# US 11,298,066 B2 · System and method for electrophysiological mapping > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,298,066 B2 - Document ID: US11298066B2 - Status: Granted - Kind: B2 - Application number: 16/623,206 - Filed: 2018-05-25 - Published: 2021-05-13 - Granted: 2022-04-12 - Earliest claimed: 2017-07-07 - Assignees: St. Jude Medical, Cardiology Division, Inc. - Applicants: St. Jude Medical, Cardiology Division, Inc. - Inventors: Jan O. Mangual-Soto - Web page: https://patentgrep.com/patent/US11298066B2 ## CPC - A61B 5/343: Potential distribution indication - A61B 5/743: {Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots} - A61B 5/0245: by using sensing means generating electric signals, {i.e. ECG signals} - A61B 5/0538: invasively, e.g. using a catheter - A61B 5/283: Invasive - A61B 5/287: Holders for multiple electrodes, e.g. electrode catheters for electrophysiological study [EPS] - A61B 5/367: Electrophysiological study [EPS], e.g. electrical activation mapping or electro-anatomical mapping - A61B 5/7475: {User input or interface means, e.g. keyboard, pointing device, joystick} - A61B 5/6852: {Catheters} - A61B 5/7221: {Determining signal validity, reliability or quality (preventing, reducing or removing noise induced by motion artefacts A61B5/7207; noise originating from a therapeutic or surgical apparatus A61B5/7217)} - A61B 18/1492: {having a flexible, catheter-like structure, e.g. for heart ablation (A61B18/1477 takes precedence)} - A61B 2034/2051: {Electromagnetic tracking systems} - A61B 2562/04: Arrangements of multiple sensors of the same type - A61B 2562/06: Arrangements of multiple sensors of different types - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract An electrophysiology map of a portion of a patient's anatomy can be visualized using an electroanatomical mapping system. The system receives a plurality of electrophysiology data points (e.g., an electrophysiology map), which includes a plurality of electrophysiology signals. The system then creates a distribution (e.g., a histogram) for one or more characteristics of the plurality of electrophysiology signals (e.g., dominant cycle length, regular cycle length, peak-to-peak voltage, fractionation, conduction velocity, or the like). The system then analyzes the distribution to determine a display convention (e.g., a range and scale) for a graphical representation of the characteristic based on, for example, a best-fit shape of the distribution, a skew of the distribution, a range of the distribution, and/or a most dominant value of the distribution. The graphical representation can then be output according to the display convention. ## Claims ### Claim 1 A method of visualizing an electrophysiology map of a portion of a patient's anatomy using an electroanatomical mapping system, the method comprising: the electroanatomical mapping system receiving a plurality of electrophysiology data points, the plurality of electrophysiology data points comprising a plurality of electrophysiology signals; the electroanatomical mapping system analyzing the plurality of electrophysiology signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals; the electroanatomical mapping system outputting a graphical representation of the at least one characteristic of the plurality of electrophysiology signals, wherein a display convention for the graphical representation is determined according to the best-fit curve for the distribution of values of the at least one characteristic of the plurality of electrophysiology signals. ### Claim 2 (depends on 1) The method according to claim 1, wherein analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals comprises analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of dominant cycle lengths of the plurality of electrophysiology signals. ### Claim 3 (depends on 1) The method according to claim 1, wherein analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals comprises analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of regular cycle lengths of the plurality of electrophysiology signals. ### Claim 4 (depends on 1) The method according to claim 1, wherein analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals comprises analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of peak-to-peak voltages of the plurality of electrophysiology signals. ### Claim 5 (depends on 1) The method according to claim 1, wherein analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals comprises analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of fractionated potentials of the plurality of electrophysiology signals. ### Claim 6 (depends on 1) The method according to claim 1, wherein analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals comprises analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of conduction velocities of the plurality of electrophysiology signals. ### Claim 7 (depends on 1) The method according to claim 1, further comprising analyzing the plurality of electrophysiological signals to determine one or more of: a skew of the distribution of values of the at least one characteristic of the plurality of electrophysiology signals; a range of the distribution of values of the at least one characteristic of the plurality of electrophysiology signals; and a most dominant value of the distribution of values of the at least one characteristic of the plurality of electrophysiology signals. ### Claim 8 (depends on 1) The method according to claim 1, wherein analyzing the plurality of electrophysiological signals to determine a best-fit curve for a distribution of values of at least one characteristic of the plurality of electrophysiology signals comprises generating a histogram of the values of the at least one characteristic of the plurality of electrophysiology signals. ### Claim 9 (depends on 1) The method according to claim 1, wherein a scale for the display convention is set according to a shape of the best-fit curve of the distribution of values of the at least one characteristic of the plurality of electrophysiology signals. ### Claim 10 A method of visualizing an electrophysiology map of a portion of a patient's anatomy using an electroanatomical mapping system, the method comprising: the electroanatomical mapping system receiving a plurality of electrophysiology data points, the plurality of electrophysiology data points comprising a plurality of electrophysiology signals; the electroanatomical mapping system creating a histogram of values of a characteristic of the plurality of electrophysiology signals; the electroanatomical mapping system analyzing the histogram of values to determine a most dominant value; the electroanatomical mapping system defining a display convention for a graphical representation of the characteristic; and the electroanatomical mapping system outputting the graphical representation of the characteristic according to the display convention, wherein a range of the display convention is centered at the most dominant value. ### Claim 11 (depends on 10) The method according to claim 10, wherein the range of the display convention extends from a low-end cutoff 45% below the most dominant value to a high-end cutoff 45% above the most dominant value. ### Claim 12 (depends on 10) The method according to claim 10, wherein a scale of the display convention between a low-end cutoff value and the most dominant value differs from a scale of the display convention between the most dominant value and a high-end cutoff value. ### Claim 13 (depends on 12) The method according to claim 12, wherein the scale of the display convention between the low-end cutoff value and the most dominant value and the scale of the display convention between the most dominant value and a high-end cutoff value are determined according to a shape of a best-fit curve to the histogram. ### Claim 14 (depends on 10) The method according to claim 10, wherein the characteristic comprises dominant cycle length, and wherein creating a histogram of values comprises binning values of dominant cycle length into bins of 5 ms width ranging from 100 ms to 300 ms. ### Claim 15 (depends on 10) The method according to claim 10, wherein the characteristic comprises regular cycle length, and wherein creating a histogram of values comprises binning values of regular cycle length into bins of 2 ms width ranging from 0 ms to 100 ms. ### Claim 16 (depends on 10) The method according to claim 10, wherein the characteristic comprises peak-to-peak voltage, and wherein creating a histogram of values comprises binning values of peak-to-peak voltage into bins of 0.05 mV width ranging from 0 mV to 2.5 mV. ### Claim 17 (depends on 10) The method according to claim 10, wherein the characteristic comprises fractionation, and wherein creating a histogram of values comprises binning values of fractionation into bins of 5 ms width ranging from 50 ms to 200 ms. ### Claim 18 (depends on 10) The method according to claim 10, wherein the characteristic comprises conduction velocity, and wherein creating a histogram of values comprises binning values of conduction velocity into bins of 0.05 mm/s width ranging from 0 mm/s to 2 mm/s. ### Claim 19 A system for visualizing an electrophysiology map of a portion of a patient's anatomy, comprising: a visualization processor configured to: receive as input a plurality of electrophysiology data points, the plurality of electrophysiology data points comprising a plurality of electrophysiology signals; create a histogram of values of a characteristic of the plurality of electrophysiology signals; analyze the histogram of values to determine a best-fit curve to the histogram; define a display convention for a graphical representation of the characteristic based upon a shape of the best-fit curve to the histogram; and output the graphical representation of the characteristic according to the display convention. ### Claim 20 (depends on 19) The system according to claim 19, wherein a scale of the display convention is determined according to the shape of the best-fit curve to the histogram.