Many technical communities are vigorously pursuing research topics that contribute to the
Internet of Things (IoT). Nowadays, as sensing, actuation, communication, and control …

Background Electronic mental health interventions for mood disorders have increased
rapidly over the past decade, most recently in the form of various systems and apps that are …

We present a mobile instrumentation toolkit, AWARE, an open-source effort to develop an
extensible and reusable platform for capturing, inferring, and generating context on mobile …

Background: Several studies have recently reported on the correlation between objective
behavioral features collected via mobile and wearable devices and depressive mood …

Essentially, the emerging term “Cyber–Physical Systems (CPS)” is an architectural paradigm
in which the pervasive sensing technologies represent a fundamental part. Originally …

Detecting when a household is occupied by its residents is fundamental to enable a number
of home automation applications. Current systems for occupancy detection usually require …

Background Uncertainty surrounds the ethical and legal implications of algorithmic and data-
driven technologies in the mental health context, including technologies characterized as …

Adverse and suboptimal health behaviors and habits are responsible for approximately 40%
of preventable deaths, in addition to their unfavorable effects on quality of life and …

Deep learning, a relatively new branch of machine learning, has been investigated for use in
a variety of biomedical applications. Deep learning algorithms have been used to analyze …

This paper articulates three main challenges for employing feedback control with humans in
the loop. They are:(i) the need for a comprehensive understanding of the complete spectrum …