System and method for visualization of vectorcardiograms for ablation procedures
Inventors
Assignees
Interested in licensing this patent?
MTEC can help explore whether this patent might be available for licensing for your application.
Publication Number
US-12329463-B1
Publication Date
2025-06-17
Expiration Date
Abstract
A system for visualization of vectorcardiograms for ablation procedures, the system including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to receive an input matrix having a plurality of electrocardiogram signals associated with a plurality of time variables, transform the plurality of electrocardiogram signals into a cardiac vector as a function of the input matrix, and determine at least one ablative reaction as a function of the cardiac vector, wherein determining the at least one ablative reaction includes generating a graphical visualization of an X-Y plot, wherein cardiac deviations are plotted along a vertical axis of the X-Y plot and time variables are plotted along a horizontal axis of the X-Y plot.
Core Innovation
The invention is a system and method for visualization of vectorcardiograms for ablation procedures. The system receives an input matrix comprising a plurality of electrocardiogram signals associated with a plurality of time variables, wherein the electrocardiogram signals are generated using at least one sensor of a plurality of sensors connected to a patient during an ablation procedure. The system transforms the plurality of electrocardiogram signals into a cardiac vector as a function of the input matrix, and determines at least one ablative reaction as a function of the cardiac vector.
A graphical visualization is generated to support the determination of the at least one ablative reaction. The system generates an X-Y plot in which cardiac deviations are plotted along a vertical axis and time variables are plotted along a horizontal axis. In addition, the system generates a vectorcardiogram image as a function of the cardiac vector, including the use of three-dimensional space and vector loops in some implementations.
The system further uses cardiographic machine learning with iterative training based on vector cardiogram images correlated to ablative reactions and a user input that includes a correction to one or more ablative reactions. The system determines the at least one ablative reaction as a function of the vectorcardiogram image using the trained cardiographic machine learning model. Based on the at least one ablative reaction, the system determines a new heart abnormality that occurred during the ablation procedure.
Claims Coverage
The provided independent claims include a system claim and a method claim. Across these claims, the inventive features include visualization of vectorcardiograms for ablation procedures, transforming electrocardiogram signals into a cardiac vector, determining at least one ablative reaction using an X-Y plot and a vectorcardiogram image, iterative training of a cardiographic machine learning model with user-corrected ablative reaction data, and determining a new heart abnormality based on the ablative reaction(s).
Vectorcardiogram visualization system for ablation procedures
A system for visualization of vectorcardiograms for ablation procedures that receives an input matrix of electrocardiogram signals associated with time variables from sensors connected to a patient during an ablation procedure.
Transforming electrocardiogram signals into a cardiac vector
The system transforms the plurality of electrocardiogram signals into a cardiac vector as a function of the input matrix.
Determining ablative reactions using X-Y plot and vectorcardiogram image
The system determines at least one ablative reaction as a function of the cardiac vector, including generating an X-Y plot with cardiac deviations on a vertical axis and time variables on a horizontal axis, and generating a vectorcardiogram image as a function of the cardiac vector.
Iterative cardiographic machine learning training with user corrections
The system trains, iteratively, a cardiographic machine learning model as a function of cardiographic training data and a user input, where the cardiographic training data comprises a plurality of vector cardiogram images correlated to a plurality of ablative reactions and the user input comprises a correction to one or more ablative reactions.
Using the trained model to determine ablative reactions and a new heart abnormality
The system determines the at least one ablative reaction as a function of the vectorcardiogram image using the trained cardiographic machine learning model, and determines a new heart abnormality that occurred during the ablation procedure based on the at least one ablative reaction.
Vectorcardiogram visualization method for ablation procedures
A method for visualization of vectorcardiograms for ablation procedures that receives an input matrix of electrocardiogram signals associated with time variables from sensors connected to a patient during an ablation procedure.
Transforming electrocardiogram signals into a cardiac vector (method)
The method transforms the plurality of electrocardiogram signals into a cardiac vector as a function of the input matrix.
Determining ablative reactions using X-Y plot and vectorcardiogram image (method)
The method determines at least one ablative reaction as a function of the cardiac vector, including generating an X-Y plot with cardiac deviations on a vertical axis and time variables on a horizontal axis, and generating a vectorcardiogram image as a function of the cardiac vector.
Iterative cardiographic machine learning training with user corrections (method)
The method trains, iteratively, a cardiographic machine learning model as a function of cardiographic training data and a user input, where the cardiographic training data comprises a plurality of vector cardiogram images correlated to a plurality of ablative reactions and the user input comprises a correction to one or more ablative reactions.
Using the trained model to determine ablative reactions and a new heart abnormality (method)
The method determines the at least one ablative reaction as a function of the vectorcardiogram image using the trained cardiographic machine learning model, and determines a new heart abnormality that occurred during the ablation procedure based on the at least one ablative reaction.
Claim coverage centers on transforming time-referenced electrocardiogram signals into a cardiac vector, visualizing cardiac deviations with an X-Y plot and a vectorcardiogram image, determining at least one ablative reaction from those outputs, and iteratively training and applying a cardiographic machine learning model using vector cardiogram images correlated to ablative reactions and user corrections. Both claims also include determining a new heart abnormality during the ablation procedure based on the ablative reaction(s).
Stated Advantages
Documented Applications
No documented applications found
Interested in licensing this patent?