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Computer vision method used for mental state auxiliary diagnosis

A technology of computer vision and auxiliary diagnosis, which is applied in the field of computer vision, can solve the problems of single evaluation method of patients' mental state and lack of objective evaluation, and achieve high flexibility, improve calculation accuracy, and improve diagnosis accuracy and efficiency.

Active Publication Date: 2017-10-13
HEFEI UNIV OF TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a computer vision method for auxiliary diagnosis of mental state, so as to solve the problems in the prior art that there is a single method for assessing the patient's mental state and lack of objective assessment.

Method used

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  • Computer vision method used for mental state auxiliary diagnosis
  • Computer vision method used for mental state auxiliary diagnosis
  • Computer vision method used for mental state auxiliary diagnosis

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Experimental program
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Embodiment Construction

[0031] Such as figure 1 As shown, a computer vision method for auxiliary diagnosis of mental state, the process is as follows:

[0032] (1), select 343 facial expression video sequences of 12 objects as the training database. These include deadpan videos and micro-expressive videos.

[0033] (2) Take out each frame of the video and convert it to gray scale, and cut out each frame of the image into a face image of equal size, which is used as a training sample first.

[0034] (3) Use a convolutional neural network for network training. This convolutional neural network includes a total of 4 convolutional layers and 4 pooling layers. The operations of convolution and pooling are performed alternately. First, the image is input to the first layer. In the convolution layer, it is known that there are multiple convolution kernels. After the convolution kernels are discretely convolved with the original image and a bias item is added, the extracted image features are obtained thro...

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Abstract

The invention discloses a computer vision method used for mental state auxiliary diagnosis. A face video of known micro-expressions is used as a training database, a convolutional neural network including a convolutional layer and a pooling layer is used to extract characteristics and merge image frames in the video, and then a stochastic gradient descent method is used for multi-iteration and update, to obtain an optimized network which is used as a network completing training. Then, a to-be-tested image is input to the network which completes training, and the network which completes training directly outputs a detection result that whether micro-expressions appear in the to-be-tested image, so as to provide reference for a doctor to diagnose mental state of a patient. When a person tries to depress real emotion of the person, the micro-expression would appear, detecting the micro-expression can reflect mental state of the person, so as to assist diagnosis of a doctor. The method improves accuracy and efficiency for a doctor to diagnose mental state of a patient to certain extent.

Description

technical field [0001] The invention relates to the field of computer vision methods, in particular to a computer vision method for auxiliary diagnosis of mental state. Background technique [0002] The role and purpose of diagnosing the patient's mental state is to diagnose the patient's mental behavioral state and whether it has changed. It is a very important part of the treatment process to improve the patient's mental behavioral state according to different mental states. During the course of treatment, patients will be affected by some stressors such as surgery, understanding of their own condition, etc., resulting in relatively severe psychological and physiological stress reactions. If these stress reactions are very strong, they may affect the endocrine system, nervous system, etc. The system has an impact, resulting in anxiety, depression and other psychology, and even interferes with the implementation and effect of diagnosis, surgery, and treatment. Therefore, i...

Claims

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Application Information

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IPC IPC(8): A61B5/16G06K9/62G06K9/00
CPCA61B5/165A61B5/7246G06V40/174G06F18/241G06F18/214
Inventor 詹曙李秋宇杨福猛余骏
Owner HEFEI UNIV OF TECH