A5085027865- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Neural Networks and Applications
- Emotion and Mood Recognition
- Neural Networks and Reservoir Computing
- Neural and Behavioral Psychology Studies
- Face and Expression Recognition
- Advanced Memory and Neural Computing
- Functional Brain Connectivity Studies
Technical University of Sofia
2014-2019
Sofia University "St. Kliment Ohridski"
2015
Electroencephalography (EEG) based affective computing is a new research field that aims to find neural correlates between human emotions and the registered EEG signals. Typically, emo- tion recognition systems are personalized, i.e. discrimination models subject-dependent. Building subject-independent harder problem due high variability be- tween individuals. In this paper we propose unified system for efficient of positive negative in group 26 users. The users were exposed arousal images...
Despite numerous successful applications of Deep Learning (DL) to large-scale image, video, speech and text data, they remain relatively unexplored in brain imaging field. In this paper, we make an overview recent DL architectures for recognizing cognitive activities from Electroencephalogram (EEG) data with particular emphasis on Brain Computer Interface(BCI) technologies Affective Neurocomputing. We discuss the use convolutional, recurrent neural nets, as well deep belief networks,...
This study aims at finding the relationship between EEG-based biosignals and human emotions. Event Related Potentials (ERPs) are registered from 21 channels of EEG, while subjects were viewing affective pictures. 12 temporal features (amplitudes latencies) offline computed used as descriptors positive negative emotional states across multiple (inter-subject setting). In this paper we compare two discriminative approaches : i) a classification model based on all one channel ii) over channels....