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:
Jul. 16, 2024

Filed:

Nov. 16, 2023
Applicant:

Central China Normal University, Hubei, CN;

Inventors:

Liang Zhao, Hubei, CN;

Sannyuya Liu, Hubei, CN;

Zongkai Yang, Hubei, CN;

Xiaoliang Zhu, Hubei, CN;

Jianwen Sun, Hubei, CN;

Qing Li, Hubei, CN;

Zhicheng Dai, Hubei, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 8/14 (2006.01); A61B 5/00 (2006.01); A61B 5/0205 (2006.01); A61B 5/1171 (2016.01); A61B 5/16 (2006.01); G06N 3/0464 (2023.01); G06N 3/08 (2023.01); G06V 10/30 (2022.01); G06V 40/16 (2022.01); A61B 5/024 (2006.01); A61B 5/08 (2006.01);
U.S. Cl.
CPC ...
A61B 5/16 (2013.01); A61B 5/0205 (2013.01); A61B 5/1176 (2013.01); A61B 5/725 (2013.01); A61B 5/726 (2013.01); A61B 5/7264 (2013.01); G06N 3/0464 (2023.01); G06N 3/08 (2013.01); G06V 10/30 (2022.01); G06V 40/161 (2022.01); A61B 5/02427 (2013.01); A61B 5/0816 (2013.01); G06V 2201/03 (2022.01);
Abstract

The present disclosure provides a non-contact fatigue detection system and method based on rPPG. The system and method adopt multi-thread synchronous communication for real-time acquisition and processing of rPPG signal, enabling fatigue status detection. In this setup, the first thread handles real-time rPPG data capture, storage and concatenation, while the second thread conducts real-time analysis and fatigue detection of rPPG data. Through a combination of skin detection and LUV color space conversion, rPPG raw signal extraction is achieved, effectively eliminating interference from internal and external environmental facial noise; Subsequently, an adaptive multi-stage filtering process enhances the signal-to-noise ratio, and a multi-dimensional fusion CNN model ensures accurate detection of respiration and heart rate. The final step involves multi-channel data fusion of respiration and heartbeats, succeeding in not only learning person-independent features for fatigue detection but also detecting early fatigue with very high accuracy.


Find Patent Forward Citations

Loading…