The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 19, 2023

Filed:

Jul. 24, 2020
Applicant:

Zoll Medical Corporation, Chelmsford, MA (US);

Inventors:

Tsuyoshi Masuda, Pittsburgh, PA (US);

Kent Volosin, Mars, PA (US);

Assignee:

ZOLL Medical Corporation, Chelmsford, MA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); G06T 7/00 (2017.01); A61B 5/282 (2021.01); A61B 5/352 (2021.01); A61B 5/316 (2021.01); G06T 5/00 (2006.01); A61B 7/00 (2006.01); A61N 1/39 (2006.01); A61B 5/361 (2021.01); A61B 5/363 (2021.01); A61B 7/04 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 5/0006 (2013.01); A61B 5/282 (2021.01); A61B 5/316 (2021.01); A61B 5/352 (2021.01); A61B 5/4842 (2013.01); A61B 5/7264 (2013.01); A61B 7/00 (2013.01); G06T 5/002 (2013.01); A61B 5/361 (2021.01); A61B 5/363 (2021.01); A61B 7/04 (2013.01); A61B 2562/0219 (2013.01); A61N 1/3904 (2017.08); G06T 2207/20081 (2013.01); G06T 2207/30048 (2013.01);
Abstract

Systems and methods are provided for monitoring progression of a cardiac disease in a patient by providing cardio-vibrational image matrixes and/or ECG image matrices generated using sensor data supplied by a medical device. In some examples, cardio-vibrational image matrices and/or ECG image matrices are output as image files. In some implementations, systems and methods are provided for using such cardio-vibrational image matrices and/or an ECG image matrices, and/or other clinical information, using machine learning classifiers, to assess cardiac risk in a patient. In some implementations, systems and methods are provided for using cardio-vibrational image matrixes and/or ECG image matrices, and/or other clinical information for real-time analysis of cardiac risk.


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