公开(公告)号：US20210204884A1

公开(公告)日：2021-07-08

申请号：US16733797

申请日：2020-01-03

Applicant: GE Precision Healthcare LLC

Inventor： Harihan Ravishankar ,  Rahul Venkataramani

IPC: A61B5/00 ,  A61B5/04 ,  G06N3/08 ,  G06N3/04 ,  G16H40/63 ,  G16H10/60 ,  G16H50/20

Abstract: Methods and systems are provided for automatically determining a phase shift and noise insensitive similarity metric for electrocardiogram (ECG) beats in a Holter monitor recording. In one embodiment, a deep neural network may be trained to map an ECG beat to a phase shift insensitive and noise insensitive feature space embedding using a training data triad, wherein the training data triad may be produced by a method comprising: selecting a first beat and a second beat recorded via one or more Holter monitors, determining a dynamic time warping (DTW) distance between the first beat and the second beat, setting a similarity label for the first beat and the second beat based on the DTW distance, and storing the first beat, the second beat, and the similarity label, in a location of non-transitory memory as an ECG training data triad.