Electroencephalography-guided upper-limb hybrid robotic platform to modulate cortical excitability

This study present an intervention combining an electroencephalography-based brain computer interface with a hybrid robotic system for the modulation of the cortical excitability (plasticity). Plasticity is intended to be elicited through the association of the voluntary motor-related cortical processes with the hybrid assistance during the execution of reaching movement. The cortical excitability was assessed before and after the intervention measuring the peak-to-peak amplitude of the Motor Evoked Potentials (MEPs) induced through transcranial magnetic stimulation pulses. Five healthy subjects participated in the experiments. Results showed an overall and distributed increase in the cortical excitability as a result of the proposed intervention

Detecting and classifying three different hand movement types through electroencephalography recordings for neurorehabilitation

Brain–computer interfaces can be used for motor substitution and recovery; therefore, detection and classification of movement intention are crucial for optimal control. In this study, palmar, lateral and pinch grasps were differentiated from the idle state and classified from single-trial EEG using only information prior to the movement onset. Fourteen healthy subjects performed the three grasps 100 times, while EEG was recorded from 25 electrodes. Temporal and spectral features were extracted from each electrode, and feature reduction was performed using sequential forward selection (SFS) and principal component analysis (PCA). The detection problem was investigated as the ability to discriminate between movement preparation and the idle state. Furthermore, all task pairs and the three movements together were classified. The best detection performance across movements (79 ± 8 %) was obtained by combining temporal and spectral features. The best movement–movement discrimination was obtained using spectral features: 76 ± 9 % (2-class) and 63 ± 10 % (3-class). For movement detection and discrimination, the performance was similar across grasp types and task pairs; SFS outperformed PCA. The results show it is feasible to detect different grasps and classify the distinct movements using only information prior to the movement onset, which may enable brain–computer interface-based neurorehabilitation of upper limb function through Hebbian learning mechanisms

Brain-State Dependent Stimulation boosts functional recovery following stroke

This is the peer reviewed version of the following article: “Brain-State Dependent Stimulation boosts functional recovery following stroke”, which has been published in final form at http://dx.doi.org/10.1002/ana.25375. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived.Objective Adjuvant protocols devised to enhance motor recovery in subacute stroke patients have failed to show benefits with respect to classic therapeutic interventions. Here we evaluate the efficacy of a novel brain-state dependent intervention based on known mechanisms of memory and learning, that is integrated as part of the weekly rehabilitation program in subacute stroke patients. Methods Twenty-four hospitalized subacute stroke patients were randomly assigned to two intervention groups; 1. The associative group received thirty pairings of a peripheral electrical nerve stimulus (ES) such that the generated afferent volley arrived precisely during the most active phase of the motor cortex as patients attempted to perform a movement; 2. In the control group the ES intensity was too low to generate a stimulation of the nerve. Functional (including the lower extremity Fugl-Meyer assessment (LE-FM; primary outcome measure)) and neurophysiological (changes in motor evoked potentials (MEPs)) assessments were performed prior to and following the intervention period. Results The associative group significantly improved functional recovery with respect to the control group (median (interquartile range) LE-FM improvement: 6.5 (3.5-8.25) and 3 (0.75-3), respectively; p=0.029). Significant increases in MEP amplitude were seen following all sessions in the associative group only (p’s≤0.006). Interpretation This is the first evidence of a clinical effect of a neuromodulatory intervention in the subacute phase of stroke. This was evident with relatively few repetitions in comparison to available techniques, making it a clinically-viable approach. The results indicate the potential of the proposed neuromodulation system in daily clinical routine for stroke rehabilitation. This article is protected by copyright. All rights reserved.Kong Christian den Tiendes Fond (39/2016