We investigate how multipass emotion labelling protocols generate ecologically valid dynamic emotion transition labelling of affective touch behaviour (and other modalities).
We develop machine learning models of affect using touch and biometrics (such as EEG signal, skin conductance, heart rate, etc) to support affective interaction with companion robots for health applications.
Hop, run, skip, and jump your way to better health (and context-aware applications).
