US 12,451,258 B2
Movement feedback for orthopedic patient
Dalton Winterbach, Grand Rapids, MI (US); Matt Vanderpool, Warsaw, IN (US); Kelli Palm, Grand Rapids, MI (US); Jenny Wang, Lake Oswego, OR (US); John Kotwick, Grand Rapids, MI (US); Vinay Tikka, Winona Lake, IN (US); Ted Spooner, Grand Rapids, MI (US); and Dugal James, Bendigo (AU)
Assigned to Zimmer US, Inc., Warsaw, IN (US)
Filed by Zimmer US, Inc., Warsaw, IN (US)
Filed on Mar. 13, 2024, as Appl. No. 18/603,842.
Application 18/603,842 is a division of application No. 16/851,606, filed on Apr. 17, 2020, abandoned.
Claims priority of provisional application 62/966,438, filed on Jan. 27, 2020.
Claims priority of provisional application 62/853,425, filed on May 28, 2019.
Claims priority of provisional application 62/836,338, filed on Apr. 19, 2019.
Prior Publication US 2024/0212866 A1, Jun. 27, 2024
Int. Cl. G16H 50/70 (2018.01); A61B 5/00 (2006.01); A61B 5/024 (2006.01); A61B 5/11 (2006.01); G06T 7/00 (2017.01); G06T 7/246 (2017.01); G06V 40/16 (2022.01); G06V 40/20 (2022.01); G16H 15/00 (2018.01); G16H 20/30 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01)
CPC G16H 50/70 (2018.01) [A61B 5/024 (2013.01); A61B 5/112 (2013.01); A61B 5/1121 (2013.01); A61B 5/1124 (2013.01); A61B 5/1127 (2013.01); A61B 5/1128 (2013.01); A61B 5/4824 (2013.01); A61B 5/6822 (2013.01); A61B 5/7405 (2013.01); A61B 5/744 (2013.01); A61B 5/7445 (2013.01); A61B 5/7455 (2013.01); A61B 5/746 (2013.01); G06T 7/0014 (2013.01); G06T 7/251 (2017.01); G06V 40/174 (2022.01); G06V 40/25 (2022.01); G16H 15/00 (2018.01); G16H 20/30 (2018.01); G16H 40/67 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 2562/0219 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/30196 (2013.01); G06T 2207/30204 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method comprising:
capturing pre-operative video of a patient;
identifying, using processing circuitry, a pre-operative gait of the patient based on walking movement performed by the patient in the pre-operative video;
determining a gait type using a machine learning model, the machine learning model trained using gait patterns from a plurality of patients having a plurality of co-morbidities and a plurality of gait types;
generating, using the processing circuitry, an orthopedic intervention plan for the patient based on the gait type; and
outputting information indicative of the orthopedic intervention plan for display, wherein outputting the information indicative of the orthopedic intervention plan for display includes outputting a set of instant loading data on a knee of the patient at corresponding stages of the identified pre-operative gait.