Germán Gómez-Herrero

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Directional connectivity in the brain has been typically computed between scalp electroencephalographic (EEG) signals, neglecting the fact that correlations between scalp measurements are partly caused by electrical conduction through the head volume. Although recently proposed techniques are able to identify causality relationships between EEG sources(More)
The prompt and adequate detection of abnormal cardiac conditions by computer-assisted long-term monitoring systems depends greatly on the reliability of the implemented ECG automatic analysis technique, which has to discriminate between different types of heartbeats. In this paper, we present a comparative study of the heartbeat classification abilities of(More)
Blind inversion of a linear and instantaneous mixture of source signals is a problem often encountered in many signal processing applications. Efficient fastICA (EFICA) offers an asymptotically optimal solution to this problem when all of the sources obey a generalized Gaussian distribution, at most one of them is Gaussian, and each is independent and(More)
Resonance in thalamocortical networks is critically involved in sculpting oscillatory behavior in large ensembles of neocortical cells. Neocortical oscillations provide critical information about the integrity of thalamocortical circuits and functional connectivity of cortical networks, which seem to be significantly disrupted by the neuronal death and(More)
Finding interdependency relations between (possibly multivariate) time series provides valuable knowledge about the processes that generate the signals. Information theory sets a natural framework for non-parametric measures of several classes of statistical dependencies. However, a reliable estimation from information-theoretic functionals is hampered when(More)
In this paper, we present a method based on the Matching Pursuits algorithm for extraction of time-frequency features that can be used for classification of various abnormal heartbeats. Further, we investigate the usefulness of Independent Component Analysis for extracting additional spatial features from multichannel electrocardiographic recordings. The(More)
OBJECTIVE The objective of the present work was to develop and compare methods for automatic detection of bilateral sleep spindles. METHODS AND MATERIALS All-night sleep electroencephalographic (EEG) recordings of 12 healthy subjects with a median age of 40 years were studied. The data contained 6043 visually scored bilateral spindles occurring in(More)
The aim of this paper is to combine the strengths of two recently proposed Blind Source Separation (BSS) algorithms. The first algorithm, abbreviated as EFICA, is a sophisticated variant of the well-known Independent Component Analysis (ICA) algorithm FastICA. EFICA is based on minimizing the statistical dependencies between the instantaneous (marginal)(More)
Even under thermoneutral conditions, skin temperature fluctuates spontaneously, most prominently at distal parts of the body. These fluctuations were shown to be associated with fluctuations in vigilance: mild manipulation of skin temperature during nocturnal sleep affects sleep depth and the power spectral density of the electroencephalogram (EEG), and(More)
STUDY OBJECTIVES Whereas both insomnia and altered interoception are core symptoms in affective disorders, their neural mechanisms remain insufficiently understood and have not previously been linked. Insomnia Disorder (ID) is characterized by sensory hypersensitivity during wakefulness and sleep. Previous studies on sensory processing in ID addressed(More)