  Wearables equipped with pervasive sensors enable us to monitor physiological
and behavioral signals in our everyday life. We propose the WellAff system able
to recognize affective states for wellbeing support. It also includes health
care scenarios, in particular patients with chronic kidney disease (CKD)
suffering from bipolar disorders. For the need of a large-scale field study, we
revised over 50 off-the-shelf devices in terms of usefulness for emotion,
stress, meditation, sleep, and physical activity recognition and analysis.
Their usability directly comes from the types of sensors they possess as well
as the quality and availability of raw signals. We found there is no versatile
device suitable for all purposes. Using Empatica E4 and Samsung Galaxy Watch,
we have recorded physiological signals from 11 participants over many weeks.
The gathered data enabled us to train a classifier that accurately recognizes
strong affective states.
