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:
Apr. 16, 2024

Filed:

Aug. 06, 2021
Applicant:

Rehab2fit Technologies Inc., Longmont, CO (US);

Inventors:

Michael Bissonnette, Denver, CO (US);

Luis Berga, Austin, TX (US);

Steven Mason, Las Vegas, NV (US);

Philip Powers, Denver, CO (US);

James D. Steidl, Denver, CO (US);

Assignee:

Rehab2Fit Technologies Inc., Longmont, CO (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
A63B 24/00 (2006.01); A63B 21/00 (2006.01); A63B 21/002 (2006.01); A63B 21/005 (2006.01); A63B 21/22 (2006.01); A63B 22/00 (2006.01); A63B 22/06 (2006.01); A63B 22/18 (2006.01); A63B 23/035 (2006.01); A63B 23/04 (2006.01); A63B 23/08 (2006.01); A63B 23/12 (2006.01); A63B 71/06 (2006.01); G06N 20/00 (2019.01); G16H 20/30 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
A63B 24/0087 (2013.01); A63B 21/00076 (2013.01); A63B 21/4033 (2015.10); A63B 22/0605 (2013.01); A63B 23/03533 (2013.01); A63B 23/0355 (2013.01); A63B 23/0417 (2013.01); A63B 23/1209 (2013.01); A63B 24/0006 (2013.01); A63B 24/0062 (2013.01); A63B 71/0622 (2013.01); G06N 20/00 (2019.01); G16H 20/30 (2018.01); G16H 50/20 (2018.01); A63B 21/0023 (2013.01); A63B 21/0058 (2013.01); A63B 21/225 (2013.01); A63B 2022/0038 (2013.01); A63B 2022/0041 (2013.01); A63B 2022/0094 (2013.01); A63B 2022/0617 (2013.01); A63B 22/18 (2013.01); A63B 23/085 (2013.01); A63B 2024/0009 (2013.01); A63B 24/0059 (2013.01); A63B 2024/0065 (2013.01); A63B 2024/0093 (2013.01); A63B 2024/0096 (2013.01); A63B 2071/063 (2013.01); A63B 2071/0652 (2013.01); A63B 2071/0655 (2013.01); A63B 2071/0675 (2013.01); A63B 2071/068 (2013.01); A63B 2071/0683 (2013.01); A63B 2220/24 (2013.01); A63B 2220/30 (2013.01); A63B 2220/40 (2013.01); A63B 2220/51 (2013.01); A63B 2220/52 (2013.01); A63B 2220/805 (2013.01); A63B 2225/15 (2013.01); A63B 2225/20 (2013.01); A63B 2225/50 (2013.01); A63B 2230/06 (2013.01); A63B 2230/207 (2013.01); A63B 2230/30 (2013.01);
Abstract

A method is disclosed for using an artificial intelligence engine to modify resistance of one or more pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive one or more measurements as input, and outputting, based on the one or more measurements, a control instruction that causes the exercise device to modify the resistance of the one or more pedals. The method includes receiving the one or more measurements from a sensor associated with the one or more pedals of the exercise device, determining whether the one or more measurements satisfy a trigger condition, and responsive to determining that the one or more measurements satisfy the trigger condition, transmitting the control instruction to the exercise device.


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