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Deep Neural Networks for Depression Recognition Based on Facial Expressions -Deep Learning Project- Matlab

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Deep Neural Networks for Depression Recognition Based on Facial Expressions -Deep Learning Project- Matlab

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Deep Neural Networks for Depression Recognition Based on Facial Expressions -Deep Learning Project- Matlab

With the growth of the global population, the proportion of individuals with depression has rapidly increased; it is currently the most prevalent mental health disorder. Although existing studies on depression have mainly examined the several databases, which comprise facial images and videos of  subjects,

In this study, we first create a depression database by asking participants to perform five mood-elicitation tasks. After each task, their facial expressions are collected via a Kinect. In the depression database, the facial feature points (FFP) and facial action units (AU) are obtained.

We build a range of deep belief network (DBN) models based on FFPs and AUs to extract facial features from facial expressions, named 5DBN, AU-5DBN and 5DBN-AU. 

The experimental results show higher recognition performance in the database; thus, the proposed method is validated as effective in identifying depression.

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