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Fatigue detection method and device based on face ppg signal

A fatigue detection and signal technology, which is applied in the field of fatigue detection based on face ppg signals, can solve problems such as lack of human physiological signals, and achieve the effect of improving fatigue detection accuracy and increasing correlation

Active Publication Date: 2022-03-18
ZHEJIANG LAB
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Problems solved by technology

However, this detection method is missing a key feature - human physiological signals

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  • Fatigue detection method and device based on face ppg signal
  • Fatigue detection method and device based on face ppg signal
  • Fatigue detection method and device based on face ppg signal

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[0037] In order to make the object, technical solution and technical effect of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0038] An intelligent fatigue detection method based on face ppg signals, different from existing fatigue detection methods, the method proposed by the present invention not only relies on traditional detection methods such as eye signals, facial features and head movements, but also The face ppg signal is used for classification detection. And this classification method is learned through deep learning. Different from the existing fatigue detection method, the method proposed in the present invention extracts the ppg signal of the face, extracts the feature of the signal block through the method of deep learning, and then weights it with the frequency of blinking, yawning, and bowing the head to confirm whether it is fatigue , to improve th...

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Abstract

The invention relates to the technical field of artificial intelligence algorithms, in particular to a face ppg signal-based fatigue detection method and device, and the method comprises the following steps: 1, collecting a video frame containing a face through a camera, and carrying out the face extraction; step 2, extracting face key points by using a key point detection method, and performing head motion detection; and step 3, preprocessing the extracted face, and obtaining a fatigue detection result through a fatigue classification model in combination with the detected head motion information. Aiming at the physiological signal change of the human face, a deep learning training mode is adopted, and the correlation between fatigue detection and the physiological signal change of the human face is increased, so that the fatigue detection precision based on the human face is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence algorithms, in particular to a fatigue detection method and device based on human face ppg signals. Background technique [0002] In the technology of face fatigue detection, the mainstream method is to first detect the face and key points of the face, and then track the key points, so as to extract facial features, eye signals, head movements, etc. Infer the fatigue state of the person. However, this detection method is missing a key feature-human physiological signals. From a medical point of view, the fatigue of the human body is also a manifestation of human physiological information. The physiological information reflected by different fatigue levels is different. Therefore, the present invention mainly extracts the physiological signals of the face and combines the head movement Information for fatigue detection, thereby improving the accuracy of fatigue detection through h...

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Application Information

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IPC IPC(8): G06V40/16G06V20/40G06V10/75G06V10/774G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/22G06F18/214
Inventor 应志文徐晓刚王军何鹏飞
Owner ZHEJIANG LAB
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