Blar i NTNU Open på forfatter "Giraldo, Eduardo"
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Automatic Selection of Frequency Bands for Electroencephalographic Source Localization
Munoz, Pablo; Giraldo, Eduardo; Lopez, Maximiliano Bueno; Molinas Cabrera, Maria Marta (Journal article; Peer reviewed, 2019)This paper shows a method to locate actives sources from pre-processed electroencephalographic signals. These signals are processed using multivariate empirical mode decomposition (MEMD). The intrinsic mode functions are ... -
DYNLO: Enhancing Non-linear Regularized State Observer Brain Mapping Technique by Parameter Estimation with Extended Kalman Filter
Soler Guevara, Andres Felipe; Giraldo, Eduardo; Molinas Cabrera, Maria Marta (Journal article; Peer reviewed, 2019)The underlying activity in the brain can be estimated using methods based on discrete physiological models of the neural activity. These models involve parameters for weighting the estimated source activity of previous ... -
Low-Density EEG for Neural Activity Reconstruction Using Multivariate Empirical Mode Decomposition
Soler Guevara, Andres Felipe; Munoz, Pablo; Bueno-Lopez, Maximiliano; Giraldo, Eduardo; Molinas Cabrera, Maria Marta (Journal article; Peer reviewed, 2020)Several approaches can be used to estimate neural activity. The main differences between them concern the a priori information used and its sensitivity to high noise levels. Empirical mode decomposition (EMD) has been ... -
Low-Density EEG for Source Activity Reconstruction using Partial Brain Models
Soler Guevara, Andres Felipe; Giraldo, Eduardo; Molinas Cabrera, Maria Marta (Chapter, 2020)Brain mapping studies have shown that the source reconstruction performs with high accuracy by using high-density EEG montages, however, several EEG devices in the market provide low-density configurations andthus source ... -
Partial Brain Model For real-time classification of RGB visual stimuli: A brain mapping approach to BCI
Soler Guevara, Andres Felipe; Molinas Cabrera, Maria Marta; Giraldo, Eduardo (Chapter, 2019)Brain-computer interface (BCI) applications are characterized by real-time feature extraction and classification. Thus, brain activity reconstruction is not generally performed due to the long computation times required ... -
The Mode Mixing Problem and its Influence in the Neural Activity Reconstruction
Bueno-Lopez, Maximiliano; Giraldo, Eduardo; Molinas Cabrera, Maria Marta; Fosso, Olav B (Journal article; Peer reviewed, 2019)This paper presents and discusses the challenge of mode mixing when using the Empirical Mode Decomposition (EMD) to identify intrinsic modes from EEG signals used for neural activity reconstruction. The standard version ...