Conference Paper

An Automatic Depression Recognition Method from Spontaneous Pronunciation Using Machine Learning

The rapidly growing number of depressed people increases the burden of clinical diagnosis. Due to the abnormal speech signal of depressed patients, automatic audio-based depression recognition has the potential to become a complementary method for …

A Novel Gait Analysis Method Based on The Pseudo-Velocity Model for Depression Detection

As the occurrence of depression in society becomes increasingly more common, it is an urgent task to find more objective and effective tools for real-time depression assessment. Gait analysis offers a new low-cost and contactless method for …

F-score Based EEG Channel Selection Methods for Emotion Recognition

Emotion, as an advanced function of the human brain, affects kinds of human behaviors. Electroencephalographs (EEG) are widely used in the field of emotion classification owing to their low cost and portability. In this work, we study the effects of …

Feature-level Fusion for Depression Recognition Based on fNIRS Data

Tens of millions of people suffer from depression worldwide. It is urgent to explore an effective method for diagnosing depression. This study developed a novel of multimodal feature fusion depression recognition method based on functional …