US 12,293,287 B2
Systems and methods of identity analysis of electrocardiograms
Conner Daniel Galloway, Sunnyvale, CA (US); Alexander Vainius Valys, Sunnyvale, CA (US); David E. Albert, Oklahoma City, OK (US); and Frank Losasso Petterson, Los Altos Hills, CA (US)
Assigned to ALIVECOR, INC., Mountain View, CA (US)
Filed by AliveCor, Inc.
Filed on Dec. 20, 2022, as Appl. No. 18/085,427.
Application 18/085,427 is a continuation of application No. 15/914,337, filed on Mar. 7, 2018, granted, now 11,562,222.
Claims priority of provisional application 62/468,303, filed on Mar. 7, 2017.
Prior Publication US 2023/0131876 A1, Apr. 27, 2023
Int. Cl. A61B 5/35 (2021.01); A61B 5/00 (2006.01); A61B 5/341 (2021.01); A61B 5/346 (2021.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G16H 40/63 (2018.01); G16H 50/20 (2018.01)
CPC G06N 3/08 (2013.01) [A61B 5/341 (2021.01); A61B 5/346 (2021.01); A61B 5/35 (2021.01); A61B 5/7221 (2013.01); G06N 3/04 (2013.01); G16H 40/63 (2018.01); G16H 50/20 (2018.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
processing training data comprising a set of training electrocardiograms (ECGs) for each of a plurality of subjects using a machine learning model to generate an output for each training ECG of each of the plurality of subjects, wherein for each of the plurality of subjects, the set of training ECGs for the subject is labeled with an identity of the subject;
training the machine learning model by comparing the output generated for each training ECG to a corresponding label of the training ECG to generate an identity model to identify ECGs of a first subject of the plurality of subjects;
inputting a first ECG into the identity model, the identity model to generate an output indicating whether the first ECG corresponds to the first subject; and
in response to the output indicating that the first ECG does not correspond to the first subject, determining based on the output, a condition that the first subject has or may develop.