A smartphone-based app detecting signs of depression based on the user’s behaviour has been developed by American engineers.
Called the LifeRhythm, the app gathers data from the phone’s various sensors including accelerometers, microphones and GPS to create a comprehensive picture of the user’s overall mental state.
The researchers believe that unlike psychiatric questionnaires the app provides objective data to evaluate mental health.
While accelerometers provide information about the level of the user’s physical activity, the amount of phone calls and messages he or she exchanges with friends and family provides an understanding of the quality of his or her social life. Microphones could be used to analyse the user’s speech to search for patterns typical for depressed people, such as slow tempo, the duration of pauses and volume. GPS reveals whether the user goes out or stays at home most of the time.
Developed as part of a $718,815 research project funded by the US National Science Foundation, the app is a brainchild of the University of Connecticut Professor Bing Wang, who hopes to run first trials on the university’s students soon.
"We will only focus on students living on campus," Wang said. "College students are more likely than others to be depressed. They're very young, away from home for the first time and there's all kinds of stresses."
Wang’s team hopes to recruit 120 students to take part in the experiment, expected to last for one semester.
Half of the group would have a prior history or exhibit current symptoms of depression and the other half would not.
For the second phase, the researchers plan to recruit 300 students. During this phase, the team will refine the data collection process.
Wang believes the technology could revolutionise the diagnosis of depression and enable the screening of whole populations. The major advantage of the app, according to Wang, is the fact that it is completely unobtrusive.
There are currently no known biological markers for depression, meaning that doctors have to rely on what the patient tells them. In the US, interview-based methods are used to assess mental well-being, focusing on mood, quality of sleep, energy levels, changes of appetite and suicidal thoughts. However, the approach requires patients to remember how they were feeling and allows them to adjust their answers based on what they anticipate the doctor wants to hear, thus preventing accurate diagnosis.