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:
Oct. 17, 2023

Filed:

Sep. 29, 2020
Applicant:

Shenzhen University, Shenzhen, CN;

Inventors:

Kaishun Wu, Shenzhen, CN;

Yandao Huang, Shenzhen, CN;

Lin Chen, Shenzhen, CN;

Assignee:

SHENZHEN UNIVERSITY, Shenzhen, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06F 21/35 (2013.01); G01M 7/02 (2006.01); G06F 1/16 (2006.01); G06F 9/30 (2018.01); G06F 21/31 (2013.01); G06F 18/214 (2023.01); G06F 18/2413 (2023.01);
U.S. Cl.
CPC ...
G06F 21/35 (2013.01); G01M 7/025 (2013.01); G06F 1/163 (2013.01); G06F 9/3001 (2013.01); G06F 18/214 (2023.01); G06F 18/24147 (2023.01); G06F 21/316 (2013.01);
Abstract

A vibration signal-based smartwatch authentication method includes generating incremental vibration signals using a vibration motor in a smartwatch; performing frequency band-based hierarchical endpoint segmentation to obtain vibration signals at a plurality of frequency bands; extracting frequency-domain features for the vibration signals at the plurality of frequency bands; training a dynamic time warping model by taking the vibration signals at the plurality of frequency bands as a training data set, training a nearest neighbor model by taking the extracted frequency-domain features as training data; collecting to-be-authenticated vibration signals which are processed to serve as test data signals; discriminating similarities between the test data signals and corresponding training data signals through the dynamic time warping model, giving a classification result through the nearest neighbor model, performing weighted calculation on a discrimination result of the dynamic time warping model and a discrimination result of the nearest neighbor model to obtain an authentication result.


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