Invited Talks

Towards assessing and improving brain-computer interface user-training?
by Léa Pillette

Brain-computer interfaces (BCIs) introduce promising possibilities for interacting with digital applications solely through the analysis of brain activity, often acquired using electroencephalography (EEG). For instance, BCIs enable to control the direction of a character in a video game through the imagination of right- or left-hand movement to turn in the according direction. Despite promising applications for clinical and non-clinical applications, BCIs are not yet reliable enough to be used outside research laboratories. For instance, BCIs do not work for 10 to 30% of people. Several leads exist to improve the reliability of BCIs. One of them, is to improve the user training during which the users must learn to produce different patterns of brain activity that are recognizable by the computer. Indeed, the current user training does not fit the recommendations made in the field of education. The neurofeedback, the information regarding the users’ brain activity that is fed back to them, represents one main element of the user training. In this talk, I will present some previous work in which I investigated different neurofeedback and their influence on the usability of BCI user training and present some of my recent work at the intersection between virtual reality and BCIs.

AI-driven robot-assisted neurorehabilitation: from experimental trials towards a safe, reliable and effective human-robot interaction
by Stefano Mazzoleni

In last three decades a better understanding of neurophysiological mechanisms underlying upper limb movements and gait together with the investigation of neural substrates that underlie motor recovery after neurological impairments (such as stroke and spinal cord injury) has led to the development of robotic systems for rehabilitation that incorporate key elements of motor re-learning such as intensive training involving goal-oriented repeated movements.
Robotic devices for the upper limb and gait are increasingly used in neurorehabilitation: several studies have demonstrated the effectiveness of these devices in reducing motor impairments, but only a limited evidence has been found on the improvement of upper limb and gait function so far.
Other studies have investigated the effects of combined approaches that target muscle function (e.g., functional electrical stimulation), modulate neural activity (e.g., non-invasive brain stimulation) and enhance motivation (e.g., Virtual Reality) to enhance the benefits of robot-assisted training.
Recent developments in multimodal human-robot interaction and artificial intelligence are offering significant insights for improving safety, reliability and effectiveness of robot-assisted rehabilitation treatments, in particular in terms of control strategies and prediction of recovery trends (e.g., DSSs).
During the talk, these aspects will be critically reviewed and an overview of the status of robot-assisted therapies and combined treatments will be discussed together with an analysis of the rationale behind them. Recent applications of machine learning algorithms applied to cognitive rehabilitation for stroke patients during upper limb robot-assisted rehabilitation will be presented as well.
Finally, the scientific, technological, ethical, legal and social challenges of robot-assisted rehabilitation of the next decade will be presented.

Emotion Elicitation in Virtual Reality: Techniques and Applications
by Francesco Ferrise

Emotions play a fundamental role in our daily lives, shaping our choices, interpersonal relationships, and work. Scientific interest in this field has been steadily growing, with Virtual Reality (VR) emerging as a captivating medium for emotion generation. VR has the unique ability to immerse users in fully simulated environments, engaging all the senses and offering manipulative potential. It also provides a safe space for studying emotions in diverse contexts. This presentation will unveil some tricks to effectively evoke emotions in VR and uncover the promising applications awaiting further research.