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Piotr J Durka

Publications and source records attributed to Piotr J Durka.

12 recordsLinked to original sources
PubMed2006

Explicit parameterization of sleep EEG transients.

Adaptive time-frequency approximations, implemented via the matching pursuit algorithm, offer description of local signals structures in terms of their time occurrence and width, frequency and amplitude. This allows to construct explicit filters for finding EEG waveforms, known from the visual analysis, in the matching pursuit decomposition of signals. In such a way detectors of relevant structures of both transient and oscillatory nature can be constructed in the space of physically meaningful parameters. This study presents evaluation of changes of power and frequency of sleep spindles and delta waves, related to the depth of the sleep, which were previously assessed in a qualitative way. We confirm quantitatively the decrease of frequencies of sleep spindles and delta waves with the depth of the sleep.

Algorithms↗
PubMed2005

Multichannel matching pursuit and EEG inverse solutions.

We present a new approach to the preprocessing of the electroencephalographic time series for EEG inverse solutions. As the first step, EEG recordings are decomposed by multichannel matching pursuit algorithm--in this study we introduce a computationally efficient, suboptimal solution. Then, based upon the parameters of the waveforms fitted to the EEG (frequency, amplitude and duration), we choose those corresponding to the the phenomena of interest, like e.g. sleep spindles. For each structure, the corresponding weights of each channel define a topographic signature, which can be subject to an inverse solution procedure, like e.g. Loreta, used in this work. As an example, we present an automatic detection and parameterization of sleep spindles, appearing in overnight polysomnographic recordings. Inverse solutions obtained for single sleep spindles are coherent with the averages obtained for 20 overnight EEG recordings analyzed in this study, as well as with the results reported previously in literature as inter-subject averages of solutions for spectral integrals, computed on visually selected spindles.

Algorithms↗
PubMed2005

High resolution parametric description of slow wave sleep.

We propose a new framework for quantitative analysis of sleep EEG, compatible with the traditional analysis, based upon adaptive time-frequency approximation of signals. Using a high resolution description of EEG rhythms and transients in terms of their time occurrence and width, frequency and amplitude, we present a detailed detection and parameterization of delta waves, including also the time occupied by each delta wave-a parameter inaccessible directly by previously applied signal processing methods. To validate the proposed parameterization, we construct a simple detector of sleep stages 3 and 4, based explicitly upon the classical criteria related to delta waves. To properly compare its performance to the inter-expert agreements and other expert systems, we sort out and discuss the methodology of reporting concordance in this context. Since the proposed parameterization proves to be compatible with the visual analysis of EEG, we can derive new variables for quantitative analysis of EEG patterns recognized for decades. As examples, we present a continuous description of delta waves and sleep spindles in the overnight sleep, and compare results to the traditional FFT-based estimates.

Adult↗
PubMed2005

On the methodological unification in electroencephalography.

BACKGROUND: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. METHODS: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and applicability in various experimental and clinical setups. RESULTS: Four lemmas and three conjectures support the following conclusion. CONCLUSION: Adaptive time-frequency approximations of signals unify most of the univariate computational approaches to EEG analysis, and offer compatibility with its traditional (visual) analysis, used in clinical applications.

Action Potentials↗
PubMed2005

Time-frequency-space localization of epileptic EEG oscillations.

This paper presents a hybrid method for localization of oscillatory EEG activity. It consists of two steps: multichannel matching pursuit with complex Gabor dictionary, and LORETA inverse solution. Proposed algorithm was successfully applied to the localization of epileptogenic EEG in a single patient.

Algorithms↗
PubMed2004

Adaptive time-frequency parametrization of epileptic spikes.

Adaptive time-frequency approximations of signals have proven to be a valuable tool in electroencephalogram (EEG) analysis and research, where it is believed that oscillatory phenomena play a crucial role in the brain's information processing. This paper extends this paradigm to the nonoscillating structures such as the epileptic EEG spikes, and presents the advantages of their parametrization in general terms such as amplitude and half-width. A simple detector of epileptic spikes in the space of these parameters, tested on a limited data set, gives very promising results. It also provides a direct distinction between randomly occurring spikes or spike/wave complexes and rhythmic discharges.

Electroencephalography↗
PubMed2004

SignalML: metaformat for description of biomedical time series.

This paper introduces a complete and elegant solution to the problem of inherent incompatibility of different formats used for digital storage of biomedical time series (in particular EEG) and their annotations. We define a simple XML-based language, in which information on the structure of binary data files can be simply and efficiently coded. In most cases, description of an existing format takes relatively few lines of XML code. Once written, this information can be used by any software, which, owing to this meta-description, may read the original data files, thus eliminating the need for conversions and duplication of data. This proposition is hereby submitted to an open discussion within the community involved in relevant research, clinical and commercial applications. Links to the current version of the XML Schema defining the language and pilot implementation of a compliant viewer/annotator are located at http://eeg.pl/SignalML/.

Database Management Systems↗
PubMed2004

On the statistical significance of event-related EEG desynchronization and synchronization in the time-frequency plane.

We propose and discuss a complete framework for estimating significant changes in the average time-frequency density of energy of event-related signals. Addressed issues include estimation of time-frequency energy density (matching pursuit and spectrogram), choice of resampling statistics to test the hypothesis of change in one small region (resel), and correction for multiplicity (false discovery rate). We present estimation of the significance of event-related electroencephalograph desynchronization and synchronization (ERD/ERS) in the time-frequency plane.

Adult↗
PubMed2004

Identification of otoacoustic emissions components by means of adaptive approximations.

Clicks and a set of tone bursts covering the same frequency band were applied as a stimuli evoking otoacoustic emissions (OAE). Recorded otoacoustic emissions were decomposed into the basic waveforms by means of high-resolution adaptive time-frequency approximation method based on the matching pursuit algorithm. The method allows for description of the signal components in terms of frequencies, time occurrences, time spans, and energy. The analysis of OAE's energy density distributions in time-frequency space revealed that click responses can be considered as linear superpositions of responses to tone bursts, The frequency-latency relationship was studied and compared with earlier works. The method made possible the exhaustive description of the resonant modes specific for given subject/ear. They were characterized not only by the close frequencies appearing for different tones, but they usually had similar latencies and time spans. Short-time and long-time resonant modes were identified. The second ones might be connected with spontaneous emissions. The method opens new perspectives in studying the fine structure of the OAE and testing of the theoretical models.

Acoustic Stimulation↗
PubMed2003

From wavelets to adaptive approximations: time-frequency parametrization of EEG.

This paper presents a summary of time-frequency analysis of the electrical activity of the brain (EEG). It covers in details two major steps: introduction of wavelets and adaptive approximations. Presented studies include time-frequency solutions to several standard research and clinical problems, encountered in analysis of evoked potentials, sleep EEG, epileptic activities, ERD/ERS and pharmaco-EEG. Based upon these results we conclude that the matching pursuit algorithm provides a unified parametrization of EEG, applicable in a variety of experimental and clinical setups. This conclusion is followed by a brief discussion of the current state of the mathematical and algorithmical aspects of adaptive time-frequency approximations of signals.

Algorithms↗
PubMed2002

Adaptive time-frequency parametrization in pharmaco EEG.

Adaptive time-frequency approximations offer description of the local structures of a signal in terms of their time and frequency coordinates, widths and amplitudes. These parameters can then be used to select and study electroencephalogram (EEG) structures like sleep spindles or slow wave activity (SWA) with high resolution. Such a detailed description of relevant structures improves on the sensitivity of the traditionally used spectral power estimates and opens new possibilities of investigation. These advantages are illustrated using a double-blind test of the influence of zolpidem and midazolam on sleep EEG, and the results are compared with the traditional approach. The observed decrease of frequency of the SWA under the influence of sleep-inducing drugs gives an example of an effect elusive to classical methodology.

Action Potentials↗