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:
Nov. 14, 2023

Filed:

Aug. 08, 2022
Applicant:

Verb Surgical Inc., Santa Clara, CA (US);

Inventors:

Jagadish Venkataraman, Menlo Park, CA (US);

Dave Scott, Oakland, CA (US);

Eric Johnson, Pacific Grove, CA (US);

Assignee:

Verb Surgical Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 1/00 (2006.01); H04N 7/18 (2006.01); H04N 7/01 (2006.01); A61B 90/00 (2016.01); A61B 1/313 (2006.01); A61B 34/30 (2016.01); A61B 34/20 (2016.01); G06N 20/00 (2019.01); A61B 1/045 (2006.01); G06V 20/40 (2022.01); H04N 19/59 (2014.01); A61B 34/00 (2016.01);
U.S. Cl.
CPC ...
H04N 7/183 (2013.01); A61B 1/0004 (2022.02); A61B 1/00009 (2013.01); A61B 1/00045 (2013.01); A61B 1/00055 (2013.01); A61B 1/000096 (2022.02); A61B 1/045 (2013.01); A61B 1/3132 (2013.01); A61B 34/20 (2016.02); A61B 34/25 (2016.02); A61B 34/30 (2016.02); A61B 90/37 (2016.02); G06N 20/00 (2019.01); G06V 20/41 (2022.01); H04N 7/0117 (2013.01); H04N 19/59 (2014.11); A61B 2034/2055 (2016.02); A61B 2034/2057 (2016.02); A61B 2090/373 (2016.02); G06V 20/44 (2022.01);
Abstract

Embodiments described herein provide various examples of monitoring adverse events in the background while displaying a higher-resolution surgical video on a lower-resolution display device. In one aspect, a process for detecting adverse events during a surgical procedure can begin by receiving a surgical video. The process then displays a first portion of the video images of the surgical video on a screen to assist a surgeon performing the surgical procedure. While displaying the first portion of the video images, the process uses a set of deep-learning models to monitor a second portion of the video images not being displayed on the screen, wherein each deep-learning model is constructed to detect a given adverse event among a set of adverse events. In response to detecting an adverse event in the second portion of the video images, the process notifies the surgeon of the detected adverse event to prompt an appropriate action.


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