Physicians and researchers might be able to use patients' constant interaction with their smartphones to better diagnose depression, according to researchers at the University of Connecticut in Storrs, Conn.
Bing Wang, an associate professor of computer science and engineering at the University of Connecticut, has developed an app called LifeRhythm that gathers data from various sensors on a phone to help diagnose depression and other mental conditions. The app is funded by a $718,815 grant from the National Science Foundation Directorate for Computer and Information Sciences and Engineering, according to a UConn blog post.
Ms. Wang said in the blog post that there are signs of depression, including activity, energy levels and social interactions, which can be drawn from data on a smartphone's location sensor, motion sensor and microphone. Depression has been traditionally difficult to diagnose by standard clinical markers because providers only get a short glimpse into a patient's life, according to the blog post.
The app's developers hope to recruit 120 UConn students for the first phase of a trial of the app. The first trial will last one semester; the second trial will expand the subject base and refine the data collection process, according to the blog post. Ms. Wang said the app could also be a platform for communicating with patients for intervention methods.
"The intervention could be as simple as a text saying 'Go out for a walk,'" Ms. Wang said. "Intervention would be a very natural next step."