Depression is one of the most common mental disorders associated with suicide. Timely diagnosis and intervention of depression will improve life quality and reduce suicidal rate. Recent studies have shown that motor activities measured from wearable sensors may correlate with the depressive state. We developed a machine learning model to diagnose depression using motor activity data. Our model improves the base-line performance by 44%, suggesting the potential of artificial intelligence in mental health management.

Authors:

Ivy Xie (Presenter)
Newark Academy