Dependence of Brain-Computer Interface Control Training on Personality Traits.

Personality traits (PTs) are predictors of the success of control of brain-computer interfaces (BCIs); however, it is unknown how the PTs that are optimal for BCI control changes during training. The paper for the first time analyzes the correlations between PTs and the accuracy of the classification (AC) of brain states in imagining the movements of the hands, feet, and locomotion during 10-day training of ten volunteers in BCI control. In the first 3 days of training, the AC is higher for more stressed and anxious volunteers; in the last days, for calmer ones. In the middle of the training period, AC is higher in low-demonstrativeness persons, it is more pronounced when imagining foot movements. Correlations of low demonstrativeness, as well as of foresight and self-control with AC when imagining foot movements are revealed significantly more often than when imagining hand movements and locomotions. During almost the entire period of training, AC with locomotion imagination is higher in individualists. The results make it possible to propose individually-oriented recommendations for the use of BCI based on the imagination of movements for the rehabilitation of patients with motor disorders.

[Arm Motor Function Recovery during Rehabilitation with the Use of Hand Exoskeleton Controlled by Brain-Computer Interface: a Patient with Severe Brain Damage].

We studied the dynamics of motor function recovery in a patient with severe brain damage in the course of neurorehabilitation using hand exoskeleton controlled by brain-computer interface. For estimating the motor function of paretic arm, we used the biomechanical analysis of movements registered during the course of rehabilitation. After 15 weekly sessions of hand exoskeleton control, the following results were obtained: a) the velocity profile of goal-directed movements of paretic hand became bell-shaped, b) the patient began to extend and abduct the hand which was flexed and adducted in the beginning of rehabilitation, and c) the patient began to supinate the forearm which was pronated in the beginning of rehabilitation. The first result is an evidence of the general improvement of the quality of motor control, while the second and third results prove that the spasticity of paretic arm has decreased.

[Sources of electrophysiological and foci of hemodynamic brain activity most relevant for controlling a hybrid brain­Computer interface based on classification of EEG patterns and near-infrared spectrography signals during motor imagery].

The method is described for joint use of electroencephalography and near-infrared spectrography for location of sources of electrophysiological and focuses of hemodynamic brain activity during motor execution and imagination. The sources of electrophysiological and focuses of hemodynamic activity the most relevant for controlling the hybrid brain-computer interface based on motor imagery are revealed and discussed.

[Rehabilitation of post stroke patients using a bioengineering system "brain-computer interface + exoskeleton"]. / Reabilitatsiia bol'nykh, perenesshikh insul't, s pomoshch'iu bioinzhenernogo kompleksa "interfeis mozg-komp'iuter + ékzoskelet"

Objective. To investigate the possibility of using a bioengineering system, which includes an electroencephalograph and a personal computer with a software for synchronous data transmission, recognition and classification of EEG signals, development of directions for intended actions in real time in the combination with the hand exoskeleton (the bioengineering system "brain-computer interface + exoskeleton"), in motor rehabilitation of post stroke patients with paresis of the upper extremity. Material and methods. Brain-computer interface is a promising field of neurorehabilitation. Rehabilitation treatment, including 8-10 sessions, was conducted in 5 patients with paresis of the upper extremity. All patients had large MRI lesions in cortical/subcortical areas. Results. Positive changes in neurological status measured with the NIHSS, a significant increase in the volume and power of movements in the paretic hand, improvement of coordination and slight decrease in the level of spasticity were found after the treatment. There was an increase in daily activities measured with the Barthel index, mostly due to the improvement of fine motor skills. The level of disability assessed by the modified Rankin scale was changed significantly. Conclusion. The use of "brain-computer interface + exoskeleton" in the rehabilitation of post stroke patients with hand paresis provided positive results that would need to be verified in further studies.

[Localization of brain electrical activity sources and hemodynamic activity foci during motor imagery].

Studied are sources of brain activity contributing to EEG patterns which correspond to motor imagery. The accuracy of their classification determines the efficiency of brain-computer interface (BCI) allowing for controlling external technical devices directly by brain signals without involving muscle activity. Sources of brain activity are identified by Independent Component Analysis. Those independent components for which the BCI classification accuracy are at maximum are treated as relevant for motor imagery task. Two of the most relevant sources demonstrate strictly exposed event related desynchronization and synchronization of mu--rhythm during imagery of contra--and ipsilateral hands. These sources are localized by solving inverse EEG problem taking into account individual geometry of brain and its covers provided by anatomical MRI images. The sources are shown to be localized in BA 3A relating to proprioceptive sensitivity of the contralateral hand. Their positions are closed to foci of BOLD activity obtained by fMRI.

[Motor imagery and its practical application].

The mechanisms underlying the process of motor imagery are similar to the motor control mechanisms. It can be used for motor learning in patients with movement disorders. Motor imagery may be the only one method for recovery of motor function in patients with severe paresis. It was the prerequisite of increased scientist interest in motor imagery during last decade. Brain-computer interface technology can support the motor imagery trainings.

[Principles of neurorehabilitation based on brain-computer interface and biologically plausible control of the exoskeleton].

The paper examines neurophysiological basis for development and performance of brain-computer interface (BCI) that permits cerebral activity alone to control computers or other external technical devices. BCI based on the discrimination of EEG patterns related to an imagery of extremity movements is considered. The problem of BCI application to restoring of motor functions in patients with motor disabilities is discussed.

[Bayesian classifier for brain-computer interface based on mental representation of movements].

This paper proposes Bayesian approach to classification of EEG patterns on the basis of imaginary movements of extremities based on analysis ofcovariance matrices of native EEG recordings. An efficacy of a Brain-Computer Interface (BCI) based on the proposed classifier is evaluated. Bayesian classifier is shown to be competitive with the MCSP (Multiclass Common Spatial Patterns) classifier known from the literature as one of the efficient variant for BCI implementation. The influence of eye movement and blinking artifacts on the BCI performance is investigated. It is shown that the presence of such artifacts does not affect the classification accuracy.