Deep Learning Method for Micromotion Detection and Mental Health Disease Diagnosis

Over the past few decades, mental disorders (e.g., depressive and anxiety) have become a significant medical burden for people of all ages. According to the survey performed by the World Health Organization (WHO), at least one out of ten people in the world suffers from mental health diseases (i.e., mental disorders, neurological disorders and addition). Many factors, such as heredity, work pressure and aging, can attribute to these disorders and degradations. However, some of these mental health diseases are preventable and treatable. In this project, we aim to develop a software system, especially a mobile app, for the detection of mental health diseases, in particular depression for now. This app uses facial and audio pattern recognition techniques, GPS and gait to assess mental health conditions for patients which will help with early diagnosis of depression symptom and trigger clinical intervention if necessary.

Faculty Supervisor:

Jie Chen

Student:

Shiang Qi;Ben Flanders

Partner:

Hidaca Inc.

Discipline:

Engineering - computer / electrical

Sector:

Life sciences

University:

University of Alberta