The list of national projects SAS
Institute of Measurement Science
EEG data analysis by blind source separation methods
Analýza EEG signálu pomocou metód hľadania skrytých zdrojov
| Duration: |
1.9.2024 - 31.8.2026 |
| Program: |
|
| Project leader: |
Mgr. Rošťáková Zuzana PhD. |
| Annotation: | Blind source separation (BSS) approaches are unsupervised machine learning methods focused on the detection of hidden, directly unobservable (latent) structure of real-world data. They play a crucial role in image processing, medical imaging, and music. The proposed project focuses mainly on human electroencephalogram (EEG), for which BSS is beneficial when detecting the narrowband brain oscillations representing brain processes either in health or disease. Two-dimensional BSS methods like principal or independent component analysis are easily applicable and understandable for a broader medical and neurophysiological community. However, the estimated latent component properties are usually incompatible with the real electrophysiological signal character. Consequently, they miss their neurophysiological interpretation. Tensor decomposition is a complex but more flexible mathematical procedure that allows adapting the model structure and constraints to the solution to mimic real-world signal characteristics. The proposed project focuses on tensor decomposition as a tool for i) EEG preprocessing, artefact detection and removal, ii) EEG latent structure analysis using a nonnegative tensor decomposition with block structure allowing to model various relationships between latent components, and iii) post-decomposition analysis of latent component dynamic properties. Obtaining comprehensive information about EEG latent structure and developing novel, user-friendly algorithms is crucial for better understanding brain processes and new methods for treating neurophysiological diseases and disorders. |
Automatic data evaluation tool from the longitudinal quantitative MRI studies of articular cartilage
Automatický softvérový nástroj na výhodnocovanie kvantitatívnych MRI štúdií artikulárných chrupaviek v čase
| Duration: |
1.7.2022 - 30.6.2026 |
| Program: |
SRDA |
| Project leader: |
Ing. Dr. Szomolányi Pavol (PhD.) |
| Annotation: | The aim of the project is to design a comprehensive tool for automatic evaluation of human articular cartilage data from quantitative MRI. Data obtained from the Osteoarthritis Initiative database, and measured at Institute of Measurement Science and Medical University of Vienna will be segmented using an automated segmentation tool based on convolutional neural networks. The annotated data will then be registered on quantitative MRI data that will be available from the database (T2 and T1rho mapping, gagCEST, sodium MR) using automated or semiautomated tools developed within this project. The data obtained will be evaluated at multiple time points according to MR measurements that will be available. In addition to quantitative MR data, this will include volumetric data, cartilage thickness, and texture analysis of quantitative maps. Patient evaluation will be based on risk factor groups (transverse ligament rupture, meniscus rupture and menisectomy). The expected number of patients is approximately 4000 divided into individual groups in the ratio 40/30/30. The output of the project will be a compiled version of an automatic cartilage evaluation tool that will be available in a public source (such as website of Institute of Measurement). |
Trustworthy human–robot and therapist–patient interaction in virtual reality
Dôveryhodná interakcia človek–robot a terapeut–pacient vo virtuálnej realite
| Duration: |
1.7.2022 - 30.6.2026 |
| Program: |
SRDA |
| Project leader: |
Ing. Mgr. Rosipal Roman DrSc. |
| Annotation: | We aim to study specific forms of social interaction using state-of-the-art technology - virtual reality (VR) which is
motivated by its known benefits. The project has two main parts, human–robot interaction (HRI) and therapist–
patient interaction (TPI). The interactions are enabled using head-mounted displays and controllers allowing the
human to act in VR. We propose two research avenues going beyond the state-of-the-art in respective contexts. In
HRI, we will develop scenarios allowing the humanoid robot to learn, understand and imitate human motor actions
using flexible feedback. Next, we develop scenarios for testing and validating human trust in robot behavior based
on multimodal signals. We will also investigate physical interaction with a humanoid robot NICO. In TPI with stroke
patients, we develop a series of VR-based occupational therapy procedures for motor and cognitive impairment
neurorehabilitation using an active and passive brain-computer interface, and we will validate these procedures.
We expect observations from HRI experiments to be exploited in TPI. The proposed project is highly
multidisciplinary, combining knowledge and research methods from psychology, social cognition, robotics, machine
learning and neuroscience. We expect to identify features and mechanisms leading to trustworthy processes with a
human in the loop, as a precondition of success, be it a collaborative task or treatment in VR. |
Dual‑tuned ¹H/¹⁹F RF coil for preclinical MRI
Duálne ladená ¹H/¹⁹F RF cievka pre predklinické MRI
| Duration: |
1.9.2026 - 31.8.2030 |
| Program: |
SRDA |
| Project leader: |
Ing. Gogola Daniel PhD. |
| Annotation: | The project focuses on the design, optimization, and experimental verification of a dual‑tuned ¹H/¹⁹F radiofrequency (RF) coil intended for preclinical MRI. Combined ¹H/¹⁹F imaging represents a promising technology enabling simultaneous
anatomical (¹H) and quantitative functional measurements (¹⁹F), particularly in studies involving the biodistribution of
fluorinated compounds, cell‑tracking applications, inflammatory processes, and functional lung imaging. The absence of endogenous ¹⁹F signal in biological tissues allows absolute quantification without background reconstruction, which increases the accuracy and interpretability of measurements. Despite its potential, only a limited number of solutions optimized for small‑animal imaging currently exist, and available systems often do not achieve the required sensitivity and B₁ homogeneity for fluorine MRI.
The project includes the development of detailed FEM/FDTD models of various coil geometries, their optimization for both
resonance frequencies, and the subsequent construction of a physical prototype. The experimental phase will involve
S‑parameter and Q‑factor measurements, B₁ field mapping, and testing of tuning stability. The functional performance of
the coil will be evaluated using phantoms with defined fluorine content and, in the final stage, through preclinical measurements in small animals. The project also includes the development of a software tool that enables the calculation
and optimization of RF coil parameters for different dimensions and frequencies.
The outcome of the project will be an experimentally validated dual‑tuned ¹H/¹⁹F RF coil and a complete methodology for
its design, applicable in preclinical research, pharmacological studies, and the development of fluorinated markers. The
project will contribute to the advancement of preclinical MRI technologies in Slovakia and create a foundation for further
interdisciplinary applications in biomedical imaging. |
Identification of stress-induced alterations in expression of NRF2 target genes in rat models of prehypertension: the effect of comorbid hypertriglyceridemia and dimethyl fumarate treatment
Identifikácia stresom vyvolaných zmien v expresii cieľových génov NRF2 v potkaních modeloch prehypertenzie: vplyv komorbidnej hypertriglyceridémie a liečby dimetylfumarátom
| Duration: |
1.7.2023 - 30.6.2027 |
| Program: |
SRDA |
| Project leader: |
Ing. Maňka Ján CSc. |
| Annotation: | The nuclear transcription factor erythroid 2-related factor 2 (NRF2) is a key molecular link between several non-
communicable diseases, as it regulates the expression of approximately 250 target genes, including those involved
in maintenance of redox balance, the development of metabolic disorders, cardiovascular and liver diseases, as
well as in immune responses. Borderline elevated blood pressure (prehypertension) is a common cardiovascular
disorder in humans, and elevated blood pressure has been found to be positively correlated with triglyceride levels.
In addition, chronic stress is an etiological factor in the development of non-communicable diseases, including
elevated blood pressure and hypertriglyceridemia (HTG). In experimental studies, borderline hypertensive rats
(BHR) and hypertriglyceridemic rats (HTGR) are suitable models of prehypertension without and with comorbid
hypertriglyceridemia. These models are relevant for investigating the effects of stress as well as for investigating
the role of changes in expression of NRF2 target genes in the development of hypertension associated with
metabolic diseases. To understand better the role of NFR2 as well as the impact of chronic social stress on the
mentioned diseased states, the aims of this project are: 1) to identify differences in expression of NRF2 target
genes in two experimental models of prehypertension - without (in BHR) and with (in HTGR) comorbid HTG - in
control conditions and during chronic social stress, 2) to determine if NRF2 activator dimethyl fumarate can reduce
stress-induced pathologies in prehypertensive rats, especially in those with comorbid HTG, and 3) to specify a set
of suitable whole blood RNA biomarkers for evaluation of changes in NRF2 target genes in prehypertension and
HTG and those genes altered by chronic social stress. |
Innovations in the Transfer Entropy Method: Implementing Alternative Entropic Measures for More Robust Causal Inference
Inovácie v metóde prenosovej entropie: Implementácia alternatívnych entropických mier pre robustnejšiu kauzálnu inferenciu
| Duration: |
1.7.2025 - 30.6.2026 |
| Program: |
|
| Project leader: |
Mgr. Mezeiová Kristína PhD. |
| Annotation: | The aim of the project is to explore the use of alternative entropy measures, such as Rényi entropy, Tsallis entropy, and permutation entropy, in the transfer entropy method to enhance the accuracy, robustness, and computational efficiency of causal analysis in complex systems. The project will focus on the software implementation of appropriately modified causal algorithms, their testing on synthetic and real-world data, and the identification of areas where the proposed innovations provide significant advantages. |
Innovative approaches to uncovering relationships and interactions within multivariate time measurements
Inovatívne prístupy k odhaľovaniu vzťahov a interakcií v rámci multivariátnych časových meraní
| Duration: |
1.1.2026 - 31.12.2029 |
| Program: |
VEGA |
| Project leader: |
RNDr. Krakovská Anna CSc. |
| Annotation: | The project focuses on developing and applying methods for analyzing relationships between simultaneously
measured processes. After experience with bivariate causal detection, we now target multivariate cases, often
modelled as dynamical networks with time series at their nodes.
We investigate Granger causality for autoregressive (AR) models and search for connections in reconstructed
state spaces when deterministic dynamics prevail. Transfer entropy, a strong representative of causal methods,
will also be explored, including proposed modifications using alternative entropy measures. We also examine the
potential of machine learning methods in causal analysis.
Expected outcomes include computational tools for more reliable detection of causal links and synchronisation,
and for improved modelling, forecasting, and classification of the studied processes.
The proposed methods will be validated on simulated data and applied to real measurements, such as effective
brain connectivity and climate observations. |
Cooperative AI-enhanced BCI-HMD rehabilitation for post-stroke recovery
Kooperatívna AI BCI-HMD rehabilitácia pre pacientov po cievnej mozgovej príhode
| Duration: |
1.9.2026 - 31.8.2030 |
| Program: |
SRDA |
| Project leader: |
Ing. Mgr. Rosipal Roman DrSc. |
| Annotation: | This project aims to advance post-stroke neurorehabilitation through the development of an artificial intelligence (AI)-enhanced, collaborative brain–computer interface (BCI) system integrated with immersive head-mounted display (HMD)–based virtual reality (VR). AI serves as a central enabling component, supporting adaptive neural decoding, cognitive-state monitoring, and data-driven optimization of rehabilitation protocols. A key focus is on the creation of
cooperative, shared-action rehabilitation environments, in which the patient and therapist jointly perform the same task in real time. This combination of AI-driven adaptation and shared-action cooperation moves beyond isolated task execution toward socially interactive, coordinated motor rehabilitation with high ecological validity.
The approach extends the state of the art by employing AI for adaptive neural decoding, cognitive-state monitoring, and longitudinal meta-analysis of rehabilitation trajectories. Active BCI components use personalized models to decode motor imagery under inter- and intra-subject variability, while passive BCI continuously monitors cognitive workload, mental
fatigue, and engagement. An exploratory component investigates the feasibility of an AI-assisted therapeutic agent capable of partially supporting therapist actions within immersive, cooperative VR environments, while preserving safety, interpretability, and clinical oversight.
The ambition is to establish a scalable and personalized neurorehabilitation framework that enhances therapeutic efficacy, strengthens patient–therapist interaction through shared-action VR tasks, and reduces therapist workload. By integrating active and passive BCI, cooperative VR, and explainable AI within a single coherent system, the project aims to generate
new scientific insights into rehabilitation dynamics and provide a clinically relevant pathway toward accessible, data-driven post-stroke rehabilitation in clinical and home-based settings. |
Metrological framework for the verification of dynamic 3D scanning systems according to ISO GPS in digital manufacturing
Metrologický rámec verifikácie dynamických 3D skenovacích systémov podľa ISO GPS v podmienkach digitálnej výroby
| Duration: |
1.9.2026 - 31.8.2029 |
| Program: |
SRDA |
| Project leader: |
Doc. RNDr. Witkovský Viktor CSc. |
| Annotation: | The project addresses the lack of a comprehensive methodological framework for the verification of handheld 3D scanning systems. Despite their massive implementation in digital manufacturing (Industry 4.0/5.0), their metrological assurance lags behind technical hardware capabilities. The core scientific challenge is the missing link between the variable nature of handheld scanning (operator influence, trajectory, strategy) and the strict requirements of the Geometrical Product
Specifications (ISO GPS) system.
The objective is to research and develop a metrological framework that transforms handheld 3D scanning from a
visualization tool into a full-fledged system for product conformity decision-making. The project focuses on developing specialized reference artifacts with complex geometry designed for dynamic optical systems. It uniquely combines the technological expertise of UNIZA in digital quality control with the fundamental metrological competencies of the Institute of Measurement SAS in calibration and uncertainty estimation (GUM).
The original contribution is an ISO GPS-oriented verification methodology that systematically integrates dynamic measurement uncertainty sources into final conformity assessment. The outputs include a physical reference artifact with SI traceability and verified procedures for the automotive and machinery industries. The project directly supports digital manufacturing chains by enhancing production quality and reducing non-conformance costs through metrologically correct
validation of complex components. |
Multi-lead ECG measurement to create a personalized model of the electric field of the heart and research the possibilities of its use for the diagnosis and optimization of cardiac arrhythmia therapy
Mnohozvodové meranie EKG na vytvorenie personalizovaného modelu elektrického poľa srdca a výskum možností jeho využitia na diagnostiku a optimalizáciu terapie srdcových arytmií
| Duration: |
1.1.2025 - 31.12.2028 |
| Program: |
VEGA |
| Project leader: |
Ing. Švehlíková Jana PhD. |
| Annotation: | In the proposed project, we plan to link multi-lead ECG measurements on the chest with a personalized
model of the heart and chest of the measured patient obtained from a CT scan. We intend to implement the physiological properties of healthy myocardium into the heart chamber model, as well as some pathological morphological and structural changes, such as left ventricular hypertrophy or left bundle branch block in heart failure.
Using simulations of activation propagation in the heart chambers, we will study changes in ECG signals in
the above diagnoses, as well as the consequences of different settings of supportive stimulation in resynchronization therapy for heart failure.
We will implement advanced methods of signal processing and calculation of selected characteristics in quasi-real
time into a new multi-lead ECG measurement system with wireless data transmission to a control computer. |
Design of a Methodology and its Verification for the Measurement of Selected Parameters of Ti Implants in the Manufacturing Process
Návrh metodiky a jej overenie pre meranie vybraných parametrov Ti implantátov vo výrobnom procese
| Duration: |
1.7.2023 - 30.6.2027 |
| Program: |
SRDA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | The project focuses on the development and application of measurement and non-destructive testing methods in
the manufacturing of titanium dental implants. Dental implants are medical devices that have to comply with the
technical requirements given by regulation of the European Parliament and Council EU 2017/745 from 5 Apr 2017.
Under this regulation, among other obligations, the manufacturer must ensure that these devices are safe and
effective and do not compromise the clinical condition or patients safety. The dental implants should also meet a
high level of health and safety protection, taking into account the generally accepted state of the art in science and
technology. In this project we will address the requirements related to the design and manufacturing and in
particular: the compatibility of the different parts of the device, the influence of processes on the properti es of the
materials, the mechanical properties of the materials used such as strength, ductility, resistance to wear and
fatigue, the properties of the surfaces, and confirmation that the device meets all defined physical specifications as
well as the identification of contaminants in the manufacturing process. To ensure these requirements, we intend to
use state-of-the-art measurement methods such as X-ray microtomography (microCT), scanning electron
microscopy (SEM), optical measurement of surface roughness, SQUID magnetometry. Since the above
measurement methods are time consuming and do not allow their full application in the production, the solution will
also include the design of effective methods of statistical quality control, which will be applied at the manufacturer
of dental titanium implants MARTIKAN, s.r.o. The objectives of the proposed project correlate with the Research
and Innovation Strategy for Smart Specialisation of the Slovak Republic 2021-2027 (SK RIS3 2021+), while they
affect two defined domains, namely Innovative Industry for the 21st Century and Healthy Society. |
Methods and algorithms for causal analysis and quantification of measurement uncertainty
Názov projektu Metódy a algoritmy kauzálnej analýzy a kvantifikácie neistôt meraní
| Duration: |
1.9.2026 - 31.12.2029 |
| Program: |
SRDA |
| Project leader: |
Doc. RNDr. Witkovský Viktor CSc. |
| Annotation: | The project develops advanced methods and algorithms for causal analysis of stochastic and deterministic processes and for quantifying measurement uncertainties. It addresses methodological challenges in the analysis of time series and dynamical data, where correlation alone is insufficient to reveal the mechanisms governing system behavior. Many
applications, therefore, require identifying causal relations between variables while reliably characterizing uncertainties arising from measurement processes, noise, and incomplete observations.
The project will develop classical and modern approaches to causal analysis of time series based on probabilistic and statistical modeling, and integrate them with algorithms enabling statistical inference and prediction in the presence of randomness, measurement errors, and uncertainty.
Modern applications in physical, biomedical, economic, environmental, and linguistic measurements, as well as in the social sciences (education, psychology), generate large and complex datasets with intricate dependence structures and temporal dynamics. A significant project component is hence the study of stochastic dynamical models, including diffusion processes, as a natural framework for modeling random dynamics observed via measurement time series. When modeling complex temporal or spatio-temporal data using kriging, causal structure will serve as a key starting point.
The project also advances uncertainty methods for quantifying measurement uncertainties in line with modern metrology and aims to establish a unified methodological framework combining causal analysis, dynamical modeling, and statistical inference and forecasting. Interdisciplinary collaboration among the Institute of Measurement Science of the SAS, the
Mathematical Institute of the SAS, and the Faculty of Science of P. J. Šafárik University creates favorable conditions for the development of new theoretical results, efficient algorithms, and their applications. |
Non-invasive measurement and metrological traceability of DC component in modern networks with battery storage
Neinvazívne meranie a metrologická sledovateľnosť jednosmernej zložky v moderných sieťach s batériovými úložiskami
| Duration: |
1.9.2026 - 28.2.2029 |
| Program: |
SRDA |
| Project leader: |
Ing. Gogola Daniel PhD. |
| Annotation: | In the context of Slovakia's energy transformation, the share of renewable energy sources and battery storage systems integrated into the electricity grid is increasing. These devices operate with direct current (DC) but connect to alternating current (AC) networks, requiring metrologically reliable on-site measurement of DC power and energy. The first objective is to test and characterize a non-invasive DC sensor for measuring high currents (up to 1200 A) with 0.1% accuracy, suitable for battery storage, photovoltaic systems, and electric mobility. The second objective is to establish a reference standard for DC power and energy traceable to national standards. Additionally, connecting DC sources without transformers injects
DC components into AC networks, causing overheating, increased losses, and reduced power quality. The project therefore investigates the impact of DC components on AC electricity meters, with results serving as a basis for updating legislative requirements. The project supports the development of smart energy grids and contributes to effective electricity flow management in Slovakia's economy. |
Optimization and Standardization of Quantitative Magnetic Resonance Imaging Methods. Suppression of Metallic Artifacts on low-field MR Scanners
Optimalizácia a štandardizácia kvantitatívnych metód zobrazovania magnetickou rezonanciou. Potlačenie kovových artefaktov na nízkopolových MR skeneroch
Collaborative BCI post-stroke neurorehabilitation using a patient-therapist interactive VR environment
Pacient-terapeut kolaboratívna BCI-VR neurorehabilitácia po cievnej mozgovej príhode
| Duration: |
1.9.2024 - 31.8.2026 |
| Program: |
|
| Project leader: |
Ing. Mgr. Rosipal Roman DrSc. |
| Annotation: | A growing body of evidence suggests that integrated brain-computer interface (BCI) technologies and virtual reality (VR) environments provide a flexible platform for a range of neurorehabilitation therapies, including significant motor recovery and cognitive-behavioral therapy following stroke. When a subject is immersed in such an environment, their perceptual level of social interaction is often impaired due to a suboptimal interface quality that lacks the social aspect of human interactions. The project proposes a user-friendly intelligent BCI system with a suitable VR environment in which both patient and therapist interact through their person-specific avatar representations. On the one hand, the patient voluntarily and at his/her own pace controls his/her activity in the environment and interacts with the therapist through a BCI-driven mental imagery process. On the other hand, the therapist's unrestricted motor and communication skills allow for full control of the environment. Thus, the VR environment can be flexibly modified by the therapist, allowing for the creation and selection of different occupational therapy scenarios according to the patient's recovery needs, mental states, and immediate reactions. |
Advanced diagnostics of neurodegenerative disorders using magnetic resonance techniques and artificial intelligence
Pokročilá diagnostika neurodegeneratívnych ochorení pomocou techník magnetickej rezonancie a umelej inteligencie
| Duration: |
1.7.2023 - 30.6.2027 |
| Program: |
SRDA |
| Project leader: |
Ing. Gogola Daniel PhD. |
| Annotation: | Neurodegenerative diseases (ND) are becoming a severe problem in developed countries. Since we currently have
no effective therapies available, early diagnosis is critical to ensure a good quality of life for ND patients. ND are
characterized by iron accumulation and magnetite mineralization in brain tissue, with ferritin as a precursor. Due to
its low relaxivity, physiological ferritin is at the edge of visibility using magnetic resonance imaging (MRI)
techniques. On the contrary, "pathological" ferritin causes a significant shortening of MRI relaxation times. This
creates hypointense artifacts, which theoretically allow the distinguishability of both proteins. Since iron
accumulation precedes the clinical symptoms of the disease, MRI has the potential to become a non -invasive
diagnostic method for the early stages of ND. At present, however, this is limited by the insufficient characterization
of the relaxation properties of biogenic iron and the uncertainty in the interpretation of clinical data. Therefore, our
basic goal (application output) is the development of a comprehensive methodology (FERINO software tool) for the
unequivocal diagnosis of the early stages of ND. To reach our goal, we will use a combination of several diagnostic
techniques and artificial intelligence tools. The diagnostic techniques include in-vitro, in-silico, and in-vivo
characteristics of ferritin relaxation, structural MRI, magnetic resonance spectroscopy (MRS), neurological tests,
and clinical biochemistry biomarkers. The cornerstone of the methodology will be the FerroQuant software tool,
which was proposed by the principal investigator within the APVV 2012. It enables the analysis and quantification
of iron-related clinical MRI data but lacks new findings in iron MRI (false-positive artifacts, ferritin's mineral phases).
FerroQuant also does not use artificial intelligence and does not combine different diagnostic data, whic h, however,
will be an integral part of the FERINO tool. |
The application of Artificial Intelligence methods for improved Magnetic Resonance Imaging
Použitie metód umelej inteligencie na zlepšenie zobrazovania pomocou magnetickej rezonancie
| Duration: |
1.1.2026 - 31.12.2028 |
| Program: |
VEGA |
| Project leader: |
RNDr. Krafčík Andrej PhD. |
| Annotation: | Magnetic Resonance (MR) is a widely used, useful diagnostic tool. However, since the measured signal is
influenced by many factors (e.g., by the amount of biogenic contrast agents), quantitative analysis is difficult and
lengthy. Therefore, the proposed project aims to model the influence of biogenic nanoparticles of ferritin on MR
signal and to use artificial intelligence for automated analysis (identification, segmentation and volumetry) of
structures in MR images of joint, muscles and the heart. Advanced deep learning methods will be used for these
tasks. In addition, the project will focus on design and implementation of novel acquisition and calibration
sequences and protocols for metabolic and structural MR imaging. The project will also analyse the physiological
response of MR measurements on cardiovascular system through wearable optical sensors. |
Determination of Iron in blood and tissues of laboratory animals using SQUID magnetometer.
Stanovenie množstva železa v krvi a tkanivách laboratórnych zvierat pomocou SQUID magnetometra
| Duration: |
1.9.2024 - 31.8.2026 |
| Program: |
|
| Project leader: |
Mgr. Škrátek Martin PhD. |
| Annotation: | Iron is an essential chemical element that is part of many metabolic processes. However, the amount of iron in the body must be balanced, as its excess or deficiency can lead to serious health conditions. Iron is found in the body in ferritin, hemoglobin or transferrin proteins. Deoxyhemoglobin, methemoglobin, and myoglobin are known to exhibit paramagnetism, which originates from the Fe2+ Fe3+ ions embedded in their molecules. Ferritin, as an iron storage protein, contains Fe atoms mineralized in the form of oxyhydroxide nanoparticles, whose behavior is superparamagnetic. SQUID magnetometry offers the possibility of detecting and quantifying different forms of iron with high sensitivity and could be more useful than other established methods (colorimetric, spectrophotometric, histochemical or atomic absorption spectrometry) in determining the amount of iron in small samples. |
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Štipendiá pre excelentných PhD. študentov a študentky R1
| Duration: |
1.9.2023 - 31.8.2026 |
| Program: |
|
| Project leader: |
Ing. Pajanová Iveta |
| Annotation: | PhD Topic: Application of deep-learning algorithms on automated MRI data processing.
Annotation: Automated identification and segmentation of clinical data, obtained primary by MRI, is very desirable. The reason is typically large size of data and therefore enormous time, which radiologist has to invest into the manual segmentation. Availability of powerful hardware open new capabilities to automate this processes and speedup via deep learning techniques using convolutional neural networks (CNN). Therefore, student will learn the fundamental functionality principles of MRI device (theoretically and practically), try manual segmentation of volumetric MRI data, and theoretically and practically learn principles of CNN. Student will design own architecture of CNN for automated segmentation of volumetric data, further train, validate and implement on testing data.
The output of this dissertation should be a CNN capable of deployment in clinical practice, in the diagnosis and quantitative analysis of selected tissues (cartilage, ligaments, tendons, menisci, subcutaneous fat, etc.). It is theoretical work, in which programming basics and knowledge of some programming language are necessary. As the programming environment, for design and implementation of CNN, will be used Python with module TensorFlow. |
Cockroaches in complex past ecosystems
Šváby v komplexných pravekých ekosystémoch
| Duration: |
1.9.2026 - 31.8.2028 |
| Program: |
SRDA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | Cockroaches, together with their predatory descendants, praying mantises, and social themes, have been pillars of
ecosystems for more than 300 million years, primarily through the decomposition of biomass - they have no substitutes in this. New discoveries make it possible to grasp their evolution in a broader context and to the extent to which they influence the cycle of individual elements during the geological scale. Therefore, the samples in this project, in addition to the detailed frontier evolutionary analysis, also include complex geological, physical and chemical analysis and knowledge applied to entire ecosystems. The project benefits from global cooperation and possibly already processed material from around the world, which will represent not only almost 10% of the latest knowledge, but all groups are already included in
the appropriate system. Such work has no parallel in other terrestrial groups and is based on 110,000 samples, of which 4,000 are represented by various ambers, including those from the time of dinosaurs. This year's research has already been published in high impact (NSR IF= 20.7) and therefore this study is promising. In addition to science and wide popularization (over 40,000 students), the project will also create a new job and provide part-time jobs for exceptionally talented high school students who would otherwise end up abroad and/or in a commerce. |
Theoretical properties and applications of special families of probability distributions
Teoretické vlastnosti a aplikácie špeciálnych tried rozdelení pravdepodobnosti
| Duration: |
1.1.2024 - 31.12.2027 |
| Program: |
VEGA |
| Project leader: |
Doc. RNDr. Witkovský Viktor CSc. |
| Annotation: | In the project, problems related to probability distributions and their applications in mathematical modeling will be studied. We will analyze some classes of distributions (distributions generated by partial summations, the Schröter family) and study properties of distributions belonging to these classes. Issues related to calibration regression models will be addressed. New methods for solving multivariate statistical problems will be developed. These methods will be based on the calculation of exact probability distributions using the inverse transformation of the characteristic function of the distribution of the output variable. Entropy, another property of probability distributions, plays an important role in detecting causality in time series. The primary area of application is the
use of the distribution of test statistics in hypothesis testing. The new results obtained during the solution of the project will also be applied to mathematical modeling in metrology, linguistics and actuarial mathematics. |
Characteristic function-based goodness-of-fit test for fuzzy data with application to climate analysis
Testy dobrej zhody založené na charakteristickej funkcii pre neurčité údaje s aplikáciou na analýzu klimatických dát
| Duration: |
1.1.2026 - 31.8.2028 |
| Program: |
SRDA |
| Project leader: |
Doc. RNDr. Witkovský Viktor CSc. |
| Annotation: | Modern research faces growing data uncertainty from measurement errors, gaps, and subjective assessments. Traditional statistical methods, assuming precise data, often fail under such conditions. Fuzzy data, which capture vagueness and imprecision, offer a natural framework, yet robust statistical tools for them remain scarce. This interdisciplinary project — combining probability and mathematical statistics, applied mathematics, and measurement science — aims to develop a goodness-of-fit test based on characteristic functions for fuzzy and interval-valued data. This novel methodology addresses both theoretical and applied challenges, with a focus on climate analysis.
Objectives include:
(1) Developing theoretical and empirical characteristic functions for fuzzy data, defining distance measures, formulating the test, and deriving its statistical properties.
(2) Designing and implementing efficient algorithms in R, MATLAB, or Python.
(3) Evaluating performance through simulations and benchmarking against existing methods.
(4) Applying the method to real climate datasets (e.g., temperature, rainfall) to demonstrate its relevance under uncertainty.
The methodology leverages the uniqueness and computational benefits of characteristic functions, extended to fuzzy settings. The project innovatively integrates characteristic functions and fuzzy theory for hypothesis testing, providing a statistically rigorous yet practical approach to imprecise data analysis. Expected outcomes include: a new statistical test, open-source software, simulation and benchmark studies, case studies on climate data, and preparation of a publication in leading journal. This bilateral project brings together expertise in fuzzy theory (University of Montenegro) and measurement science (Institute of Measurement Science of the Slovak Academy of Sciences). |
Effects of low-frequency and pulsed electromagnetic fields at a cellular level
Účinky nízkofrekvenčných a pulzných elektromagnetických polí na bunkovej úrovni
| Duration: |
1.1.2025 - 31.12.2028 |
| Program: |
VEGA |
| Project leader: |
Mgr. Teplan Michal PhD. |
| Annotation: | Although there is ongoing interest in the adverse and beneficial effects of electromagnetic fields (EMF), a clear
explanation of EMF's influence on living structures is lacking. To investigate low-frequency (LF) magnetic fields
(MF), we will enhance our experimental platform to test their possible inhibitory or stimulatory effects based on
frequency and magnetic flux density parameters. As a model organism yeast strain Saccharomyces cerevisiae
will be used. Its response to time-harmonic and pulsed MF will be studied by measuring cell growth curve using
turbidimetry, impedance spectroscopy and microscopy. Moreover, the ion parametric resonance interaction
model will be verified for biogenic ions and the magnitude of the ambient static geomagnetic field. The importance
of this area of research lies in exploring physical methods for manipulating biological structures, with potential
benefits for biotechnology and medical treatment. |
Assessment of restitution of normal ventricular activation by ECG mapping
Vyhodnotenie reštitúcie normálnej komorovej aktivácie pomocou EKG mapovania
| Duration: |
1.9.2025 - 31.8.2028 |
| Program: |
SRDA |
| Project leader: |
Ing. Švehlíková Jana PhD. |
| Annotation: | The project intends to optimize and personalize cardiac resynchronization therapy (CRT) for patients with heart failure. This effective, nonpharmacological, pacing-based treatment aims to restore interventricular resynchronization of ventricular activation by pacing both ventricles with an expected subsequent increase in cardiac output. However, about 30-40% of the patients do not benefit from the therapy and are designed as “non-responders”. To improve the efficacy of ventricular resynchronization, conduction system pacing (CSP) was recently introduced into clinical practice, which replaces biventricular stimulation with direct stimulation of the conduction system. However, CSP to achieve a narrow QRS complex is not feasible in up to 15% of patients for multiple anatomical, pathological, and technical reasons. Therefore, an optimal individualized strategy to achieve effective ventricular resynchronization is an unmet need in electrical therapies in heart failure patients. The proposed research project is methodologically based on noninvasive body surface potential ECG measurements of patients with heart failure indicated for a CRT/CSP device implantation. From the measured data, conducted using a dedicated in-house measuring device, the new parameters for the evaluation of the dynamics of the ventricular activation will be derived to set the proper programming stimulation of the device. A possible reduction of the number of ECG electrodes from the currently used 128 will also be studied to facilitate the routine clinical feasibility of the recording system. The simulations of the failing heart will be performed to understand better the processes that are undergoing in the ventricles. The area of the starting spontaneous ventricular activity will be assessed by solving the inverse problem of electrocardiography using a personalized heart-torso model obtained from the CT scan. The dedicated measuring system will implement a GUI to apply the suggested methods easily. |
Research of Dental Implant Components for the Creation of Personalized 3D Models
Výskum digitalizácie komponentov dentálnych implantátov za účelom
| Duration: |
1.4.2024 - 30.6.2026 |
| Program: |
|
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | The main objective of the present project is the development and optimization of digitization methods and processes in the field of dental implants, with special emphasis on the development of personalized 3D models implementable in the production process. This goal includes the intention to expand current knowledge with new methodologies, technologies, and procedures that will enable more accurate, faster, and more efficient production of dental implants, with a high degree of individualization for individual patients.
The fulfilment of the project's intentions should bring significant progressive changes in the field of digitization of dental implantology. This ambitious endeavor includes research-oriented research in digital technologies, data measurement, and processing to push the existing frontiers of knowledge and set new standards in the industry. Current knowledge will be expanded to include new methodologies, technologies, and procedures that have the potential to change the paradigm of the design, manufacture, and testing of dental implants. With new scientific findings and technological innovations, we can achieve the production of dental implants that will be more accurate, reliable, and effective in terms of their functional properties.
A great benefit of the project is the high degree of individualization. By creating personalized 3D models, it will be possible to create implants tailored to individual patients. This will affect not only the implants themselves, but also the entire production process, from planning and design to final implementation. This will bring patients not only better quality treatment but also faster rehabilitation and a significant improvement in their quality of life.
The result of the project will be not only technological progress in the design and production of dental implants but also innovative solutions with a positive overlap in the areas of healthcare and dentistry. The future development of dental implants will be based on accurate data and personalized solutions, which will increase the efficiency of the implantation process, safety, and patient satisfaction, and this is an important benefit of the presented project.
|
Research on the correlation dependences of magnetic, structural, and optical properties of aluminate glasses, titanium alloys, and titanium-based nanocolloids, and ion liquids
Výskum korelačných závislostí magnetických, štruktúrnych a optických vlastností hlinitanových skiel, titánových zliatin a nanokoloidov na báze titánu a iónových kvapalín
| Duration: |
1.1.2025 - 31.12.2028 |
| Program: |
VEGA |
| Project leader: |
Mgr. Škrátek Martin PhD. |
| Annotation: | The project focuses on the development of magnetic measurement methods for selected areas of materials
research and biomedicine, for a deeper understanding of the physical and chemical properties associated with
changes in the distribution of electrical charges, and for their utilization in designing revised technological
procedures and diagnosing surface properties. First goal of the project is to investigate the influence of
composition, precursor powder preparation methods, and the preparation method of aluminate
glasses/glass-ceramics on their structure and magnetic properties. The second goal is the investigation of the
influence of properties and composition of ion liquids on the phase composition, shape, size distribution, and
stability of titanium-based nanoparticles and nanostructures. The physicochemical and magnetic properties of
nanocolloids will be studied with attention to the surface properties of biomedical Ti-alloys, especially
nanostructures based on titanium oxide. |
Research of the metal organ pipe collections of historical pipe organs in Slovakia
Výskum kovového píšťalového fondu historických organov na Slovensku
| Duration: |
1.9.2025 - 31.8.2028 |
| Program: |
SRDA |
| Project leader: |
RNDr. Krafčík Andrej PhD. |
| Annotation: | The sound-stylistic quality of historical organs is determined by various factors, including the material used for the organ pipes and the scaling (mensuration) of individual pipes and entire stops. The proposed project will examine organ metal as a key sound-stylistic determinant of historical organs, with consideration of the constructional evolution of organs in Slovakia from the 17th to the 20th century. The project will be conducted in four phases. The first phase will focus on the chemical composition analysis of organ pipe metal from selected instruments. These pipes and entire stops will undergo mensuration analysis, leading to the development of a mathematical model. The next phase will involve the visual recording (collection) of signings—etched or stamped markings indicating the specific tone for which a pipe is constructed. The signings of pipes from instruments with known builders will be documented to create a standard that will enable the use of neural networks (AI) to identify the authorship of organs whose builders are currently unknown. The research will also address the technical condition of organ metal, particularly corrosion, which affects not only the sound properties but also the preservation of the metal components of these historical instruments. The project's outcomes will include an online map of organ metal composition, corrosion, mensurations, an atlas of various types of corrosion and defects in organ pipes, as well as a comprehensive mapping of the metal and mensurations of studied stops. Furthermore, we will establish a method for gradually authorizing organs whose builders remain unidentified. All findings will be contextualized within the sound-stylistic development of historical organ building on Slovak territory. |
Research of reference standards and measurement methods ensuring determination of the relationship of geometric specifications and qualitative indicators of 3D objects created by additive technologies
Výskum referenčného etalónu a meracích metód zabezpečujúcich určenie vzťahu geometrických špecifikácií a kvalitatívnych ukazovateľov 3D objektov vytvorených aditívnymi technológiami
| Duration: |
1.7.2024 - 31.12.2027 |
| Program: |
SRDA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | The present project is aimed at evaluating the quality of additive manufacturing, a reference test artefact designed and developed for this purpose. The development of the reference artefact and the quantification of its parameters will make use of the latest knowledge in additive manufacturing, state-of-the-art measurement strategies implemented using X-ray microtomography, magnetometry, coordinate measuring devices, optical and electron scanning microscopes and methods of mathematical-statistical processing of measured data. Additive manufacturing technologies are capable of producing parts with very complex geometries that conform to the desired design without further machining. It is for this reason that they are very promising and their use in industry is growing. In order for additive manufacturing products to fully replace conventionally machined parts, they must meet the required quality criteria such as shape and dimensional accuracy, surface roughness, internal defects, residual stresses, etc. The final quality of parts produced by additive manufacturing technology is influenced by the characteristics of the raw material and the parameters and settings of the system. The aim of the project is to investigate the production of modified monofilaments and the measurement methods necessary for the realization of a stable and reproducible reference test artifact, which would be used to assess not only the geometric capability of additive manufacturing systems but also the internal structure and selected properties of the final product. |
Research on the influence of hydrodynamic flows on the distribution of oxygen vacancies in Yttrium-Aluminum garnet single crystal grown via Horizontally Directed Crystallization for detectors
Výskum vplyvu hydrodynamických prúdov na rozloženie kyslíkových vakancií v monokryštáloch ytriovo-hlinitého granátu vypestovaných horizontálne riadenou kryštalizáciou pre detektory
| Duration: |
1.9.2026 - 31.8.2029 |
| Program: |
SRDA |
| Project leader: |
Ing. Majerová Melinda PhD. |
| Annotation: | The project is focused on the research of oxygen vacancies in single crystals of Yttrium aluminium garnet. During the growing process, these oxygen vacancies are distributed unevenly in the volume of the crystal, which is affected by hydrodynamic flows in the melt. Since the melting temperature for YAG is higher than 1950°C, a physical model will be built for the research. On the basis of these data, an experimental thermal unit will be assembled with the possibility of controlling the thermal field, which will enable the control of convection currents in the melt. Crystals will be grown in this
thermal unit and will be characterised. The result of the project will be data and correlation of the influence of hydrodynamic flows on the distribution of oxygen vacancies in single crystal of Yttrium aluminium garnet, which has a high potential for use in detectors. |
Development and standardization of MR-based methods for detecting and evaluating metabolic and structural adaptations of aging muscles to exercise.
Vývoj a štandardizácia MR metód založených na magnetickej rezonancii na detekciu a hodnotenie metabolických a štrukturálnych adaptácií starnúcich svalov na cvičenie.
| Duration: |
1.9.2025 - 31.8.2029 |
| Program: |
SRDA |
| Project leader: |
Mgr. Klepochová Radka PhD. |
| Annotation: | Aging is associated with a loss of muscle mass and the functional capacity of skeletal muscles; however, regular
exercise can slow down these processes. The focus of this project is on examining the metabolic, functional, and
structural parameters in the lower limb muscles, which we can non-invasively and repeatedly measure using
innovative magnetic resonance methods (MR). This allows us to compare the trajectories of aging in skeletal
muscles of sedentary individuals and those who are physically active. One of the key parameters that define a
muscle's ability to efficiently mobilize and use energy for muscle work is called metabolic flexibility. The aim of the
project is to develop innovative MR methods to study metabolic flexibility and structural changes in skeletal
muscles during aging, and relate them to whole-body metabolic flexibility, as well as the metabolic phenotype and
structural and molecular changes in the skeletal muscles of older adults. As part of the project, we will standardize the measurement of dynamic changes in metabolites in muscle during exercise using proton (1H) MR
spectroscopy, create standard procedures for quality control of acquired MR spectroscopy data, and a key aspect
of the project will also be the development of an automated segmentation method based on a convolutional neural
network, which will enable more efficient and reliable evaluation of MR images of skeletal muscles. These
innovative methods will be validated using data from ongoing longitudinal studies at the Biomedical Center of the
Slovak Academy of Sciences, and their results will be directly compared with parallel changes in metabolic health,
functional capacity, histological structure, and molecular mediators of metabolic flexibility in skeletal muscles. The
results may not only improve our understanding of the processes that define metabolic flexibility during aging but
may also offer relevant strategies to support metabolically healthy aging. |
Development of advanced luminescent glass 3D structures by additive techniques
Vývoj pokročilých luminscenčných 3D štruktúr pomocou aditívnej výroby
Changes in fossil lizard communities at older and younger Cenozoic sites in and around Europe as a result of dramatic global climate change – the key to understanding our future is in the past
Zmeny v spoločenstvách fosílnych jašterov na lokalitách staršieho a mladšieho kenozoika v Európe a okolí ako dôsledok dramatických globálnych klimatických zmien – kľúčom k budúcnosti je chápanie minulosti
| Duration: |
1.1.2024 - 31.12.2026 |
| Program: |
VEGA |
| Project leader: |
RNDr. Hain Miroslav PhD. |
| Annotation: | Terrestrial ecosystems in Europe, but practically everywhere, changed significantly during the Cenozoic due to
global climatic changes. The importance of their better understanding is magnified by present global climate
change. In that respect, lizards are widely regarded as excellent indicators of past climates, particularly ambient
temperatures. The project is focused on the research of new, often complete finds from localities of different ages
such as the Paleocene site of Walbeck in Germany, the Lower Eocene sites of Dormaal in Belgium, Cos,
Pasturat and Viélase in France. We also include new complete finds from the Middle Eocene German Messel
locality (Unesco). Furthermore, fossils from the Oligocene and Lower Miocene sites of Phosphorites du Quercy
(France), Miocene to Pliocene sites in Austria, Slovakia, Poland, Hungary, but also in Africa (Kenya) will be
studied. The aim is this research using CT is an interpretation of the phylogenetic relationships of studied taxa
and changes in their communities. |
The total number of projects: 32
