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:
May. 16, 2023

Filed:

Nov. 22, 2022
Applicant:

MS Technologies, Rockville, MD (US);

Inventors:

Shuchuan Jack Cheng, Potomac, MD (US);

Yuan-Ming Fleming Lure, Potomac, MD (US);

Assignee:

MS TECHNOLOGIES, Rockville, MD (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G08B 21/00 (2006.01); G08B 21/04 (2006.01); G06N 20/00 (2019.01); G08B 27/00 (2006.01); G01S 13/62 (2006.01);
U.S. Cl.
CPC ...
G08B 21/043 (2013.01); G01S 13/62 (2013.01); G06N 20/00 (2019.01); G08B 27/005 (2013.01);
Abstract

A system and method for quantifying Alzheimer's disease (AD) risk using one or more interferometric micro-Doppler radars (IMDRs) and deep learning artificial intelligence to distinguish between cognitively unimpaired individuals and persons with AD based on gait analysis. The system utilizes IMDR to capture signals from both radial and transversal movement in three-dimensional space to further increase the accuracy for human gait estimation. New deep learning technologies are designed to complement traditional machine learning involving separate feature extraction followed-up with classification to process radar signature from different views including side, front, depth, limbs, and whole body where some motion patterns are not easily describable. The disclosed cross-talk deep model is the first to apply deep learning to learn IMDR signatures from two perpendicular directions jointly from both healthy and unhealthy individuals. Decision fusion is used to integrate classification results from feature-based classifier and deep learning AI to reach optimal decision.


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