• Enhancing cognition and motor rehabilitation using mixed reality (ECoReMiR)

    07/2017 – 06/2021

    Technological advancements based on mixed reality (MR) offer various challenges for research and medical treatment. The project focuses on two objectives related to healthy subjects and hemiparetic patients after stroke. First, we will test the hypothesis whether cognitive training using appropriately designed MR environment will enhance perceptual and cognitive performance in healthy subjects. This will be tested by computerized psychological experiments as well as by measuring event-related potentials or ERPs. Second, we will test the hypothesis whether experience with training in MR (in combination with motor-imagery based brain-computer interface developed by us) will enhance oscillatory sensory-motor rhythms. This will be tested by measuring subject’s EEG activity before and after each training session, clinical testing, as well as by the questionnaires aiming to learn about human factors including mental fatigue, motivation, irritation or sleepiness due to training. In both objectives, we will design and implement a set of testing procedures, carry out a battery of dedicated experiments, and critically evaluate the results with the goal to validate MR designs.
    Project is funded by the Slovak Research and Development Agency, APVV-16-0202.


  • Brain-computer interface with robot-assisted training for rehabilitation (BCI-RAS)

    10/2013 – 09/2017

    Within the project we developed an advanced intelligent system allowing the users to go through the process of self-controlled training of motor pathways. To meet this goal we combined the brain-computer interface (BCI) technology with a robotic arm system into a compact system that is primarily used as a robot-assisted neurorehabilitation tool. The BCI directly uses the signal of the brain electrical activity, which allows to users operating the environment without any muscular activation. As a part of this development we are addressed several critical issues ranging from signal acquisition and selection of the proper BCI paradigm to the evaluation of the affective state, cognitive load and system acceptability of the environment by users. We addressed these issues by using new signal processing and machine learning algorithms, training protocols and intelligent methods for the users' physiological state changes detection and monitoring. We used and validated the novel pre-training and model construction training protocols, including the mirror visual feedback and neurofeedback training. The system was tested in practice on selected patients with motor impairments caused by stroke, as well as on healthy volunteers.
    Project was funded by the Slovak Research and Development Agency, APVV-0668-12.


    Video: Training with RoboArm (for Slovak version click here)

  • Effects of sleep disturbances on day-time neurocognitive performance in patients with stroke (SleepCog)

    01/2013 – 06/2016

    Sleep deprivation, whether from disorder or lifestyle, whether acute or chronic, poses a significant risk in day-time cognitive performance, excessive somnolence, impaired attention or decreased level of motor abilities. Sleep deprivation is closely related to sleep fragmentation often associated with short several second long arousals. Although limited studies of partial sleep restriction and sleep fragmentation have revealed important sleep indices leading to cognitive deficits, a challenging question how a typical, good quality, structure of sleep should look like remains open. To improve these results the project investigated and evaluated a novel probabilistic sleep model. In a preliminary series of tests on healthy subjects it has been shown that the model contains significantly more objective information about external measures of the sleep quality than the traditional sleep staging. Patients with specific cerebral lesions were studied in the project. These patients are strongly vulnerable to sleep disturbances that often lead to deficits in their day-time cognitive and attentional performance.
    Project was funded by the Ministry of Health of the Slovak Republic, MZ 2013/46-SAV-6.