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. 02, 2024

Filed:

May. 28, 2020
Applicant:

Toyota Jidosha Kabushiki Kaisha, Toyota, JP;

Inventors:

Nobuhisa Otsuki, Toyota, JP;

Issei Nakashima, Toyota, JP;

Manabu Yamamoto, Toyota, JP;

Hodaka Kito, Nagoya, JP;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/11 (2006.01); A61B 5/00 (2006.01); A61B 5/103 (2006.01); A61H 1/02 (2006.01); B25J 9/00 (2006.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 40/20 (2022.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01);
U.S. Cl.
CPC ...
A61B 5/1038 (2013.01); A61B 5/112 (2013.01); A61B 5/7267 (2013.01); A61B 5/742 (2013.01); A61H 1/0262 (2013.01); B25J 9/0006 (2013.01); G06F 18/2148 (2023.01); G06N 20/00 (2019.01); G06V 10/7747 (2022.01); G06V 10/776 (2022.01); G06V 40/25 (2022.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); A61B 2505/09 (2013.01); A61H 2201/1652 (2013.01); A61H 2201/5058 (2013.01); A61H 2205/10 (2013.01);
Abstract

The learning system includes a data generation unit configured to generate learning data based on rehabilitation data and a learning unit configured to perform machine learning using the learning data. A sensor is provided to detect a plurality of motion amounts in a walking motion of a trainee, and it is evaluated that, when one of the motion amounts matches one of abnormal walking criteria, that the walking motion is an abnormal walking pattern that meets the matched abnormal walking criterion. The data generation unit generates each of the pieces of rehabilitation data before and after a change in the results of evaluation of the abnormal walking pattern as learning data. The learning unit sequentially inputs each of the pieces of rehabilitation data as one data set, thereby performing machine learning.


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