The human brain has been an object of extensive investigation in different fields. While
several studies have focused on understanding the neural correlates of error processing …

Communication with a robot using brain activity from a human collaborator could provide a
direct and fast feedback loop that is easy and natural for the human, thereby enabling a wide …

We describe error-related potentials generated while a human user monitors the
performance of an external agent and discuss their use for a new type of brain-computer …

One of the fundamental challenges in brain-computer interfaces (BCIs) is to tune a brain
signal decoder to reliably detect a user's intention. While information about the decoder can …

Gesture-based recognition systems are susceptible to input recognition errors and user
errors, both of which negatively affect user experiences and can be frustrating to correct …

This paper presents a novel semi-autonomous navigation strategy designed for low
throughput interfaces. A mobile robot (eg intelligent wheelchair) proposes the most probable …

Reinforcement learning algorithms have been successfully applied in robotics to learn how
to solve tasks based on reward signals obtained during task execution. These reward …

The promise of Brain-Computer Interfaces (BCI) technology is to augment human
capabilities by enabling interaction with computers through a conscious and spontaneous …

Input recognition errors are common in gesture-and touch-based recognition systems, and
negatively affect user experience and performance. When errors occur, systems are …

Opportunistic sensing allows to efficiently collect information about the physical world and
the persons behaving in it. This may mainstream human context and activity recognition in …