Principal Investigator: Sohrob Saeb, PhD
Previous studies have shown that there is a strong relationship between the amount of social activity and the severity of depression. One main aspect of sociability is daily face-to-face communications. Traditionally, researchers and clinicians measure this factor based on the patients’ weekly or daily self-reports. The aim of this project is to develop machine learning algorithms that can passively infer the amount of face-to-face communication in depressed patients by analyzing the audio data collected from their smartphones, and thereby provide a momentary, objective assessment of the sociability factor in the context of their daily lives.
Supported by P20MH09031 (Principal Investigator: David C. Mohr, Ph.D.)