Facial nerve paralysis rehabilitation detection system based on artificial intelligence

A facial nerve paralysis and artificial intelligence technology, applied in computer parts, medical automation diagnosis, medical informatics, etc., can solve the problems of lack of accuracy and efficiency, facial muscle analysis and feature extraction, and inability to describe facial muscle movement characteristics. , to achieve accurate and credible quantitative results, reduce power consumption, and achieve accurate 3D models.

Inactive Publication Date: 2021-03-26
黄振海
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, the methods for detecting facial nerve paralysis mostly use facial semantic segmentation and key point detection methods or analysis methods based on facial symmetry, but these methods have not been able to perform complete analysis and feature extraction on the characteristics of the patient's facial muscles, and lack accuracy. and efficiency
For example, the invention patent application document with the publication number CN111553250A proposes a method based on the analysis of the movement of each region of the face to realize facial paralysis detection. This method analyzes all facial key points under each action sequence, but the invention The above key points cannot describe the more detailed movement characteristics of facial muscles

Method used

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  • Facial nerve paralysis rehabilitation detection system based on artificial intelligence
  • Facial nerve paralysis rehabilitation detection system based on artificial intelligence
  • Facial nerve paralysis rehabilitation detection system based on artificial intelligence

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Experimental program
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Embodiment

[0037] The face of the patient is facing the camera, and the RGB image data of the patient's face is collected. In the face 3D model building module, the 3D model of the patient's face is obtained by using the patient's face image, that is, the 3D reconstruction of the face. There are many methods for face 3D reconstruction, such as PRNet, VRNet, 2DASL, etc. The embodiment uses the 2DASL method to obtain a 3DMM model of the face, that is, a 3D mesh of the face.

[0038]2DASL is a public 3D face reconstruction method. Its input is a face image and a special single-channel image. The pixel value of the single-channel image is 1 at the key points of the face, and -1 at the other positions; the output It is the parameters of the 3DMM model, and these parameters can be applied to the 3DMM model to obtain the face 3D mesh corresponding to the face image. The 3DMM model is a deformable 3D face 3D mesh, which adjusts the shape and expression of a face 3D mesh by changing some paramete...

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Abstract

The invention provides a facial nerve paralysis rehabilitation detection system based on artificial intelligence. The system comprises: a facial three-dimensional model construction module for constructing a three-dimensional model of the face of a patient according to an acquired facial image of the patient; a face three-dimensional model calibration module which is used for calibrating a three-dimensional model of the face of the patient based on the acquired face thermal imaging image of the patient; a three-dimensional model parameter prediction module which is used for predicting a next frame of three-dimensional model based on the patient face thermal imaging image and the parameters of the three-dimensional model; a facial muscle detection module which is used for obtaining the responsivity of facial muscles based on the obtained muscle current response sequence and obtaining the movement degree of the facial muscles based on the predicted three-dimensional model; and a rehabilitation degree detection module which is used for obtaining the rehabilitation degree of the patient based on the movement degree of the facial muscles and the responsivity of the facial muscles. The system can accurately quantify the rehabilitation degree of a patient and assist the patient in rehabilitation training.

Description

technical field [0001] The invention relates to the fields of medical treatment and artificial intelligence, in particular to an artificial intelligence-based facial nerve paralysis rehabilitation detection system. Background technique [0002] At present, the methods for detecting facial nerve paralysis mostly use facial semantic segmentation and key point detection methods or analysis methods based on facial symmetry, but these methods have not been able to perform complete analysis and feature extraction on the characteristics of the patient's facial muscles, and lack accuracy. and efficiency. For example, the invention patent application document with the publication number CN111553250A proposes a method based on the analysis of the movement of each region of the face to realize facial paralysis detection. This method analyzes all facial key points under each action sequence, but the invention The above key points do not describe the more detailed movement characteristi...

Claims

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Application Information

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IPC IPC(8): G16H50/20G06K9/00
CPCG16H50/20G06V20/64G06V40/171G06V40/161
Inventor 黄振海徐双双
Owner 黄振海
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