Projects

Gabriela Sobolová

Project selection:

National projects

Causal analysis of measured signals and time series
Kauzálna analýza nameraných signálov a časových radov
Program: VEGA
Duration: 1.1.2022 – 31.12.2025
Project leader: RNDr. Krakovská Anna, CSc.
Annotation: The project is focused on the causal analysis of measured time series and signals. It builds on the previous results of the team, concerning the generalization of the Granger test and the design of new tests in the reconstructed state spaces. The aim of the project is the development of new methods for bivariate and multidimensional causal analysis. We will see the investigated time series and signals as one-dimensional manifestations of complex systems or subsystems. We will also extend the detection of causality to multivariate cases – dynamic networks with nodes characterized by time series. Such complex networks are common in the real world. Biomedical applications are among the best known. Brain activity, determined by multichannel electroencephalographic signals, is a crucial example. We want to help show that causality research is currently at a stage that allows for ambitious goals in the study of effective connectivity (i.e., directed interactions, not structural or functional links) in the brain.
Assessment and detection of mental fatigue in BCI-HMD
Hodnotenie a detekcia mentálnej únavy pri BCI-HMD
Program: Plán obnovy EÚ
Duration: 1.7.2024 – 31.12.2024
Project leader: Ing. Sobolová Gabriela, PhD.
Annotation: The continuous improvement of virtual reality (VR) technologies and the affordability of VR products, such as head-mounted display (HMD) VR goggles, have enabled the use of VR concepts in medicine, engineering, aerospace, education, entertainment, and other fields. With the wider use of VR, the issue of mental fatigue caused by prolonged use of VR devices is increasingly emerging. Many users of VR devices report suffering from various problems like eye pain, eyestrain, dizziness, and mental fatigue. Therefore, in recent years, researchers have paid considerable attention to the impact of VR technology on human health.At the Institute of Measurement, SAV, we have designed and developed a system for interfacing VR with a brain-computer interface (BCI), the so-called BCI-HMD concept, where the VR environment is implementing using HMDs. In the present study, Evaluation, and Detection of Mental Fatigue in BCI-HMD, we focus on detecting and evaluating mental fatigue in healthy subjects during prolonged use of a BCI-HMD environment.The aim is to analyze and determine electroencephalographic (EEG) biomarkers of mental fatigue occurring during the execution of repetitive mental imagery of hand movements in a virtual environment, called motor imagery, MI. We will focus on the quantitative evaluation of EEG data during the resting state with eyes open and eyes closed before and after long-term use of the BCI-VR system. The project includes a rigorous preprocessing and analysis of EEG data in MATLAB and Python programming environments, leading to the development of a software platform for further studies on detecting and monitoring mental fatigue.