公开(公告)号：US20230389850A1

公开(公告)日：2023-12-07

申请号：US18249667

申请日：2021-10-21

Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA

Inventor： Niema M. PAHLEVAN ,  Rashid ALAVI DEHKORDI

IPC: A61B5/363 ,  A61B5/024 ,  A61B5/00 ,  G16H50/20

CPC classification number: A61B5/363 ,  A61B5/02438 ,  A61B5/7267 ,  G16H50/20

Abstract: The present application relates to using noninvasive techniques to determine whether a patient has experienced a cardiac event. The present application also relates to using noninvasive techniques to determine a size of a myocardial infarction experienced by a patient. In some embodiments, arterial pressure waveforms may be obtained, and from the arterial pressure waveform, a set of cardiac parameters may be extracted. The extracted cardiac parameters may be provided, as input, to the trained machine learning model, which may output a result indicating whether the patient experienced a cardiac event, a size of a myocardial infarction experience by a patient, or other information about the patient's cardiac health.

公开(公告)号：US20230420132A1

公开(公告)日：2023-12-28

申请号：US18251337

申请日：2021-11-10

Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA

Inventor： Niema M. PAHLEVAN ,  Rashid ALAVI DEHKORDI ,  Ray V. MATTHEWS

IPC: G16H50/20 ,  A61B5/352 ,  A61B5/00 ,  G16H50/70 ,  G16H50/30 ,  A61B5/021

CPC classification number: G16H50/20 ,  A61B5/352 ,  A61B5/7267 ,  G16H50/70 ,  G16H50/30 ,  A61B5/02108

Abstract: Some embodiments relate to non-invasive techniques for determining whether a patient has experienced heart failure. In some embodiments, a machine learning model may be trained to determine whether the patient has experienced heart failure using blood pressure waveforms and ECGs taken concurrently. Using the intrinsic frequency methodology and the cardiac triangle mapping methodology, features about the patient's cardiac cycle can be extracted and provided to the trained model as input.

公开(公告)号：US20230404488A1

公开(公告)日：2023-12-21

申请号：US18249952

申请日：2021-10-21

Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA

Inventor： Niema M. PAHLEVAN ,  Rashid ALAVI DEHKORDI

IPC: A61B5/00 ,  A61B5/0205 ,  G16H40/67 ,  G16H50/20

CPC classification number: A61B5/7267 ,  A61B5/7282 ,  A61B5/746 ,  A61B5/0205 ,  G16H40/67 ,  G16H50/20 ,  A61B5/14542

Abstract: The present application relates to using noninvasive techniques to determine whether a patient has experienced a cardiac event. The present application also relates to using noninvasive techniques to determine a size of a myocardial infarction experienced by a patient. In some embodiments, arterial pressure waveforms may be obtained, and from the arterial pressure waveform, a set of cardiac parameters may be extracted. The extracted cardiac parameters may be provided, as input, to the trained machine learning model, which may output a result indicating whether the patient experienced a cardiac event, a size of a myocardial infarction experience by a patient, or other information about the patient's cardiac health.