  From a computational viewpoint, emotions continue to be intriguingly hard to
understand. In research, direct, real-time inspection in realistic settings is
not possible. Discrete, indirect, post-hoc recordings are therefore the norm.
As a result, proper emotion assessment remains a problematic issue. The
Continuously Annotated Signals of Emotion (CASE) dataset provides a solution as
it focusses on real-time continuous annotation of emotions, as experienced by
the participants, while watching various videos. For this purpose, a novel,
intuitive joystick-based annotation interface was developed, that allowed for
simultaneous reporting of valence and arousal, that are instead often annotated
independently. In parallel, eight high quality, synchronized physiological
recordings (1000 Hz, 16-bit ADC) were made of ECG, BVP, EMG (3x), GSR (or EDA),
respiration and skin temperature. The dataset consists of the physiological and
annotation data from 30 participants, 15 male and 15 female, who watched
several validated video-stimuli. The validity of the emotion induction, as
exemplified by the annotation and physiological data, is also presented.
