A5027044621- EEG and Brain-Computer Interfaces
- Blind Source Separation Techniques
- Sleep and Wakefulness Research
- Neural dynamics and brain function
- Visual perception and processing mechanisms
- Neural and Behavioral Psychology Studies
- Sleep and Work-Related Fatigue
- Visual Attention and Saliency Detection
- Ocular and Laser Science Research
- Advanced Vision and Imaging
- Gaze Tracking and Assistive Technology
- Sleep and related disorders
- Advanced Chemical Sensor Technologies
- Functional Brain Connectivity Studies
- Neural Networks and Applications
University of Lisbon
2010-2018
Instituto Politécnico de Lisboa
2010-2012
This work proposes a methodology for sleep stage classification based on two main approaches: the combination of features extracted from electroencephalogram (EEG) signal by different extraction methods, and use stacked sequential learning to incorporate predicted information nearby stages in final classifier. The feature methods used this include three representative ways extracting EEG signals: Hjorth features, wavelet transformation symbolic representation. Feature selection was then...
Manual visualization-based sleep stage classification is a time-consuming task prone to errors. Since the correct identification of stages vital for disorders and research in this field general, there growing demand efficient automatic methods. However, still no symbolic representation biomedical signals that leads reliable accurate system. This work presents application novel method EEG evaluates its potential as information source classifier, case SVM classifier. The data first analyzed...
This work proposes a complete structure of an EEG biofeedback platform focused on efficient way for its user to learn how self regulate cortical activity. A longitudinal study voluntary training specific electro activity produces any stable changes in the electroencephalogram is also presented. Correlations these with short term memory are hypothesized. In this human brain was seen as electrochemical machine capable receiving stimuli and adapt accordingly. So, only relevant fed back trainee...
The algorithm for artifacts detection and classification, applying different sets of constraint rules, was proposed. Two automatic detectors based on the proposed thresholding techniques that use descriptive statistics a histogram analysis, were developed. At first, performance both evaluated by matching with human expert scoring. Detectors tested various threshold values; ones provided best results selected. end, two compared each other detector identified. Detected classified into three...
K-complex is a stereotyped transient wave in the human electroencephalogram (EEG), it appears frequently during sleep recordings. Its role and significance have been disregarded since its discovery until recently, when American Association of Sleep Medicine (AASM) proposed new classification with relevant for K-complexes definition stages. It now one key features that contribute to stage assessment. are associated arousal can occur spontaneously or as an evoked response external stimuli....
Many studies have demonstrated the relationship between alpha activity and central visual ability, in which ability is usually assessed through static stimuli. Besides circumstance, however real environment there are often dynamic changes peripheral a (i.e., ability) important for all people. So far, no work has reported whether activity. Thus, objective of this study was to investigate their relationship. Sixty-two soccer players performed newly designed vision task stimuli were dynamic,...
This paper describes a method for converting sleep Electroencephalogram (EEG) signals into music. For that purpose, new segmentation procedure is used extracting relevant information from the EEG then translated sequences of notes, chords, arpeggios and pauses, with varying tempo defined by stages. The final outcome direct time-domain conversion brain activity during sound. Since typical EEGs vary age disorders, different groups subjects were in experiments: babies, sane adults patients...
This study used a peripheral vision test that evaluates how well visual information captured in two different areas of the retina is and tries to establish relation with performance subjects other fields.
This paper introduces a new methodology for converting sleep Electroencephalogram (EEG) signals into sound. The main goal is to investigate the possibility of encoding events sequences notes and breaks, generating musical sound that consistent audible, while allowing global appraisal dynamics.