The prevalence of mobile phones and wearable devices enables the passive capturing and
modeling of human behavior at an unprecedented resolution and scale. Past research has …

Recent research has demonstrated the capability of behavior signals captured by
smartphones and wearables for longitudinal behavior modeling. However, there is a lack of …

The rate of depression in college students is rising, which is known to increase suicide risk,
lower academic performance and double the likelihood of dropping out of school. Existing …

We present a machine learning approach that uses data from smartphones and fitness
trackers of 138 college students to identify students that experienced depressive symptoms …

Depression is a common mood disorder that causes severe medical problems and interferes
negatively with daily life. Identifying human behavior patterns that are predictive or indicative …

Depression is a multifaceted illness with large interindividual variability in clinical response
to treatment. In the era of digital medicine and precision therapeutics, new personalized …

Remarkable advances in smartphone technology, especially in terms of passive sensing,
have enabled researchers to passively monitor user behavior in real-time and at a …

Experience sampling has long been the established method to sample people's mood in
order to assess their mental state. Smartphones start to be used as experience sampling …

Depression is a serious mental illness. The symptoms associated with depression are both
behavioral (in appetite, energy level, sleep) and cognitive (in interests, mood …

There are rising rates of depression on college campuses. Mental health services on our
campuses are working at full stretch. In response researchers have proposed using mobile …