Program
Schedule
TBA
Invited Talks
AI personalised models based on subjective data
by Francesca Gasparini
by Francesca Gasparini
Nowadays wearable devices and environmental sensors allow us to easily collect data related to subjects' emotions and behaviour.
Advanced human system interfaces can benefit from this data, taking into account the emotions involved in the interaction.
The affective computing cycle that is the basis of these applications will be presented, highlighting its limits and potentials.
The same kind of data can be extremely useful also in applications that do not imply active subject interactions, such as remote monitoring especially in case of frail people.
The role of data quality, inter and intra subject variability will be discussed to provide hints to evaluate the reliability of personalised AI models.
Case studies will be re presented and critically discussed.
The role of physiological signals in human-machine interaction
by Angelika Peer
by Angelika Peer
Novel human-machine interfaces not only consider verbal and touch interactions or interactions via gestures and facial expressions, but also exploit physiological signals. Physiological signals combined with contextual information, allow not only for the prediction of intentions related to what a person may intend to do, but also the how. In this talk, I will describe how physiological signals like heart rate, respiration rate, skin conductance, and electroencephalogram can be exploited to build brain and body computer interfaces and how recognized intentions and emotions can be mapped to real world adaptive actions.