The Experience Sampling Method (ESM) is used by scientists from various disciplines to
gather insights into the intra-psychic elements of human life. Researchers have used the …

Rapidly maturing technologies for sensing and activity recognition can provide
unprecedented access to the complex structure daily activity and interaction, promising new …

Background Supporting mental health and wellness is of increasing interest due to a
growing recognition of the prevalence and burden of mental health issues. Mood is a central …

In this research, we take an HCI perspective on the opportunities provided by AI techniques
in medical imaging, focusing on workflow efficiency and quality, preventing errors and …

Abstract The Experience Sampling Method is widely used to collect human labelled data in
the wild. Using this methodology, study participants repeatedly answer a set of questions …

Active and passive sensing technologies are providing powerful mechanisms to track,
model, and understand a range of health behaviors and well-being states. Despite yielding …

Engagement has been recognized as one of the most important factors of learning and
achievement in academic settings. Research on engagement has been gearing toward a …

A popular methodology used for in situ observations is the Experience Sampling Method
(ESM), in which participants intermittently answer short questionnaires. We analyse a set of …

Self-tracking practices enable users to record and analyze their personal data. In recent
years, non-digital forms of manual self-tracking, such as bullet journaling, have gained …

Ecological momentary assessment (EMA) is an approach to collect self-reported data
repeatedly on mobile devices in natural settings. EMAs allow for temporally dense …