  Mental health problems are on the rise globally and strain national health
systems worldwide. Mental disorders are closely associated with fear of stigma,
structural barriers such as financial burden, and lack of available services
and resources which often prohibit the delivery of frequent clinical advice and
monitoring. Technologies for mental well-being exhibit a range of attractive
properties, which facilitate the delivery of state-of-the-art clinical
monitoring. This review article provides an overview of traditional techniques
followed by their technological alternatives, sensing devices, behaviour
changing tools, and feedback interfaces. The challenges presented by these
technologies are then discussed with data collection, privacy, and battery life
being some of the key issues which need to be carefully considered for the
successful deployment of mental health toolkits. Finally, the opportunities
this growing research area presents are discussed including the use of portable
tangible interfaces combining sensing and feedback technologies. Capitalising
on the data these ubiquitous devices can record, state of the art machine
learning algorithms can lead to the development of robust clinical decision
support tools towards diagnosis and improvement of mental well-being delivery
in real-time.
