We present <i>MoA</i><sup>2</sup>, a context-aware smartphone app for the ambulatory assessment of mood, tiredness and stress level. In principle, it has two features: (1) mood assessment and (2) mood recognition. The mood assessment system combines benefits of state of the art approaches. The mood recognition is concluded by smartphone-based wearable… (More)
BACKGROUND Abnormalities in motor activity represent a central feature in major depressive disorder. However, measurement issues are poorly understood, limiting the use of objective measurement of motor activity for diagnostics and treatment monitoring. METHODS To improve measurement issues, especially sensor placement, analytic strategies and diurnal… (More)
In ambulatory assessment, subjects are monitored in everyday life. Though, it is difficult to unobtrusively assess information -- e.g. about their context and affective state -- which results in an increased burden for the subjects. This burden is caused by a complex self-report that they need to provide or by additional wearables that need to be carried.… (More)
The experience sampling method (ESM) is applied in ambulatory assessment to prompt subject self-reporting. Existing mobile apps provide time-triggered prompts but lack event-triggers. Hence, the sampling might not occur in moments that are of interest for a psychologist. To identify relevant sensor sources and contexts we conducted an online survey with… (More)
A physically active lifestyle has been related to positive health outcomes and high life expectancy, but the underlying psychological mechanisms maintaining physical activity are rarely investigated. Tremendous technological progress yielding sophisticated methodological approaches, i.e., ambulatory assessment, have recently enabled the study of these… (More)
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