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:
Jan. 25, 2022

Filed:

May. 12, 2021
Applicant:

Orbsurgical Ltd., Calgary, CA;

Inventors:

Garnette Sutherland, Calgary, CA;

Amir Baghdadi, Calgary, CA;

Rahul Singh, Calgary, CA;

Hamidreza Hoshyarmanesh, Calgary, CA;

Sanju Lama, Calgary, CA;

Assignee:

OrbSurgical Ltd., Calgary, CA;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/70 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 70/20 (2018.01); G16H 40/40 (2018.01); G16H 40/20 (2018.01); G06K 19/07 (2006.01); G16H 15/00 (2018.01); G16H 20/40 (2018.01); H04L 29/06 (2006.01); A61B 34/30 (2016.01); A61B 17/28 (2006.01); A61B 90/00 (2016.01); A61B 90/98 (2016.01); G06N 20/00 (2019.01); G06F 3/14 (2006.01); A61B 17/00 (2006.01);
U.S. Cl.
CPC ...
G16H 50/70 (2018.01); A61B 17/28 (2013.01); A61B 34/30 (2016.02); A61B 90/37 (2016.02); A61B 90/98 (2016.02); G06K 19/0723 (2013.01); G06N 20/00 (2019.01); G16H 15/00 (2018.01); G16H 20/40 (2018.01); G16H 40/20 (2018.01); G16H 40/40 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 70/20 (2018.01); H04L 63/0421 (2013.01); A61B 2017/00057 (2013.01); A61B 2017/00075 (2013.01); A61B 2090/064 (2016.02); A61B 2090/372 (2016.02); G06F 3/14 (2013.01);
Abstract

Data is received that is generated by at least one sensor forming part of a surgical instrument. The sensor(s) on the surgical instrument can characterize use of the surgical instrument in relation to a patient. A force profile segmentation model can construct a force profile using the received data. The force profile includes a plurality of force patterns. The force profile segmentation model includes at least one first machine learning trained using historical surgical instrument usage data. In addition, a plurality of features are extracted from the received data. Thereafter, one or more attributes characterizing use of the surgical instrument are determined by a force profile pattern recognition model using the constructed force profile and the extracted features. The force profile pattern recognition model includes at least one second machine learning model. Data characterizing the determination can be provided (e.g., displayed to a surgeon, etc.).


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