# US 2021/0275080 A1 · Electrocardiogram analytical tool > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0275080 A1 - Document ID: US20210275080A1 - Status: Published application - Kind: A1 - Application number: 16/329,480 - Filed: 2017-08-31 - Published: 2021-09-09 - Earliest claimed: 2016-08-31 - Assignees: Mayo Foundation for Medical Education and Research - Applicants: Mayo Foundation for Medical Education and Research - Inventors: Peter A. Noseworthy; Bo Qiang; Paul A. Friedman; Alan M. Sugrue; Vaclav Kremen; Bryan L. Striemer; Charles J. Bruce; Virend K. Somers; Kevin E. Bennet; Michael J. Ackerman; Samuel J. Asirvatham; John J. Dillon; Christopher V. DeSimone - Web page: https://patentgrep.com/patent/US20210275080A1 ## CPC - A61B 5/364: Detecting abnormal ECG interval, e.g. extrasystoles, ectopic heartbeats - A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor} - A61B 5/339: Displays specially adapted therefor - A61B 5/353: Detecting P-waves - A61B 5/355: Detecting T-waves - A61B 5/366: Detecting abnormal QRS complex, e.g. widening - A61B 5/7203: {for noise prevention, reduction or removal} - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 50/30: for calculating health indices; for individual health risk assessment - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract Systems, methods, devices, and techniques for analyzing and applying features of a T-wave derived from an electrocardiogram. A computing system can receive a set of data that characterizes an electrocardiogram of a patient. The system can analyze the set of data to identify a T-wave that occurs in the electrocardiogram. The system can determine values of one or more features of the T-wave and provide the information that identifies the values of the one or more features of the T-wave to a user. ## Claims ### Claim 1 A computer-implemented method, comprising: receiving, by a computing system, a set of data that characterizes an electrocardiogram of a patient; analyzing, by the computing system, the set of data that characterizes the electrocardiogram of the patient to identify a T-wave that occurs in the electrocardiogram; determining, by the computing system and in response to identifying a T-wave that occurs in the electrocardiogram, values of one or more features of the T-wave; and providing, by the computing system and to a client device of a user, information that identifies the values of the one or more features of the T-wave. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein analyzing the set of data that characterizes the electrocardiogram of the patient to identify the T-wave that occurs in the cardiogram comprises automatically identifying a particular segment of the electrocardiogram that corresponds to the T-wave, from among a plurality of segments of the electrocardiogram that correspond to different portions of the electrocardiogram that include the T-wave and at least one of a P-wave or a QRS-complex. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, further comprising: displaying, in a graphical user interface on an electronic display coupled to the computing system, a visual representation of the electrocardiogram for one or more heartbeats of the patient; and in conjunction with displaying the visual representation of the electrocardiogram, visually marking the particular segment of the electrocardiogram that corresponds to the T-wave. ### Claim 4 (depends on 3) The computer-implemented method of claim 3, further comprising in conjunction with displaying the visual representation of the electrocardiogram, visually marking a second segment of the electrocardiogram that corresponds to the QRS-complex. ### Claim 5 (depends on 3) The computer-implemented method of claim 3, further comprising: while displaying the visual representation of the electrocardiogram, providing a control in the graphical user interface that allows a user to confirm or reject the particular segment of the electrocardiogram that the computing system automatically identified as corresponding to the T-wave of the patient's heartbeat; and receiving input that indicates user selection of the control and a confirmation or rejection of the particular segment of the electrocardiogram as corresponding to the true T-wave of the patient's heartbeat. ### Claim 6 (depends on 3) The computer-implemented method of claim 3, further comprising adjusting a boundary of the particular segment of the electrocardiogram that corresponds to the T-wave of the patient's heartbeat according to user input that specifies the adjustment. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, comprising: receiving raw data that characterizes the electrocardiogram of the patient; and processing the raw data to generate modified data that characterizes the electrocardiogram of the patient, wherein the computing system performs at least one of the analyzing step or the determining step with respect to the modified data. ### Claim 8 (depends on 7) The computer-implemented method of claim 7, wherein processing the raw data that characterizes the electrocardiogram of the patient comprises at least one of removing noise from the electrocardiogram or removing baseline wander from the electrocardiogram. ### Claim 9 (depends on 7) The computer-implemented method of claim 7, wherein processing the raw data that characterizes the electrocardiogram of the patient comprises using a signal averaging technique to determine a representative beat of the electrocardiogram based on data that characterizes multiple beats of the patient. ### Claim 10 (depends on 7) The computer-implemented method of claim 7, wherein processing the raw data that characterizes the electrocardiogram of the patient comprises: identifying one or more beats that are deemed outliers from one or more other beats represented in the electrocardiogram; and generating a representative beat of the electrocardiogram based on data that characterizes a plurality of beats represented in the electrocardiogram to the exclusion of the one or more beats that are deemed outliers, wherein the computing system performs at least one of the analyzing step or the determining step with respect to data that characterizes the representative beat. ### Claim 11 (depends on 7) The computer-implemented method of claim 7, wherein processing the raw data that characterizes the electrocardiogram of the patient comprises: identifying data recorded from one or more leads of a multi-lead electrocardiogram device; and removing the data recorded from the one or more leads of the multi-lead electrocardiogram device, wherein the computing system performs at least one of the analyzing step or the determining step based on a portion of data received by the computing system that excludes the data recorded from the one or more leads of the multi-lead electrocardiogram device. ### Claim 12 (depends on 1) The computer-implemented method of claim 1, wherein the one or more features of the T-wave comprise at least one of T-wave left slope, T-wave right slope, T-wave area, T-wave amplitude, time interval of t-peak to t-end, or T-wave center-of gravity. ### Claim 13 (depends on 1) The computer-implemented method of claim 1, further comprising: determining respective values of the one or more-features of the T-wave for a population of patients; performing statistical analysis of the respective values of the one or more features of the T-wave for the population of patients; and based on a result of the statistical analysis, correlating values of at least one feature of the T-wave with a patient condition. ### Claim 14 (depends on 13) The computer-implemented method of claim 13, wherein the patient condition is a cardiac disease. ### Claim 15 (depends on 13) The computer-implemented method of claim 13, wherein the patient condition is long-QT syndrome. ### Claim 16 (depends on 13) The computer-implemented method of claim 13, comprising: based on the result of the statistical analysis, correlating first values of at least one feature of the T-wave with congenital long-QT syndrome; and based on the result of the statistical analysis, correlating second values of at least one feature of the T-wave with acquired long-QT syndrome. ### Claim 17 A computing system, comprising: one or more processors; and one or more non-transitory computer-readable media having instructions stored thereon that, when executed by the one or more processors, cause performance of operations comprising: receiving, by the computing system, a set of data that characterizes an electrocardiogram of a patient; analyzing, by the computing system, the set of data that characterizes the electrocardiogram of the patient to identify a T-wave that occurs in the electrocardiogram; determining, by the computing system and in response to identifying a T-wave that occurs in the electrocardiogram, values of one or more features of the T-wave; and providing, by the computing system and to a client device of a user, information that identifies the values of the one or more features of the T-wave. ### Claim 18 (depends on 17) The computing system of claim 17, wherein analyzing the set of data that characterizes the electrocardiogram of the patient to identify the T-wave that occurs in the cardiogram comprises automatically identifying a particular segment of the electrocardiogram that corresponds to the T-wave, from among a plurality of segments of the electrocardiogram that correspond to different portions of the electrocardiogram that include the T-wave and at least one of a P-wave or a QRS-complex. ### Claim 19 One or more non-transitory computer-readable media having instructions stored thereon that, when executed by one or more processors, cause performance of operations comprising: receiving, by a computing system, a set of data that characterizes an electrocardiogram of a patient; analyzing, by the computing system, the set of data that characterizes the electrocardiogram of the patient to identify a T-wave that occurs in the electrocardiogram; determining, by the computing system and in response to identifying a T-wave that occurs in the electrocardiogram, values of one or more features of the T-wave; and providing, by the computing system and to a client device of a user, information that identifies the values of the one or more features of the T-wave. ### Claim 20 (depends on 19) The computer-readable media of claim 19, wherein analyzing the set of data that characterizes the electrocardiogram of the patient to identify the T-wave that occurs in the cardiogram comprises automatically identifying a particular segment of the electrocardiogram that corresponds to the T-wave, from among a plurality of segments of the electrocardiogram that correspond to different portions of the electrocardiogram that include the T-wave and at least one of a P-wave or a QRS-complex.