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:
Feb. 28, 2023

Filed:

Jun. 01, 2020
Applicant:

Georgetown University, Washington, DC (US);

Inventors:

Gholam Motamedi, Washington, DC (US);

Ophir Frieder, Chevy Chase, MD (US);

Cristopher Flagg, Annandale, VA (US);

Jian-Young Wu, Gaithersburg, MD (US);

Assignee:

Georgetown University, Washington, DC (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/11 (2006.01); A61B 5/00 (2006.01); G06F 40/205 (2020.01);
U.S. Cl.
CPC ...
A61B 5/112 (2013.01); A61B 5/4842 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); A61B 5/742 (2013.01); G06F 40/205 (2020.01); A61B 2562/0219 (2013.01); A61B 2562/0247 (2013.01);
Abstract

A gait analysis system, which includes a neural network with a recurrent neural network layer and a fully connected layer, that receives sensor data indicative of an individual's gait and outputs an assessment regarding the individual's health. The neural network is trained using training data indicative of abnormal gaits and normal gaits. To analyze the training data and the sensor data, the recurrent neural network layer parses each piece of data into a series of windows and analyzes each window in series to generate a context vector characterizing each window and the previously analyzed windows. The fully connected layer, having been trained to differentiate between normal gaits and abnormal gaits based on context vectors characterizing the training data, is used to generate a final assessment characterizing the user gate as normal or abnormal using one or more of the context vectors characterizing the sensor data.


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