Background: With the growing ubiquity of smartphones and wearable devices, there is an
increased potential of collecting passive sensing data in mobile health. Passive data such …

Background Passive sensor data from mobile devices can shed light on daily activities,
social behavior, and maternal-child interactions to improve maternal and child health …

Psychological interventions delivered by non-specialist providers have shown mixed results
for treating maternal depression. mHealth solutions hold the possibility for unobtrusive …

Anxiety disorders are the most common class of psychiatric problems affecting both children
and adults. However, tools to effectively monitor and manage anxiety are lacking, and …

Collecting and analyzing data from sensors embedded in the context of daily life has been
widely employed for the monitoring of mental health. Variations in parameters such as …

Mental health disorders—including depression, anxiety, trauma-related, and psychotic
conditions—are pervasive and impairing, representing considerable challenges for both …

Objective To review published empirical literature on the use of smartphone-based passive
sensing for health and wellbeing. Material and methods A systematic review of the English …

Background: There is a high prevalence of untreated postpartum depression among
adolescent mothers with the greatest gap in services in low-and middle-income countries …

Digital psychiatry is a rapidly growing area of research. Mobile assessment, including
passive sensing, could improve research into human behavior and may afford opportunities …

Sensors in everyday devices, such as our phones, wearables, and computers, leave a
stream of digital traces. Personal sensing refers to collecting and analyzing data from …