A5022647012- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Neuroscience and Neural Engineering
- Complex Systems and Time Series Analysis
- Neural Networks and Applications
- Advanced Memory and Neural Computing
- Blind Source Separation Techniques
- Neural and Behavioral Psychology Studies
- ECG Monitoring and Analysis
- Sleep and Work-Related Fatigue
- Artificial Intelligence in Healthcare and Education
- Non-Invasive Vital Sign Monitoring
- Image Retrieval and Classification Techniques
- Heart Rate Variability and Autonomic Control
- Chaos-based Image/Signal Encryption
- Ethics and Social Impacts of AI
- Face Recognition and Perception
- Hand Gesture Recognition Systems
- Plant Ecology and Soil Science
- Cooperative Communication and Network Coding
- Neurological Disorders and Treatments
- Fractal and DNA sequence analysis
- Time Series Analysis and Forecasting
- Modeling, Simulation, and Optimization
- Artificial Intelligence in Healthcare
Universitatea Națională de Știință și Tehnologie Politehnica București
2013-2024
Siemens (Romania)
2023-2024
Siemens (Germany)
2024
Transylvania University of Brașov
2020-2024
Technische Universität Berlin
2015-2017
University of Bucharest
2016
Laboratoire Traitement et Communication de l’Information
2013
Institut Mines-Télécom
2013
Centre National de la Recherche Scientifique
2013
In an attempt to create a more familiar brain-machine interaction for biometric authentication applications, we investigated the efficiency of using users' personal hobbies, interests, and memory collections. This approach creates unique pleasant experience that can be later utilized within protocol. paper presents new EEG dataset recorded while subjects watch images popular pictures with no point interest great significance. addition, propose several applications tackled our newly collected...
The adoption of the European Health Data Space (EHDS) regulation has made integrating health data critical for both primary and secondary applications. Primary use cases include patient diagnosis, prognosis, treatment, while applications support research, innovation, regulatory decision-making. Additionally, leveraging large datasets improves training quality artificial intelligence (AI) models, particularly in cancer prevention, prediction, treatment personalization. Union (EU) recently...
Decoding neurocognitive processes on a single-trial basis with Brain-Computer Interface (BCI) techniques can reveal the user's internal interpretation of current situation. Such information potentially be exploited to make devices and interfaces more user aware. In this line research, we took further step by studying neural correlates different levels cognitive developing method that allows quantify how deeply presented is processed in brain.
Texture aspects are encountered in most domains that use image processing. Despite the decades of research on texture information, characterization remains a competition for scientific community because rigorous mathematical definition was not yet decided. Therefore, analysis and classification needs depth continuous improvement. Beside common fractal properties, this paper uses modern property which characterizes different descriptors order to provide additional information extract new features.
It is said that image segmentation a very difficult or complex task. First of all, we emphasize the subtle difference between notions difficulty and complexity. Then, in this article, focus on question how two widely used color complexity measures correlate with number segments resulting over-segmentation. We study evolution both as gradually decreased by means low-pass filtering. In way, tackle possibility predicting based measures. analyze images from point view entropy fractal dimension...
The impact of stress caused by car driving on heart's activity has been extensively studied for over 60 years. In the present paper, we influence drivers' heart rate. algorithm was applied electrocardiographic signals from 6 drivers, and resulting rate variability parameters in time domain were analyzed comparing those normal conditions to conditions. results show that are closely correlated. This finding could be used create an intelligent system would monitor adapt cabin order relax...
Texture plays an important role in computer vision expressing the characteristics of a surface. complexity evaluation is for relying not only on mathematical properties digital image, but also human perception. Human subjective perception verbally expressed relative time, since it can be influenced by variety internal or external factors, such as: Mood, tiredness, stress, noise surroundings, and so on, while closely capturing thought processes would more straightforward to reasoning With...
The ability to infer implicit user variables in realtime and an unobtrusive way would open a broad variety of applications such as adapting the interface human-computer interaction or developing safety assistance systems industrial workplaces. Such information may be extracted from behavior, peripheral physiology brain activity. Each these sensors has its advantages disadvantages suggesting that finally all available features should fused. While Brain-Computer Interface (BCI) research...
When developing a motion synchronous Brain-Computer Interface, it is very important to have effective stimuli. This research tests and proposes an improved brain computer interface stimulus system, based on event related spectral perturbation. In order investigate the reaction of motor cortex stimuli, influence human senses has be investigated. Considering limitations senses, article visual auditory stimuli in two similar tasks, gain accuracy better time (RT) for real movements Interface systems.
In practical applications, such as patient brain signals monitoring, a non-invasive recording system with fewer channels for an easy setup and wireless connection remotely monitor physiological will be beneficial. this paper, we investigate the feasibility of using in visual perception scenario. We complexity color natural synthetic fractal texture images, by studying correlations between four types data: image that is expressed computed entropy dimension, human subjective evaluation...
This article proposes a pilot study regarding the influence of sounds (music) on EEG activity involved in BCI implementations, based analysis. The Independent Component Analysis is applied to extract most relevant ICA components for which event related (de)synchronization alpha/beta bands furtherly considered tracking effect musing brain activity, using open access dataset. results are promising, allowing clear desynchronization bands.
A new authentication method based on EEG signal is proposed here. Biometric features such as fingerprint scanning, facial recognition, iris voice and even brainwave patterns can be used for methods. Brainwave patterns, also known brain biometrics, captured using technologies like electroencephalography (EEG) to authenticate a user their unique activity. This still in the research phase not yet commonly purposes. Extracting typically involves processing techniques analyze patterns. Here,...
This study examines disturbances in the Pecineagu watershed forests over last 50 years. The primary objective of this is to comprehensively assess intensity and consequences canopy past half-century. Utilizing meta-analysis advanced remote sensing techniques, including satellite imagery from Corona Spy, Landsat, Sentinel-2, we identified significant changes forest cover structure. analysis revealed 142 hectares disturbed between 1986 1996, with a notable portion undergoing clearcutting...
<sec> <title>UNSTRUCTURED</title> The adoption of the European Health Data Space (EHDS) regulation has made integrating health data critical for both primary and secondary applications. Primary use cases include patient diagnosis, prognosis, treatment, while applications support research, innovation, regulatory decision-making. Additionally, leveraging large datasets improves training quality artificial intelligence (AI) models, particularly in cancer prevention, prediction, treatment...
Motor imagery and actual movement are both tasks that bring forth a noticeable change in the subject's EEG mu rhythm known as Even-Related Desynchronisation (ERD). They appear magnitude decreases of frequencies included said band can be tracked measured for automatic real-time detection classification events. It has been proven an important percent changes happen within narrow frequency called reactive band, providing thus means to significantly improve efficiency interpretation such events...
Video content constitutes today a large part of the data traffic on Internet. This is allowed by capillary spreading video codec technologies: nowadays, every computer, tablet and smart phone equipped with encoding decoding technologies. As matter fact, often exists in different formats, that, even though they can be incompatible to each other, still have significant mutual redundancy. The incompatibility prevents an efficient exploitation scalability, which other hand very important...
When developing a motion synchronous Brain-Computer Interface, it is very important to have effective stimuli. This research testes and proposes an improved brain computer interface stimulus system, based on event related spectral perturbation. In order investigate the reaction of motor cortex stimuli, influence human senses has be investigated. Considering limitations senses, article visual auditory stimuli in two similar tasks, gain accuracy better time (RT) for real movements Interface systems.
EEG signal processing is a complex task that requires many (pre)processing steps, due to the low signal-to-noise ratio. Challenging approaches are continuously developed, improve performance of analysis methods. This study was performed demonstrate advantages ICA algorithm in and its impact emphasizing brain activity similarities differences when considering investigation real imaginary movements. For this reason, stimuli system based on non-invasive synchronous Brain-Computer Interface...
Current trends and needs in Human-Computer Interaction (HCI) are rapidly increasing; however the possibility to estimate user's state remains unchanged. The need predict intentions, adapt accordingly real time her/his decisions could bring benefits this dual interaction. Following purpose, we evaluate of a user by means cognitive processing. In way, study feasibility detecting level processing, order be used for controlling or modifying interface HCI application, such as, an information...
In this work we investigate an image based algorithm as a reliablemethod to perceive the eye movement and offer new possibilities for activity recognition. order test effectiveness of algorithm, data was recorded using electrooculography system. Different patterns were analyzed within conducted study. Three different lighting three activities performed in evaluate performance algorithm.
Imagining a certain movement produces changes in the subject's EEG motor rhythm same manner which real execution of does. These variations are reflected by Even-Related Desynchronizations (ERD) and appear asa magnitude decrease frequency components comprising mu band. By monitoring amplitude power changes, automatic detection imagery or can be conducted. Furthermore, features extracted used for real-time classification these events. It is known that most cases, majority constrained within...