Affect recognition is an interdisciplinary research field bringing together researchers from
natural and social sciences. Affect recognition research aims to detect the affective state of a …

Affect recognition aims to detect a person's affective state based on observables, with the
goal to eg provide reasoning for decision making or support mental wellbeing. Recently …

Many people often experience difficulties in achieving behavioral goals related to
smartphone use. Most of prior studies approached this problem with various behavior …

There is a mental health crisis facing universities internationally. A growing body of
interdisciplinary research has successfully demonstrated that using sensor and interaction …

When modeling passive data to infer individual mental wellbeing, a common source of
ground truth is self-reports. But these tend to represent the psychological facet of mental …

In this paper, we demonstrate the existence of a bidirectional causal relationship between
smartphone application use and user emotions. In a two-week long in-the-wild study with 30 …

With the popularization of low-cost mobile and wearable sensors, several studies have used
them to track and analyze mental well-being, productivity, and behavioral patterns. However …

Deep learning has revolutionized predictive modeling in topics such as computer vision and
natural language processing but is not commonly applied to psychological data. In an effort …

Emotion has long been acknowledged as an important part of technology user experience.
More recently, research has begun to catalogue ways in which people use technology to …

With the advent of digital therapeutics (DTx), the development of software as a medical
device (SaMD) for mobile and wearable devices has gained significant attention in recent …