EEG

Study about the relevance of intensity and dose of NMES, and how these parameters can influence the recruitment of the sensorimotor pathways from the muscle to the brain.

Neurophysiology analysis of the EEG correlates elicited as the results of random and unexpected disturbances along different time points of somatosensory stimulation.

Study on how to combine neural correlates of natural movements and interaction error-related potentials (ErrP) to perform a 3D reaching task, focusing on the impact that such factors have on the evoked ErrP signatures and in their classification.

A hierarchical method to asynchronously discriminate two different grasps often used in daily life actions (palmar, pincer) from a combined set of motor execution and motor intention.

We demonstrate the existence of neural correlates for two types of elicited error potentials (errors at the beginning of a movement, and errors in the middle of a trajectory), and we are able to asynchronously detect them with high accuracies.

Application of transfer learning to asynchronously detect gradual errors from EEG signals during a continuous trajectory monitoring task and post-hoc analysis of the decoded neural correlates.

Experimental protocol that allows to train a decoder and detect errors in single trial using a sliding window.

Study of brain connectivity coherence patterns in EEG during continuous monitoring tasks as an alternative feature to be exploited by asynchronous ErrP detectors.

First study towards the detection of error-related potentials from EEG measurements during continuous trajectories performed by a virtual device.

An algorithm based on policy matching for inverse reinforcement learning to infer the user goal from brain signals. We present two cases of study involving a target reaching task in a grid world and using a real mobile robot.