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:
Jul. 28, 2026

Filed:

Feb. 04, 2020
Applicants:

Smith & Nephew, Inc., Memphis, TN (US);

Smith & Nephew Asia Pacific Pte. Limited, Singapore, SG;

Smith & Nephew Orthopaedics Ag, Zug, CH;

Inventors:

Shawn P. Mcguan, San Clemente, CA (US);

Branislav Jaramaz, Pittsburgh, PA (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
A61B 34/10 (2016.01); A61B 17/00 (2006.01); A61B 17/17 (2006.01); A61B 34/00 (2016.01); A61B 90/00 (2016.01); A61F 2/46 (2006.01); G02B 27/01 (2006.01); G06N 3/08 (2023.01); G06N 5/046 (2023.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G09B 5/02 (2006.01); G09B 19/00 (2006.01); G09B 19/24 (2006.01); G16H 10/60 (2018.01); G16H 20/40 (2018.01); G16H 30/40 (2018.01); G16H 40/63 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); A61B 17/15 (2006.01); A61B 34/20 (2016.01); A61B 34/30 (2016.01); A61B 90/50 (2016.01); A61B 90/96 (2016.01); A61F 2/30 (2006.01);
U.S. Cl.
CPC ...
A61B 34/10 (2016.02); A61B 17/1764 (2013.01); A61B 34/25 (2016.02); A61B 90/361 (2016.02); A61B 90/37 (2016.02); A61B 90/39 (2016.02); A61F 2/461 (2013.01); G02B 27/0172 (2013.01); G06N 3/08 (2013.01); G06N 5/046 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G09B 5/02 (2013.01); G09B 19/003 (2013.01); G09B 19/24 (2013.01); G16H 10/60 (2018.01); G16H 20/40 (2018.01); G16H 30/40 (2018.01); G16H 40/63 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); A61B 2017/00199 (2013.01); A61B 2017/00526 (2013.01); A61B 17/15 (2013.01); A61B 17/17 (2013.01); A61B 2034/102 (2016.02); A61B 2034/104 (2016.02); A61B 2034/105 (2016.02); A61B 2034/107 (2016.02); A61B 2034/108 (2016.02); A61B 34/20 (2016.02); A61B 2034/2048 (2016.02); A61B 2034/2057 (2016.02); A61B 2034/2063 (2016.02); A61B 2034/2065 (2016.02); A61B 2034/2068 (2016.02); A61B 2034/2072 (2016.02); A61B 2034/2074 (2016.02); A61B 2034/252 (2016.02); A61B 2034/254 (2016.02); A61B 2034/256 (2016.02); A61B 2034/258 (2016.02); A61B 34/30 (2016.02); A61B 2090/363 (2016.02); A61B 2090/365 (2016.02); A61B 2090/371 (2016.02); A61B 2090/376 (2016.02); A61B 2090/3916 (2016.02); A61B 2090/502 (2016.02); A61B 90/96 (2016.02); A61F 2002/30952 (2013.01); A61F 2002/4633 (2013.01); G02B 2027/0138 (2013.01);
Abstract

Methods, non-transitory computer readable media, and surgical computing devices are illustrated that improve robotic surgical systems. With this technology, one or more machine learning models are trained based on historical state data obtained for a computer-assisted surgical system (CASS) at each of a plurality of time periods during a plurality of historical knee arthroplasty surgical procedures. One or more of the machine learning models are applied to initial state data for a current knee arthroplasty surgical procedure to generate robotic commands required to achieve one or more future states of the CASS. The initial state data comprises a surgical plan. One or more surgical tools of the CASS are then manipulated based on the robotic commands to achieve the one or more future states of the CASS and thereby carry out at least a portion of the surgical plan.


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