Background Smartphone-based digital phenotyping enables potentially clinically relevant
information to be collected as individuals go about their day. This could improve monitoring …

Background Smartphones and wearable biosensors can continuously and passively
measure aspects of behavior and physiology while also collecting data that require user …

Advances in wearable sensing and mobile computing have enabled the collection of health
and well-being data outside of traditional laboratory and hospital settings, paving the way for …

As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

Translating mental health recognition from clinical research into real-world application
requires extensive data, yet existing emotion datasets are impoverished in terms of daily …

The monitoring of depressed mood plays an important role as a diagnostic tool in
psychotherapy. An automated analysis of speech can provide a non-invasive measurement …

Real-world sound signals exhibit various aspects of grouping and profiling behaviors, such
as being recorded from identical sources, having similar environmental settings, or …

Recent years have seen a rapid increase in digital medicine research in an attempt to
transform traditional healthcare systems to their modern, intelligent, and versatile …

Affective computing (AC), as most other areas of computational research, has benefited
tremendously from advances in deep learning (DL). These advances have opened up new …

Digital health applications using Artificial Intelligence (AI) are a promising opportunity to
address the widening gap between available resources and mental health needs globally …