle normalization component in block 608, passing it an indication of the extracted VCG (eVCG) and receiving the normalized cycle (nVCG). The component increments the index j in block 609 for indexing through the VCG and loops to block 602.

[0028] FIG. 7 is a block diagram illustrating the operation of the cycle normalization component of the HGD system in some embodiments. The cycle normalization component 700 is called, passing an indication of the VCG of the cycle, to normalize the cycle. If the cycle is of an ECG, the time and voltage of the cycle may be normalized to values ​​between 0 and 1. The component identifies the maximum vector amplitude V' of the vectors in the cycle in block 701. For example, the vector amplitude of a vector may be calculated by taking the square root of the sum of the squares of the x, y, and z values ​​of the vector. The component sets an index i to index into the next axis of the VCG in block 702. If all axes have already been selected in decision block 703, the component ends to provide the normalized VCG, otherwise the component continues to block 704. The component initializes an index j to 1 in block 704 for indexing through the vectors of the normalized cycle. In decision block 705, if index j is greater than the number of vectors in the normalized cycle, the component loops to block 702 to select the next axis, otherwise the component continues to block 706. In block 706, the component sets the normalized VCG of the indexed vector of the indexed axis to the interpolation of the passed VCG, the indexed vector, and the maximum vector magnitude V'. This interpolation effectively compresses or expands the VCG to the number of vectors in the normalized VCG and divides the x, y, and z values ​​of the vector by the maximum vector magnitude V'. In block 707, the component increments the index j and loops to block 705.

[0029] FIG. 8 is a flow diagram illustrating the processing of the segment extraction component of the HGD system in some embodiments. The segment extraction component 800 extracts the relevant portion of the cycle depending on whether an atrial or ventricular analysis is being performed. The component identifies the R-peak of the cycle in block 801. For example, the component can apply a Pan-Tompkins type algorithm (see Pan, J., Tompkins, WJ, A Real-Time QRS Detection Algorithm, IEEE Reports on Biomedical Engineering (3):230 (1985)). The component identifies the QRST segment in block 802. Once the R-peak is identified, various techniques can be used to identify the QRST segment (i.e., the QT interval). One technique is to use a fixed window a certain time before and a certain time after the R-peak, such as 30 ms before and 250 ms after the R-peak. Another technique can be based on manual identification of the QRST segment, in which case the R-peak may not be identified separately. Another technique may algorithmically identify the QRST segment that takes into account the heart rate. Another technique may algorithmically identify the R onset or T offset that take into account the rate of voltage change. If, in decision block 803, an atrial segment should be identified, the component proceeds to block 804, otherwise the component proceeds to block 806. The component removes the QRST segment from the cycle in block 804, thereby leaving the atrial segment. In decision block 805, if the atrial segment meets the atrial useful criteria, the component continues to indicate the cycle in which the QRST segment was removed, otherwise it indicates that the atrial segment is not useful and exits. The atrial useful criteria may be that the atrial segment of the cycle has a length within a minimum and maximum time, such as 500 ms and 1000 ms. The component removes the non-QRST segments from the cycle in block 806.In decision block 807, if the QRST segment meets the ventricular useful criteria, the component exits indicating the cycle in which the non-QRST segment was removed, otherwise the component exits indicating that the QRST segment is not useful. The component can remove a segment of the cycle represented by the ECG by setting the value corresponding to that segment to zero.

[0030] FIG. 9 is a flow diagram illustrating source location graphic generation processing of the HGD system in some embodiments. The generate SL graphic component 900 inputs patient cycles and outputs a SL graphic for a selected set of patient cycles. The component calls the calculate library similarity score component in block 901 to generate a similarity score for the patient cycle and library cycle pair. The component calls the generate source location indicators component in block 902 to generate an indicator of the source location of each patient cycle. The component receives a selection of one or more patient cycle sets in block 903. The selection can be made by a user using the cycle selection box 230 of the SL graphic 200. The selection can also be received from a software system and data store interfacing with the HGD system, etc. The component ends if no more patient cycle sets are to be selected in decision block 904, otherwise proceeds to block 905. The component calls the set pixel color component in block 905 to set the color of each pixel of the SL graphic for the selected patient cycle. The component outputs the SL graphic in block 906. The component displays a popup when the cursor is moved to different locations on the SL graphic in block 907. For example, moving the cursor over a source location indicator can display a popup containing statistics about the patient cycles associated with the corresponding source location, such as the average similarity score of the highest similarity score of those cycles. The component then loops to block 903 to receive a selection of the patient cycle. In some embodiments, the SL graphic can be three-dimensional and the HGD system can support three-dimensional rotation of the SL graphic so that a person can see the inside, front, and back of the heart.

[0031] FIG. 10 is a flow diagram illustrating the processing of the calculate library similarity score component of the HGD system in some embodiments. The calculate library similarity score component 1000 calculates similarity scores for patient and library cycle pairs and sorts the similarity scores of the patient cycles associated with each source location for each patient cycle. The component selects the next patient cycle in block 1001. The component ends if all patient cycles have already been selected in decision block 1002, otherwise the component proceeds to block 1003. The component selects the next library cycle ("LC") in block 1003. If all library cycles have already been selected for the selected patient cycle in decision block 1004, the component proceeds to block 1006, otherwise the component proceeds to block 1005. The component calculates similarity scores for the patient cycle and library cycle in block 1005 and proceeds to block 1003. The component loops in blocks 1006-1008 to sort the library cycles for each source location. The component selects the next source location in block 1006. In decision block 1007, if all source locations for the patient cycle have already been selected, the component loops to block 1001 to select the next patient cycle, else the component continues in block 1008. In block 1008, the component sorts the library cycles associated with the selected source locations of the selected patient cycle and based on the similarity scores of the selected patient cycle. The component then loops to block 1006 to select the next source location.

[0032] FIG. 11 is a flow diagram illustrating the processing of the generate source location indicator component of the HGD system in some embodiments. The generate source location indicator component generates a source location indicator for each patient cycle. The component selects the next patient cycle in block 1101. The component ends if all patient cycles have already been selected in decision block 1102, otherwise proceeds to block 1103. The component selects the next source location in block 1103. The component proceeds to block 1106 if all source locations have already been selected in decision block 1104, otherwise proceeds to block 1105. The component generates a source location score for the selected patient cycle in block 1105. For example, the source location score can be the highest similarity score of the library cycles (and the selected patient cycle) associated with that source location. As another example, the source location score can be the average of the five highest similarity scores. The component selects the next source location in source location score order in block 1106. In decision block 1107, if the number of source locations having source location indicators to include in the SL graphic has already been selected, the component continues at block 1101, else the component continues at block 1108. In block 1108, the component sets the color of the source locations based on the source location order. In block 1109, the component sets the radius of the source locations based on the source location scores. In block 1110, the component fills a data structure that represents a circle of source locations based on the color and radius. The component then loops to block 1106 to select the next source location.

[0033] 12 is a flow diagram illustrating the processing of the set pixel color component of the HGD system in some embodiments. The set pixel color component 1200 is provided with a patient cycle and calculates a color for each pixel of the SL graphic based on the source location indicator of the patient cycle. The component selects the next pixel of the SL graphic in block 1201. The component ends if all pixels have already been selected in decision block 1202, otherwise the component proceeds to block 1203. In block 1203, the component identifies the source location indicator of the patient cycle that contains the selected pixel. In block 1204, the component calculates the average value of the identified source location indicator based on a data structure representing the source location circle. In block 1205, the component sets the pixel color based on the average value and then loops to block 1201 to select the next pixel.

[0034] The following paragraphs describe various embodiments of aspects of the HGD system. An implementation of the HGD system may employ any combination of these embodiments. The processes described below may be performed by a computer system that includes a processor executing computer-executable instructions stored on a computer-readable storage medium that implements the HGD system.

[0035] Intra-ECG Similarity In some embodiments, a method is provided for presenting information to aid in the assessment of electromagnetic ("EM") sources of a body, executed by one or more computer systems. The method accesses an indication of cycles in an EM measurement of an EM field of an EM source, where each pair of cycles has a similarity score indicating a similarity between the pair of cycles. The method generates a graphic indicating the similarity score of each pair of cycles. The method outputs the graphic to an output device. In some embodiments, the cycles have an order, and the graphic includes a map having a first axis representing each cycle in order and a second axis representing each cycle in order, where intersections of the cycle pairs indicate a similarity score of the cycle pair. In some embodiments, the indication of the similarity score is based on varying a graphic characteristic. In some embodiments, the graphic characteristic is based on color. In some embodiments, the graphic characteristic is based on intensity level. In some embodiments, the graphic further includes a third axis representing a similarity score, and the indication of the similarity score of the cycle pair is based on height along the third axis. In some embodiments, the method rotates the graphic. In some embodiments, the output device is a display device and the method receives a selection of a cycle pair and displays information about the selected cycle pair. In some embodiments, the displayed information includes a similarity score for the selected cycle pair. In some embodiments, the output device is a display device and further includes receiving a selection of a plurality of cycle pairs and displaying information about the selected plurality of cycle pairs. In some embodiments, the displayed information includes an average similarity score, a standard deviation of the similarity scores, a stability index, or a number of groups of similar cycle pairs. In some embodiments, the EM source is a heart and the EM measurements are represented by an electrocardiogram. In some embodiments, the indication of the similarity score is based on changing graphic characteristics. In some embodiments, the EM measurements are generated based on a computational model that models EM activation of the EM source.

[0036] In some embodiments, one or more computer systems are provided that present information to aid in evaluating a patient's heart. The one or more computer systems include one or more computer readable storage media that store computer executable instructions and one or more processors that execute the computer executable instructions stored in the one or more computer readable storage media. The instructions, when executed, access an indicative of cycles in an electrocardiogram of the patient. Each pair of cycles has a similarity score that indicates a similarity between the pair of cycles. The instructions generate a graphic that indicates the similarity score for each pair of cycles. The instructions display the graphic via a display device. In some embodiments, a graphic is provided in which the cycles have an order in the electrocardiogram, the graphic including a map having a first axis representing each cycle in order and a second axis representing each cycle in order, where intersections of the cycle pairs indicate a similarity score for the cycle pairs. In some embodiments, the indicative of the similarity score is based on varying a graphic characteristic. In some embodiments, the graphic characteristic is based on color. In some embodiments, the graphic characteristic is based on intensity level. In some embodiments, the graphic further includes a third axis representing a similarity score, with an indication of the similarity score of the cycle pair based on height along the third axis. In some embodiments, the instructions further receive a selection of the cycle pair and display information about the selected cycle pair. In some embodiments, the displayed information includes a similarity score for the selected cycle pair. In some embodiments, the instructions further receive a selection of a plurality of cycle pairs and display information about the selected plurality of cycle pairs. In some embodiments, the displayed information includes an average similarity score, a standard deviation of the similarity scores, a stability index, or a number of groups of similar cycle pairs. In some embodiments, the instructions further identify electrocardiogram cycles. In some embodiments, the instructions further calculate a similarity score for each cycle pair.

[0037] In some embodiments, one or more computer systems are provided that present information related to the heart. The one or more computer systems include one or more computer readable storage media that store computer executable instructions and one or more processors that execute the computer executable instructions stored on the one or more computer readable storage media. When executed, the instructions receive a request from a user for information related to the heart. The instructions transmit the request for information to a server. The instructions receive information from the server indicative of a similarity score for each pair of cycles of electrical activation of the heart. The similarity score for the cycle pair indicates a similarity between the cycles of the pair. The instructions display a visual indication of the similarity score of the received information on a display device. In some embodiments, the cycles have an order, and the graphic includes a map having a first axis representing each cycle in order and a second axis representing each cycle in order, where intersections of the cycle pairs provide a visual indication of the similarity score for the cycle pair. In some embodiments, the instructions further generate the graphic. In some embodiments, the request is sent and received information is received from the server. In some embodiments, a request is sent and received information is received from a cloud-based system. In some embodiments, the received information includes a graphic. In some embodiments, the visual indication is non-textual.

[0038] Source location In some embodiments, a method is provided for presenting information to aid in the assessment of an electromagnetic ("EM") source in a patient, the method being executed by one or more computer systems. The method accesses a library having library cycles of library EM measurements of an EM field of an EM source. Each library cycle is associated with a source location of the EM source. The method calculates, for each of a plurality of library cycles, a library cycle similarity score indicative of a similarity between the library cycle and a patient cycle of the patient EM measurements of the patient. The method identifies a source location associated with a target library cycle based on the similarity score of the target library cycle. The method generates a graphic including a representation of a portion of the EM source location and a source location indicator positioned based on the identified source location. The source location indicator has a characteristic based on the similarity score associated with the target library cycle. The method outputs the graphic to an output device. In some embodiments, the characteristic is a size of the source location indicator based on the similarity score. In some embodiments, the source location indicator is a circle and the size is indicative of a radius of the circle. In some embodiments, a smaller size indicates a higher similarity score. In some embodiments, the characteristic is a color. In some embodiments, the source location indicator is a circle and the characteristic is a size of the circle and the characteristic is a color. In some embodiments, the color varies from the center of the circle to the periphery of the circle. In some embodiments, the patient cycle is one of a plurality of patient cycles, and a graphic is generated for each patient cycle, and the graphic is output in sequence to animate the location of the source location. In some embodiments, a plurality of source locations associated with the target library cycle are identified based on the similarity score of the target library cycle, and the graphic includes source location indicators positioned based on the identified source locations, each source location indicator having a characteristic based on the similarity score associated with the target library cycle. In some embodiments, the characteristic is a size of the source location indicator, and the size is based on the similarity score of the identified library cycle. In some embodiments, a smaller size indicates a higher similarity score.In some embodiments, the characteristic is color and each source location indicator has a different color. In some embodiments, when source location indicators overlap on the graphic, the color of the overlap is based on a combination of the colors of the overlapping source location indicators. In some embodiments, the source location indicator is a circle and the characteristic is a size of the circle and the characteristic is a color indicating an order of source location scores based on the similarity scores of the target library cycles. In some embodiments, the color of the circle is at the center and the coloring of the circle varies from the center to the periphery. In some embodiments, the method receives a selection of a patient cycle specified by a human. In some embodiments, the method identifies a patient cycle. In some embodiments, the method outputs statistics regarding the identified target cycle. In some embodiments, the identification identifies a source location associated with the target library cycle based on the similarity scores of the target library cycle and the graphic includes a source location indicator for the identified source location. In some embodiments, the EM measurements are generated based on a computational model that models EM activation of the EM source. In some embodiments, the EM source is a heart and the EM measurements are represented by an electrocardiogram. In some embodiments, the source location is associated with abnormal cardiac electrical activation, further comprising displaying a source type indicator indicative of a source type of the abnormal electrical activation, hi some embodiments, the source type is selected from the group consisting of rotor, focal, fibrillation, tachycardia, and flutter.

[0039] In some embodiments, one or more computer systems are provided that present information to aid in the evaluation of a patient's heart. The one or more computer systems include one or more computer readable storage media that store computer executable instructions and one or more processors that execute the computer executable instructions stored in the one or more computer readable storage media. The instructions, when executed, calculate, for each of a plurality of library cycles in a library, a library cycle similarity score that indicates a similarity between the library cycle and a patient cycle of a patient electrocardiogram of the patient. Each library cycle is associated with a source location of the heart. The instructions identify a source location associated with a target library cycle based on the similarity score of the target library cycle. The instructions generate a graphic that includes a representation of a portion of the heart and a source location indicator that is positioned on the heart based on the identified source location. The source location indicator has a characteristic based on the similarity score associated with the target library cycle. The instructions display the graphic via a display device. In some embodiments, the characteristic is a size of the source location indicator that is based on the similarity score. In some embodiments, the source location indicator is a circle and the size indicates a radius of the circle. In some embodiments, a smaller size indicates a higher similarity score. In some embodiments, the characteristic is color. In some embodiments, the source location indicator is a circle and the characteristic is a size of the circle and the characteristic is color. In some embodiments, the color varies from the center of the circle to the periphery of the circle. In some embodiments, the patient cycle is one of a plurality of patient cycles and the instructions generate a graphic for each patient cycle and display the graphics in sequence to animate the change in source location of the patient cycle. In some embodiments, the instructions identify a source location associated with the target library cycle based on a similarity score of the target library cycle and generate a graphic including source location indicators positioned based on the identified source location, each source location indicator having a characteristic based on a similarity score associated with the target library cycle.In some embodiments, the characteristic is a size of the source location indicator, the size being based on a similarity score of the identified library cycle. In some embodiments, a smaller size indicates a higher similarity score. In some embodiments, the characteristic is a color, and each source location indicator has a different color. In some embodiments, if source location indicators overlap on the graphic, the color of the overlap is based on a combination of colors of the overlapping source location indicators. In some embodiments, the source location indicator is a circle, the characteristic is a size of the circle, and the characteristic is a color indicating an order of source location scores based on the similarity scores of the target library cycle. In some embodiments, the color of the circle is at the center and the coloring of the circle varies from the center to the periphery. In some embodiments, the instructions display statistics regarding the identified target cycle. In some embodiments, the identifying identifies a source location associated with the target library cycle based on the similarity score of the target library cycle, and the graphic includes a source location indicator of the identified source location. In some embodiments, at least a portion of the library cycles are generated based on a computational model that models electrical activation of the heart. In some embodiments, at least a portion of the library cycles of electrocardiograms are collected from people. In some embodiments, the source location is associated with abnormal electrical activation of the heart, and the instructions display a source type indicator indicative of a source type of the abnormal electrical activation, hi some embodiments, the source type is selected from the group consisting of rotor, focal, fibrillation, tachycardia, and flutter.

[0040] In some embodiments, one or more computer systems are provided that present information to aid in the evaluation of electromagnetic ("EM") sources in a patient. The one or more computer systems include one or more computer readable storage media that store computer executable instructions and one or more processors that execute the computer executable instructions stored in the one or more computer readable storage media. The instructions control the one or more computer systems to access indicative of patient cycles in EM measurements of an EM field of an EM source in the patient and to access indicative of simulated cycles in simulated EM measurements generated based on a simulation of EM activation of the EM source. The instructions control the one or more computer systems to calculate a similarity score for cycle pairs, each pair including a patient cycle and a simulated cycle. The similarity score indicates a similarity between the patient cycle and the simulated cycle of the pair. The instructions control the one or more computer systems to generate a graphic providing a visual indication of the similarity scores of a plurality of cycle pairs and output the graphic to an output device. In some embodiments, the graphic includes a map having a first axis representing a patient cycle and a second axis representing a simulated cycle, where intersections of cycle pairs on the map provide a visual indication of a similarity score for the cycle pairs. In some embodiments, the visual indication of the similarity score is based on varying a graphic characteristic. In some embodiments, the graphic further includes a third axis representing the similarity score, where the visual indication of the similarity score for the cycle pairs is based on height along the third axis. In some embodiments, the EM measurements are generated based on a computational model that models EM activation of the EM source. In some embodiments, the instructions control one or more computer systems to apply the computational model to run a simulation that models EM activation of the EM source and derive the EM measurements from the modeled EM activation.

[0041] In some embodiments, a method is provided for information aiding in assessment of an electromagnetic ("EM") source, executed by one or more computer systems. The method accesses an indication of a first cycle in a first EM measurement of a first EM field and an indication of a second cycle in a second EM measurement of a second EM field. The method calculates a similarity score for the cycle pairs, each pair including a first cycle and a second cycle. The similarity score indicates a similarity between the first cycle and the second cycle of the pair. The method generates a graphic providing a visual indication of the similarity scores of the multiple cycle pairs. In some embodiments, the graphic includes a map having a first axis representing the first cycle and a second axis representing the second cycle, where intersections of the cycle pairs on the map provide a visual indication of the similarity scores of the cycle pairs. In some embodiments, the first EM measurement and the second EM measurement are collected from the same patient at different times. In some embodiments, the first EM measurement is collected from a first patient and the second EM measurement is collected from a second patient. In some embodiments, the first EM measurement is collected from a patient and the second EM measurement is a simulated EM measurement. In some embodiments, the first EM measurement and the second EM measurement are the same simulated EM measurement. In some embodiments, the first EM measurement and the second EM measurement are derived from different simulations.

[0042] In some embodiments, a method is provided for presenting information to aid in the assessment of an EM source of a body, the method being executed by one or more computer systems. The method accesses an indicative of cycles in an EM measurement of an EM field of an EM source. The method calculates, for each of a first cycle of a plurality of cycles and each of a second cycle of a plurality of cycles, a similarity score for a cycle pair including the first cycle and the second cycle. The similarity score indicates a similarity between the first cycle and the second cycle. The method generates a graphic providing a non-textual indicative of the similarity score of the cycle pair. The method outputs the graphic to an output device. In some embodiments, the EM measurements are collected from a person. In some embodiments, the EM measurements are generated based on a computational model that models EM activation of the EM source. In some embodiments, the method further applies the computational model to perform a simulation that models EM activation of the EM source and derives the EM measurements from the modeled EM activation. In some embodiments, the non-textual indicative of the similarity score is based on varying a graphic characteristic. In some embodiments, the graphic characteristic is based on a color. In some embodiments, the graphic characteristic is based on an intensity level. In some embodiments, the graphic includes a map having a first axis representing each cycle and a second axis representing each cycle, where intersections of cycle pairs on the map provide a non-textual indication of the similarity score of the cycle pair. In some embodiments, the graphic further includes a third axis representing the similarity score, where the non-textual indication of the similarity score of the cycle pair is based on height along the third axis. In some embodiments, the output device is a display device and further includes receiving a selection of the cycle pair and displaying information about the selected cycle pair.

[0043] In some embodiments, one or more computer systems are provided that present information to aid in the evaluation of an EM source in a patient. The one or more computer systems include one or more computer readable storage media that store computer executable instructions and one or more processors that execute the computer executable instructions stored in the one or more computer readable storage media. The instructions access an indication of a patient cycle in EM measurements of an EM field of an EM source in the patient. The instructions access an indication of a simulated cycle in simulated EM measurements generated based on a simulation of EM activation of the EM source. The instructions calculate a similarity score for cycle pairs, each pair including a patient cycle and a simulated cycle. The similarity score indicates a similarity between the patient cycle and the simulated cycle of the pair. The instructions generate a graphic that provides a visual indication of the similarity scores of a plurality of cycle pairs. The instructions output the graphic to an output device. In some embodiments, the graphic includes a map having a first axis representing a patient cycle and a second axis representing a simulated cycle, where intersections of cycle pairs on the map provide a visual indication of the similarity scores of the cycle pairs. In some embodiments, the visual indication of the similarity score is based on varying a graphic characteristic. In some embodiments, the graphic further includes a third axis representing the similarity score, and the visual indication of the cycle pair's similarity score is based on height along the third axis. In some embodiments, the EM measurements are generated based on a computational model that models EM activation of the EM source. In some embodiments, the instructions further apply the computational model to perform a simulation that models EM activation of the EM source and derive the EM measurements from the modeled EM activation.

[0044] In some embodiments, one or more computer systems are provided that present information related to a patient's heart. The one or more computer systems include one or more computer readable storage media that store computer executable instructions and one or more processors that execute the computer executable instructions stored in the one or more computer readable storage media. The instructions access an indication of cycles in the patient's electrocardiogram, where each cycle pair has a similarity score that indicates a similarity between the pair's cycles. The instructions generate a graphical representation that indicates the similarity score for each cycle pair. In some embodiments, the graphical representation includes a map having a first axis representing each cycle and a second axis representing each cycle, where intersections of the cycle pairs on the map provide a visual indication of the similarity score for the cycle pair. In some embodiments, the visual indication of the similarity score is based on varying a graphic characteristic. In some embodiments, the graphical representation further includes a third axis representing the similarity score, where the visual indication of the cycle pair's similarity score is based on a height along the third axis. In some embodiments, the instructions further receive a selection of a cycle pair and display information related to the selected cycle pair.

[0045] In some embodiments, a method is provided for providing information to aid in assessment of an EM source, the method being executed by one or more computer systems. The method accesses an indication of a first cycle in a first EM measurement of a first EM field and an indication of a second cycle in a second EM measurement of a second EM field. The method calculates a similarity score for the cycle pairs, each pair including a first cycle and a second cycle, the similarity score indicating a similarity between the first cycle and the second cycle of the pair. The method generates a graphic providing a visual indication of the similarity scores for a plurality of cycle pairs. In some embodiments, the graphic includes a map having a first axis representing the first cycle and a second axis representing the second cycle, the intersection of the cycle pairs on the map providing a visual indication of the similarity scores for the cycle pairs. In some embodiments, the first EM measurement and the second EM measurement are collected from the same patient at different times. In some embodiments, the first EM measurement is collected from a first patient and the second EM measurement is collected from a second patient. In some embodiments, the first EM measurement is collected from a patient and the second EM measurement is a simulated EM measurement. In some embodiments, the first EM measurement and the second EM measurement are the same simulated EM measurement. In some embodiments, the first EM measurement and the second EM measurement are derived from different simulations.

[0046] Although the subject matter has been described in language specific to structural features and / or acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. Accordingly, the invention is not limited, except as by the appended claims.

Claims

1. 1. A method for presenting information to aid in assessment of electromagnetic ("EM") sources in a patient, the method being implemented by one or more computer systems, comprising: accessing a library of library EM measurements of the EM field of the EM source, each library beat being associated with a source position of the EM source; calculating, for each of a plurality of library beats, a similarity score for the library beat indicative of a similarity between the library beat and a patient beat of a patient EM measurement of the patient, where each of the plurality of library beats is not derived from the patient EM measurement of the patient; identifying a source location associated with the target library beat based on the similarity score of the target library beat; generating a graphic including a representation of a portion of the EM source and a source location indicator having characteristics based on the similarity score associated with the target library beat, the source location indicator being positioned based on the identified source location; outputting the graphic to an output device; Including, the EM source is the heart; The method, wherein the characteristic is a size of the source location indicator based on the similarity score.

2. the source location indicator is a circle, and the size indicates a radius of the circle. The method of claim 1.

3. Smaller sizes indicate higher similarity scores. The method of claim 1.

4. the characteristic is color; The method of claim 1.

5. A method for presenting information to assist in assessment of electromagnetic ("EM") sources in a patient, the method being implemented by one or more computer systems, comprising: accessing a library of library EM measurements of the EM field of the EM source, each library beat being associated with a source position of the EM source; calculating, for each of a plurality of library beats, a similarity score for the library beat indicative of a similarity between the library beat and a patient beat of a patient EM measurement of the patient, where each of the plurality of library beats is not derived from the patient EM measurement of the patient; identifying a source location associated with the target library beat based on the similarity score of the target library beat; generating a graphic including a representation of a portion of the EM source and a source location indicator having characteristics based on the similarity score associated with the target library beat, the source location indicator being positioned based on the identified source location; outputting the graphic to an output device; Including, the EM source is the heart; 13. The method of claim 12, wherein the source location indicator is a circle, the characteristic is a size of the circle, and the characteristic is a color.

6. The color varies from the center of the circle to the periphery of the circle. The method according to claim 5.

7. the patient pulse being one of a plurality of patient pulses, further comprising generating a graphic for each patient pulse and outputting the graphics in sequence to animate the position of the source location. The method of claim 1.

8. identifying a plurality of source locations associated with the target library beat based on the similarity score of the target library beat, the graphic including source location indicators positioned based on the identified source locations, each source location indicator having a characteristic based on the similarity score associated with the target library beat. The method of claim 1.

9. the characteristic is color, each source location indicator having a different color, and when source location indicators overlap on the graphic, the color of the overlap is based on a combination of the colors of the overlapping source location indicators; The method according to claim 8.

10. the library EM measurements are generated based on a computational model that models the EM activity of the EM source; The method of claim 1.

11. the library EM measurements and the patient EM measurements are represented by electrocardiograms; The method of claim 1.

12. the source location is associated with the abnormal electrical activation of the heart, further comprising displaying a source type indicator indicative of a source type of the abnormal electrical activation. The method of claim 11.

13. 1. One or more computer systems that present information to assist in cardiac evaluation of a patient, one or more computer readable storage media storing computer executable instructions; one or more processors capable of executing the computer-executable instructions stored on the one or more computer-readable storage media; the computer-executable instructions are configured to: For each of a plurality of library beats in a library, a similarity score for the library beat indicating a similarity between a library beat associated with an origin location of the heart and a patient beat of a patient electrocardiogram of the patient, where each of the plurality of library beats in the library is not derived from a patient electrocardiogram of the patient. identifying a source location associated with the target library beat based on the similarity score of the target library beat; generating a graphic based on the identified source locations, the graphic including a representation of a portion of the heart and a source location indicator disposed on the heart having characteristics based on the similarity score associated with the target library beat; displaying said graphic via a display device; Controlled as follows: The characteristic is a size of the source location indicator based on the similarity score. One or more computer systems comprising:

14. the source location indicator is a circle, and the size indicates a radius of the circle.

14. One or more computer systems according to claim 13.

15. Smaller sizes indicate higher similarity scores.

15. One or more computer systems according to claim 14.

16. the characteristic is color; 14. One or more computer systems according to claim 13.

17. One or more computer systems that present information to assist in cardiac evaluation of a patient, comprising: one or more computer readable storage media storing computer executable instructions; one or more processors capable of executing the computer-executable instructions stored on the one or more computer-readable storage media; the computer-executable instructions are configured to: For each of a plurality of library beats in a library, a similarity score for the library beat indicating a similarity between a library beat associated with an origin location of the heart and a patient beat of a patient electrocardiogram of the patient, where each of the plurality of library beats in the library is not derived from a patient electrocardiogram of the patient. identifying a source location associated with the target library beat based on the similarity score of the target library beat; generating a graphic based on the identified source locations, the graphic including a representation of a portion of the heart and a source location indicator disposed on the heart having characteristics based on the similarity score associated with the target library beat; displaying said graphic via a display device; Controlled as follows: The one or more computer systems according to claim 1, wherein the source location indicator is a circle, the characteristic is a size of the circle, and the characteristic is a color.

18. The color varies from the center of the circle to the periphery of the circle.

18. One or more computer systems according to claim 17.

19. the patient pulse is one of a plurality of patient pulses, generating a graphic of each patient pulse, the computer executable instructions further controlling the one or more computer systems to sequentially display the graphics to animate the change in the origin location of the patient pulse.

14. One or more computer systems according to claim 13.

20. The computer executable instructions further control the one or more computer systems to: identify source locations associated with the target library beats based on the similarity scores of the target library beats; and generate the graphic including source location indicators positioned based on the identified source locations, each source location indicator having a characteristic based on the similarity score associated with a target library beat.

14. One or more computer systems according to claim 13.

21. One or more computer systems that present information to assist in cardiac evaluation of a patient, comprising: one or more computer readable storage media storing computer executable instructions; one or more processors capable of executing the computer-executable instructions stored on the one or more computer-readable storage media; the computer-executable instructions are configured to: For each of a plurality of library beats in a library, a similarity score for the library beat indicating a similarity between a library beat associated with an origin location of the heart and a patient beat of a patient electrocardiogram of the patient, where each of the plurality of library beats in the library is not derived from a patient electrocardiogram of the patient. identifying a source location associated with the target library beat based on the similarity score of the target library beat; generating a graphic based on the identified source locations, the graphic including a representation of a portion of the heart and a source location indicator disposed on the heart having characteristics based on the similarity score associated with the target library beat; displaying said graphic via a display device; Controlled as follows: The computer executable instructions further control the one or more computer systems to: identify source locations associated with the target library beats based on the similarity scores of the target library beats; and generate the graphic including source location indicators positioned based on the identified source locations, each source location indicator having a characteristic based on the similarity score associated with a target library beat. The one or more computer systems, wherein the characteristic is a size of the source location indicator, the size being based on the similarity score of the target library beat.

22. Smaller sizes indicate higher similarity scores.

22. One or more computer systems according to claim 21.

23. the characteristic is color, and each source location indicator has a different color; 21. One or more computer systems according to claim 20.

24. if source location indicators overlap on the graphic, the color of the overlap is based on a combination of the colors of the overlapping source location indicators; 24. One or more computer systems according to claim 23.

25. One or more computer systems that present information to assist in cardiac evaluation of a patient, comprising: one or more computer readable storage media storing computer executable instructions; one or more processors capable of executing the computer-executable instructions stored on the one or more computer-readable storage media; the computer-executable instructions are configured to: For each of a plurality of library beats in a library, a similarity score for the library beat indicating a similarity between a library beat associated with an origin location of the heart and a patient beat of a patient electrocardiogram of the patient, where each of the plurality of library beats in the library is not derived from a patient electrocardiogram of the patient. identifying a source location associated with the target library beat based on the similarity score of the target library beat; generating a graphic based on the identified source locations, the graphic including a representation of a portion of the heart and a source location indicator disposed on the heart having characteristics based on the similarity score associated with the target library beat; displaying said graphic via a display device; Controlled as follows: The computer executable instructions further control the one or more computer systems to: identify source locations associated with the target library beats based on the similarity scores of the target library beats; and generate the graphic including source location indicators positioned based on the identified source locations, each source location indicator having a characteristic based on the similarity score associated with a target library beat. One or more computer systems, characterized in that the source location indicator is a circle, the characteristic is a size of the circle, and the characteristic is a color indicating an order of source location scores based on the similarity scores of the target library beats.

26. The computer executable instructions further control the one or more computer systems to display statistics regarding the target library beats.

14. One or more computer systems according to claim 13.

27. at least a portion of the library beats are generated based on a computational model that models electrical activation of the heart.

14. One or more computer systems according to claim 13.

28. At least a portion of the library beats of electrocardiograms are collected from people.

14. One or more computer systems according to claim 13.

29. A computer program for causing one or more computer systems to carry out the method according to any one of claims 1 to 12.

30. 30. One or more computer readable storage media having stored thereon the computer program of claim 29.

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