The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Relying on the existing evidence that music enhances cognitive functions such as imagination and it also induces movement, this paper explored the possibility of music as an enhancer for imagined movement tasks. As a comparison, the task were also performed in silence and listening to noise. Music prove to be an enhancer, increasing the mean amplitude and energy of the EEG (p<0.001), as well as...
P300 are event related potentials that are widely used; however, the performance of systems based on it decrease drastically when they are transported outside a laboratory environment where the stimuli can be isolated. Since isolation of the stimulus is not always practical it is desirable to study P300 when the subjects are receiving stimuli in other senses besides sight. Thus this paper tested the...
Seizure onset prediction in epilepsy is a challenge which is under investigation using many and varied signal processing techniques. Here we present a multi-stage phase synchrony based system that brings to bear the advantages of many techniques in each substage. The 1st stage of the system unmixes continuous long-term (2-4 days) multichannel scalp EEG using spatially constrained Independent Component...
This paper assesses the use of independent component analysis (ICA) as applied to epileptic scalp electroencephalographic (EEG) recordings. In particular we address the newly introduced spatio-temporal ICA algorithm (ST-ICA), which uses both spatial and temporal information derived from multi-channel biomedical signal recordings to inform (or update) the standard ICA algorithm. ICA is a technique...
Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however,...
Here we successfully extracted sources from noisy single-channel abdominal phonograms. First, an appropriate matrix of delays was constructed; then multiple independent components were calculated using TDSEP; finally, components were projected back onto the measurement space and grouped using K-means. Three single-channel phonograms from different subjects were analysed. Results showed a better-quality...
Different factors can affect the accuracy of the source localization of evoked potentials: the SNR of the data, the head model, and the number of sources, mention but a few. Another fundamental factor is the correct application of independent components analysis (ICA) to both filter out artefacts and select the independent components (IC) related to the neurological response. In this paper we assess...
Independent component analysis (ICA) has found many uses in source separation in biomedical signals. We highlight a methodology and put forward an algorithm which allows single channel ICA to be performed on single channel biomedical signal recordings. The algorithm uses a fast, deflationary approach to efficiently extract independent processes underlying the single channel recordings. We show that...
In this work we test a technique based on independent component analysis (ICA), applied to single channel brain signals recorded through the electroencephalogram. Standard (or ensemble) ICA (enICA) requires multiple channel recordings to work, however when single of few channels are required enICA cannot be readily applied. Single channel ICA (scICA) can be performed by using the method of delays...
The apparently unpredictable nature of epileptic seizures can be devastating for people with epilepsy. Current medical interventions can help 75% of patients while 25% have to live with uncontrolled seizures. This motivates the search for a seizure prediction prototype using electroencephalograms (electrical signals that capture brain activity). The concept of phase synchrony has attracted much attention...
It has been suggested that the human brain is intrinsically organised into dynamic, anti-correlated functional networks. This paper presents a study on the so-called default mode network - which is active when the brain is apparently at rest - and on brain activity related to a given task. This work involves the analysis of low frequency magnetoencephalographic recordings of children with Attention...
This paper presents a method to evaluate residual dependencies between sources estimated by ICA to be used in a hierarchical clustering procedure. As a proximity measure a mutual information-based metric is employed. The properties of each group of components are evaluated at each level of the hierarchical tree by two indices that aim at assessing both cluster tightness and physiological reliability...
A method for extracting foetal heart sounds (FHS) from noisy single channel abdominal phonograms is proposed. First, an appropriate matrix of delays is constructed; then multiple independent components are calculated using FastICA; finally, components are projected back onto the measurement space and those associated to FHS are subjectively selected. Three single channel phonograms, obtained from...
Multi-channel auditory evoked potentials (AEPs) are a useful methodology for evaluating the auditory performance of children with cochlear implants (CIs). These recordings are generally contaminated, not only with well known physiological artifacts (blinking, muscle) and line noise etc., but also by CI artifact. The CI induces an artifact in the recording at the electrodes in the temporal lobe area...
This paper presents a comparison of the use of broadband and narrow band signals for phase synchronization analysis as applied to Independent Components of ictal and interictal scalp EEG in the context of seizure onset detection and prediction. Narrow band analysis for phase synchronization is found to be better performed in the present context than the broad band signal analysis. It has been observed...
In this work we propose a technique based on independent component analysis (ICA), applied to single or two channel(s) recordings of electroencephalogram (EEG) brain signals. Standard (ensemble) ICA requires multiple channel recordings to work, however when single of few channels are required ensemble ICA cannot be readily applied. Single channel ICA (temporal ICA) can be performed by preprocessed...
Epileptic seizures are generated by an abnormal synchronization of neurons unforeseeable for the patients. In this study we analyzed invasive electroencephalogram (EEG) recordings in patients suffering from medically intractable focal epilepsy with two non-linear methods, Approximate Entropy (ApEri) and Lempel-Ziv (LZ) complexity. ApEn and LZ complexity quantify the regularity and complexity of a...
In this proof-of-principle study we analyzed intracranial electroencephalogram recordings in patients with intractable focal epilepsy. We contrast two implementations of independent component analysis (ICA) - ensemble (or spatial) ICA (E-ICA) and space-time ICA (ST-ICA) in separating out the ictal components underlying the measurements. In each case we assess the outputs of the ICA algorithms by means...
The goal of this work is to discover and extract critical features from pressure signals in the aural canal resulting from actions (tongue movements) within the oral cavity. Its scope encompasses the identification of critical features of pressure signals sensed in the ear resulting from tongue motion and the development of algorithms and methodologies to extract features from sets of these signals...
Independent component analysis can be employed as an exploratory method in electroencephalographic (EEG) data analysis. However, the assumption of statistical independence among the estimated components is not always fulfilled by ICA-based numerical methods. Furthermore it may happen that one physiological source can be split in two or more components. As a consequence, the estimated components must...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.