Depression and bipolar disorder are mood disorders affecting millions of people worldwide
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …

Mental state assessment by analysing user-generated content is a field that has recently
attracted considerable attention. Today, many people are increasingly utilising online social …

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

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 …

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 …

Continuous wearable sensor data in high resolution contain physiological and behavioral
information that can be utilized to predict human health and wellbeing, establishing the …

Assessing performance in the workplace typically relies on subjective evaluations, such as,
peer ratings, supervisor ratings and self assessments, which are manual, burdensome and …

Reflecting on stress-related data is critical in addressing one's mental health. Personal
Informatics (PI) systems augmented by algorithms and sensors have become popular ways …

The transition from high school to college is a taxing time for young adults. New students
arriving on campus navigate a myriad of challenges centered around adapting to new living …

Resident physicians (residents) experiencing prolonged workplace stress are at risk of
develo** mental health symptoms. Creating novel, unobtrusive measures of resilience …