Mobile devices equipped with rich sensors, such as smartphones, watches, or vehicles,
have been pervasively used all around the world. Their high penetration and powerful …

Mobile sensing systems have been widely used as a practical approach to collect
behavioral and health-related information from individuals and to provide timely intervention …

Background Research in psychology demonstrates a strong link between state affect
(moment-to-moment experiences of positive or negative emotionality) and trait affect (eg …

Background Respondent fatigue, also known as survey fatigue, is a common problem in the
collection of survey data. Factors that are known to influence respondent fatigue include …

Over the last decade, machine learning (ML) and deep learning (DL) algorithms have
significantly evolved and been employed in diverse applications, such as computer vision …

Mental health problems are a leading cause of disease burden and disability worldwide.
Social anxiety and depression are highly prevalent among college students. The current …

Background: Social anxiety is highly prevalent among college students. Current
methodologies for detecting symptoms are based on client self-report in traditional clinical …

On-body sensor-based human activity recognition (HAR) lags behind other fields because it
lacks large-scale, labeled datasets; this shortfall impedes progress in developing robust and …

With the widespread use of smartphones and wearable health sensors, a plethora of mobile
health (mHealth) applications to track well-being, run human behavioral studies, and clinical …

Mobile sensing is a ubiquitous and useful tool to make inferences about individuals' mental
health based on physiology and behavior patterns. Along with sensing features directly …