An application of Brain Computer Interface in chronic stroke to improve arm reaching function exploiting Operant Learning strategy and Brain Plasticity

The paper deals with a specific kind of BCI application implemented with the aim of recovering the reaching ability of mild impaired stroke survivors. The overall idea is to take advantage of the plasticity of the brain to make the subject artificially learn alternative neural paths to control the arm movement again, bypassing the injured area thanks to a BCI system with an EEG-related force provided as a real-time feedback during the training period. Preliminary results have shown improvements in the kinematics of the upper limb motion of a first patient that performed this experimental rehabilitative program. Then, this BCI application is expected to enter soon the daily clinical practise as a useful tool besides the standard rehabilitation therapy

User adaptive BCIs: SSVEP and P300 based interfaces

PsychNology Journa

Spatial attention orienting to improve the efficacy of a brain-computer interface for communication

Brain-computer interfaces (BCIs) are systems which allow users to control devices, by means of their brain signals, without the involvement of the users' muscles. BCIs represent a potential solution for completely paralyzed patients who cannot communicate. We designed two new visual interfaces for controlling the movement of a virtual cursor on a monitor, implementing the cognitive principles of exogenous and endogenous attention orienting in a BCI driven by the P300. A group of patients with amyotrophic lateral sclerosis (ALS) and a matched group of healthy controls were tested. Results show that ALS patients can use both interfaces for controlling the cursor, although they reached a better performance with the endogenous attention orienting interface. We propose that the implementation of cognitive principles can play a key role in the development of new and more efficient BCIs