ORCID Profile
0000-0002-8199-6000
Current Organisation
Information Technologies Institute
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Neural, Evolutionary and Fuzzy Computation | Artificial Intelligence and Image Processing
Application Software Packages (excl. Computer Games) | Computer Gaming Software |
Publisher: IEEE
Date: 04-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2009
Publisher: Elsevier BV
Date: 03-1999
DOI: 10.1016/S0933-3657(98)00055-4
Abstract: This study introduces new neural network based methods for the assessment of the dynamics of the heart rate variability (HRV) signal. The heart rate regulation is assessed as a dynamical system operating in chaotic regimes. Radial-basis function (RBF) networks are applied as a tool for learning and predicting the HRV dynamics. HRV signals are analyzed from normal subjects before and after pharmacological autonomic nervous system (ANS) blockade and from diabetic patients with dysfunctional ANS. The heart rate of normal subjects presents notable predictability. The prediction error is minimized, in fewer degrees of freedom, in the case of diabetic patients. However, for the case of pharmacological ANS blockade, although correlation dimension approaches indicate significant reduction in complexity, the RBF networks fail to reconstruct adequately the underlying dynamics. The transient attributes of the HRV dynamics under the pharmacological disturbance is elucidated as the explanation for the prediction inability.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2018
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2012
Publisher: IEEE
Date: 09-2009
Publisher: IEEE
Date: 07-2013
Publisher: Springer International Publishing
Date: 2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2003
Publisher: Elsevier BV
Date: 08-2010
DOI: 10.1016/J.CMPB.2009.11.003
Abstract: In this study, a pattern recognition system is presented for improving the classification accuracy of MS-spectra by means of gathering information from different MS-spectra intensity regions using a majority vote ensemble combination. The method starts by automatically breaking down all MS-spectra into common intensity regions. Subsequently, the most informative features (m/z values), which might constitute potential significant biomarkers, are extracted from each common intensity region over all the MS-spectra and, finally, normal from ovarian cancer MS-spectra are discriminated using a multi-classifier scheme, with members the Support Vector Machine, the Probabilistic Neural Network and the k-Nearest Neighbour classifiers. Clinical material was obtained from the publicly available ovarian proteomic dataset (8-7-02). To ensure robust and reliable estimates, the proposed pattern recognition system was evaluated using an external cross-validation process. The average overall performance of the system in discriminating normal from cancer ovarian MS-spectra was 97.18% with 98.52% mean sensitivity and 94.84% mean specificity values.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2001
DOI: 10.1109/72.925554
Abstract: The problem of maximizing the performance of the detection of ischemia episodes is a difficult pattern classification problem. The motivation for developing the supervising network self-organizing map (sNet-SOM) model is to exploit this fact for designing computationally effective solutions both for the particular ischemic detection problem and for other applications that share similar characteristics. Specifically, the sNet-SOM utilizes unsupervised learning for the "simple" regions and supervised for the "difficult" ones in a two stage learning process. The unsupervised learning approach extends and adapts the self-organizing map (SOM) algorithm of Kohonen. The basic SOM is modified with a dynamic expansion process controlled with an entropy based criterion that allows the adaptive formation of the proper SOM structure. This extension proceeds until the total number of training patterns that are mapped to neurons with high entropy reduces to a size manageable numerically with a capable supervised model. The second learning phase has the objective of constructing better decision boundaries at the ambiguous regions. At this phase, a special supervised network is trained for the computationally reduced task of performing the classification at the ambiguous regions only. The utilization of sNet-SOM with supervised learning based on the radial basis functions and support vector machines has resulted in an improved accuracy of ischemia detection especially in the last case. The highly disciplined design of the generalization performance of the support vector machine allows designing the proper model for the number of patterns transferred to the supervised expert.
Publisher: IEEE
Date: 08-2012
Publisher: World Scientific Pub Co Pte Lt
Date: 09-2012
DOI: 10.1142/S0218127412502252
Abstract: Electrocorticography (ECoG) is recorded directly on the exposed surface of cortex, and directional connectivity mapping of ECoG signal was proved essential in the definition of epileptogenic zones, and besides, could also be one kind of command source for Brain-Machine Interface (BMI) controlling. In this study, brain connectivity was evaluated and represented by directionality index, which was computed by phase based evolution map approach (EMA). In simulation study, directionality index and its short time correction were compared. The result showed that corrected algorithm had smaller variance and was more reasonable in cascade signal ensembles study. We applied this method to hand movement related human ECoG data, the primary motor cortex is found to have higher driving during the hand open-close movement onset than the baseline. By the experiments, the method could be further used to explore the alteration of information transfer and neural circuits during movement and could be the source for BMI tasks.
Publisher: Elsevier BV
Date: 2001
Publisher: Springer Science and Business Media LLC
Date: 06-2005
DOI: 10.1007/BF02345817
Publisher: Elsevier BV
Date: 02-2014
DOI: 10.1016/J.ULTRAS.2013.08.009
Abstract: A modulated acoustic radiation force, produced by two confocal tone-burst ultrasound beams of slightly different frequencies (i.e. 2.0 MHz ± Δf/2, where Δf is the difference frequency), can be used to remotely generate modulated low-frequency (Δf ≤ 500 Hz) shear waves in attenuating media. By appropriately selecting the duration of the two beams, the energy of the generated shear waves can be concentrated around the difference frequency (i.e., Δf ± Δf/2). In this manner, neither their litude nor their phase information is distorted by frequency-dependent effects, thereby, enabling a more accurate reconstruction of the viscoelastic properties. Assuming a Voigt viscoelastic model, this paper describes the use of a finite-element-method model to simulate three-dimensional (3-D) shear-wave propagation in viscoelastic media containing a spherical inclusion. Nonlinear propagation is assumed for the two ultrasound beams, so that higher harmonics are developed in the force and shear spectrum. Finally, an inverse reconstruction algorithm is used to extract 3-D maps of the local shear modulus and viscosity from the simulated shear-displacement fields based on the fundamental and second-harmonic component. The quality of the reconstructed maps is evaluated using the contrast between the inclusion and the background and the contrast-to-noise ratio (CNR). It is shown that the shear modulus can be accurately reconstructed based on the fundamental component, such that the observed contrast deviates from the true contrast by a root-mean-square-error (RMSE) of only 0.38 and the CNR is greater than 30 dB. If the second-harmonic component is used, the RMSE becomes 1.54 and the corresponding CNR decreases by approximately 10-15 dB. The reconstructed shear viscosity maps based on the second harmonic are shown to be of higher quality than those based on the fundamental. The effects of noise are also investigated and a fusion operation between the two spectral components is applied to enhance the reconstruction quality. Finally, a modified shear-wave spectroscopy technique, shown to be more robust to noise, is described for the estimation of the viscoelastic properties inside and outside the spherical inclusion under conditions of increased noise.
Publisher: Elsevier BV
Date: 08-2003
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2019
Publisher: Elsevier BV
Date: 09-2013
DOI: 10.1016/J.CMPB.2013.05.025
Abstract: The increasing flow of short time series microarray experiments for the study of dynamic cellular processes poses the need for efficient clustering tools. These tools must deal with three primary issues: first, to consider the multi-functionality of genes second, to evaluate the similarity of the relative change of litude in the time domain rather than the absolute values third, to cope with the constraints of conventional clustering algorithms such as the assignment of the appropriate cluster number. To address these, we propose OLYMPUS, a novel unsupervised clustering algorithm that integrates Differential Evolution (DE) method into Fuzzy Short Time Series (FSTS) algorithm with the scope to utilize efficiently the information of population of the first and enhance the performance of the latter. Our hybrid approach provides sets of genes that enable the deciphering of distinct phases in dynamic cellular processes. We proved the efficiency of OLYMPUS on synthetic as well as on experimental data. The discriminative power of OLYMPUS provided clusters, which refined the so far perspective of the dynamics of host response mechanisms to Influenza A (H1N1). Our kinetic model sets a timeline for several pathways and cell populations, implicated to participate in host response yet no timeline was assigned to them (e.g. cell cycle, homeostasis). Regarding the activity of B cells, our approach revealed that some antibody-related mechanisms remain activated until day 60 post infection. The Matlab codes for implementing OLYMPUS, as well as ex le datasets, are freely accessible via the Web (biosignal.med.upatras.gr/wordpress/biosignal/).
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2001
DOI: 10.1109/42.938245
Abstract: A novel speckle suppression method for medical ultrasound images is presented. First, the logarithmic transform of the original image is analyzed into the multiscale wavelet domain. We show that the subband decompositions of ultrasound images have significantly non-Gaussian statistics that are best described by families of heavy-tailed distributions such as the alpha-stable. Then, we design a Bayesian estimator that exploits these statistics. We use the alpha-stable model to develop a blind noise-removal processor that performs a nonlinear operation on the data. Finally, we compare our technique with current state-of-the-art soft and hard thresholding methods applied on actual ultrasound medical images and we quantify the achieved performance improvement.
Publisher: World Scientific Pub Co Pte Lt
Date: 12-2001
DOI: 10.1142/S0218127401004030
Abstract: We present a new probabilistic symmetric key encryption scheme based on the chaotic dynamics of properly designed chaotic systems. This technique exploits the concept of virtual attractors, which are not real attractors of the underlying chaotic dynamics but are created and maintained artificially. Each virtual attractor represents a symbol of the alphabet used to encode messages. The state space is partitioned over the virtual attractors creating clusters of states. The enciphering process randomizes over the set of states mapped to a virtual attractor in order to construct the ciphertext for the transmited symbol. The receiver can reconstruct perfectly this virtual state space, given the possession of the same chaotic system of difference equations with parameters tuned perfectly to those of the transmitter. Therefore, from the ciphertext chunk corresponding to a state, the virtual attractor can be derived from the details of the virtual state space. The knowledge of the virtual attractor leads to the recovery of the transmitted symbol. We demonstrate that the new algorithm is secure, reliable and very fast. It uses discrete time chaotic recurrent systems and is simple, flexible and modular. These systems can be constructed easily dynamically from an alphanumeric encryption key. The cryptographic security of the algorithm is evaluated with combinatorial arguments.
Publisher: IEEE
Date: 08-2010
Publisher: Elsevier BV
Date: 03-1999
Publisher: Springer International Publishing
Date: 2017
Publisher: Springer Berlin Heidelberg
Date: 2005
DOI: 10.1007/11560500_3
Publisher: American Physical Society (APS)
Date: 28-03-2002
Publisher: Elsevier BV
Date: 10-2007
Publisher: Elsevier BV
Date: 02-2014
DOI: 10.1016/J.ULTRAS.2013.07.009
Abstract: A localized modulated radiation force can be produced when two confocal ultrasound beams of nearly equal frequencies interfere in an attenuating medium such as tissue. It is well-established that this force generates both shear and longitudinal waves. By scanning the focal point over a plane and observing the propagation of these waves, the mechanical properties of the medium can be imaged. In this paper, the modulated radiation force is analytically derived in the case of attenuating media, by expanding on the theory of ultrasound-stimulated-vibro-acoustography (USVA) for lossless media. Furthermore, weak nonlinearities are considered in the formulation, since higher source pressures may prove to be necessary to improve the radiation-force profile - only the fundamental component is, however, studied in this paper. An analysis of the generated radiation force is performed and the effects of various parameters are investigated on its litude and spatial distribution. It will be shown that by carefully selecting the confocal geometry of the beams, as well as, the source pressure and center frequency, the spatial profile of the radiation force can be optimized. This, subsequently, could improve not only the resolution of the point-spread-function in USVA, but also, the profile of the shear waves in elastography applications.
Publisher: Wiley
Date: 24-04-2018
DOI: 10.1002/HBM.24192
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Springer Science and Business Media LLC
Date: 03-2007
DOI: 10.1007/S10548-007-0020-7
Abstract: Accumulating evidence suggests the existence of a shared neural substrate between imagined and executed movements. However, a better understanding of the mechanisms involved in the motor execution and motor imagery requires knowledge of the way the co-activated brain regions interact to each other during the particular (real or imagined) motor task. Within this general framework, the aim of the present study is to investigate the cortical activation and connectivity sub-serving real and imaginary rhythmic finger tapping, from the analysis of multi-channel electroencephalogram (EEG) scalp recordings. A sequence of 250 auditory pacing stimuli has been used for both the real and imagined right finger tapping task, with a constant inter-stimulus interval of 1.5 s length. During the motor execution, healthy subjects were asked to tap in synchrony with the regular sequence of stimulus events, whereas in the imagery condition subjects imagined themselves tapping in time with the auditory cue. To improve the spatial resolution of the scalp fields and suppress unwanted interferences, the EEG data have been spatially filtered. Further, event related synchronization and desynchronization phenomena and phase synchronization analysis have been employed for the study of functionally active brain areas and their connectivity during real and imagery finger tapping. Our results show a fronto-parietal co-activation during both real and imagined movements and similar connectivity patterns among contralateral brain areas. The results support the hypothesis that functional connectivity over the contralateral hemisphere during finger tapping is preserved in imagery. The approach and results can be regarded as indicative evidences of a new strategy for recognizing imagined movements in EEG-based brain computer interface research.
Publisher: Elsevier BV
Date: 07-2021
Publisher: IEEE
Date: 08-2012
Publisher: IEEE
Date: 08-2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2022
Publisher: Royal Society of Chemistry (RSC)
Date: 2008
DOI: 10.1039/B800446N
Abstract: The post-genomic era is flooded with data from high-throughput techniques such as cDNA microarrays. In the field of systems biology the reconstruction of gene regulatory networks from gene expression data is one of the major problems in understanding complex cell functions. Drawing conclusions from microarray data requires sophisticated computational analyses that will explore causal genetic relations. In this paper we provide a brief summary of some of the most recent and promising computational models and mathematical frameworks used to reconstruct, model and infer gene regulatory networks from data.
Publisher: Elsevier BV
Date: 07-2003
DOI: 10.1016/S1053-8119(03)00175-7
Abstract: The echoic memory trace (EMT) refers to neuronal activity associated with the short-term retention of stimulus-related information, especially within the primary and association auditory cortex. Using magnetoencephalography it is possible to determine quantitatively the lifetime of the EMT. Previous studies assumed that each new stimulus drives the EMT to its full strength, which then passively decays. In this study we show the limitations of this assumption using trains of auditory stimuli designed specifically for computing the EMT lifetime and its contextual sensitivity. We estimated a time-dependent EMT using a data-driven approach, which allows contributions from a relatively wide area around the auditory cortex in our quantitative measures. We identified: (1) internally generated cortical activations during the silent period between stimuli well separated in time from each other, which had influence on the morphology of the neuromagnetic response to the next external stimulus and (2) EMTs with different lifetimes that modulate the litude of the evoked responses at different latencies, suggesting the existence of multiple neural delay lines. Long EMT lifetimes were observed on the descending part of the M100 complex, which showed handedness and gender-dependent interhemispheric asymmetry. Specifically, all subjects showed longer EMT lifetimes on the left hemisphere, except left-handed males. Distributed source analysis of the data for one left- and one right-handed male subject identified a secondary generator in the right-handed subject, which was located posterior to the early primary generator and dominated the auditory response at late latencies, where EMT lifetime asymmetry was high. The identified multiple neural delay lines and their laterality may provide a link between macroneuronal activity and left hemisphere specialization for processing linguistic material.
Publisher: Elsevier BV
Date: 07-2008
DOI: 10.1016/J.JTBI.2008.03.004
Abstract: A mathematical model of calcium dynamics in vascular smooth muscle cell (SMC) was developed based on data mostly from rat mesenteric arterioles. The model focuses on (a) the plasma membrane electrophysiology (b) Ca2+ uptake and release from the sarcoplasmic reticulum (SR) (c) cytosolic balance of Ca2+, Na+, K+, and Cl ions and (d) IP3 and cGMP formation in response to norepinephrine(NE) and nitric oxide (NO) stimulation. Stimulation with NE induced membrane depolarization and an intracellular Ca2+ ([Ca2+]i) transient followed by a plateau. The plateau concentrations were mostly determined by the activation of voltage-operated Ca2+ channels. NE causes a greater increase in [Ca2+]i than stimulation with KCl to equivalent depolarization. Model simulations suggest that the effect of[Na+]i accumulation on the Na+/Ca2+ exchanger (NCX) can potentially account for this difference.Elevation of [Ca2+]i within a concentration window (150-300 nM) by NE or KCl initiated [Ca2+]i oscillations with a concentration-dependent period. The oscillations were generated by the nonlinear dynamics of Ca2+ release and refilling in the SR. NO repolarized the NE-stimulated SMC and restored low [Ca2+]i mainly through its effect on Ca2+-activated K+ channels. Under certain conditions, Na+-K+-ATPase inhibition can result in the elevation of [Na+]i and the reversal of NCX, increasing resting cytosolic and SR Ca2+ content, as well as reactivity to NE. Blockade of the NCX's reverse mode could eliminate these effects. We conclude that the integration of the selected cellular components yields a mathematical model that reproduces, satisfactorily, some of the established features of SMC physiology. Simulations suggest a potential role of intracellular Na+ in modulating Ca2+ dynamics and provide insights into the mechanisms of SMC constriction, relaxation, and the phenomenon of vasomotion. The model will provide the basis for the development of multi-cellular mathematical models that will investigate microcirculatory function in health and disease.
Publisher: IEEE
Date: 08-2012
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: IEEE
Date: 08-2010
Publisher: Elsevier BV
Date: 07-2005
DOI: 10.1016/J.MEDENGPHY.2004.12.005
Abstract: Ischemic preconditioning (IP) has been used as a strategy to prevent cell death in various organs, including the brain and the heart. Investigation of the effects of ischemic preconditioning mostly employed models with reduced complexity, such as cell cultures, tissue slices or perfused organ preparations. Although such models can provide valuable insight into the protective mechanism of preconditioning, the functional (re)organization of the control mechanisms at the level of the living organism cannot be assessed. The purpose of the present animal model study was to evaluate the effect of global ischemic preconditioning on the heart rate variability (HRV) response to the asphyxia insult. The data consisted of 4 h RR interval measurements recorded in five preconditioned and five non-preconditioned Wistar rats. Using linear (time and frequency domain) and nonlinear (approximate entropy and parameters of Poincare plots) measures, we evaluated the dynamic time course of the HRV response to the asphyxia insult and the effect of preconditioning on the autonomic neurocardiac control. Both the linear and nonlinear parameters indicate a faster recovery of the baseline HRV corresponding to the preconditioned groups, though only the spectral analysis identifies a statistically significant difference between the two groups. For the preconditioned group, at about 90 min after the asphyxic insult, the autonomic neural balance (measured by LF/HF ratio) appears fully recovered. The small variation of the rest of the parameters indicates the necessity of further investigation including the design of a larger study with a higher statistical power. Our results show for the first time that global ischemic preconditioning influences the HRV response to the asphyxia injury. The neuroprotective effect of preconditioning translates into a faster recovery of the basal HRV and the autonomic modulation of the heart.
Publisher: Springer Science and Business Media LLC
Date: 11-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2009
Publisher: Springer Science and Business Media LLC
Date: 23-10-2007
Abstract: Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI) networks. A key concept in the organization of PPI networks is the existence of dense subnetworks (functional modules) in them. In recent approaches clustering algorithms were applied at these networks and the resulting subnetworks were evaluated by estimating the coverage of well-established protein complexes they contained. However, most of these algorithms elaborate on an unweighted graph structure which in turn fails to elevate those interactions that would contribute to the construction of biologically more valid and coherent functional modules. In the current study, we present a method that corroborates the integration of protein interaction and microarray data via the discovery of biologically valid functional modules. Initially the gene expression information is overlaid as weights onto the PPI network and the enriched PPI graph allows us to exploit its topological aspects, while simultaneously highlights enhanced functional association in specific pairs of proteins. Then we present an algorithm that unveils the functional modules of the weighted graph by expanding a kernel protein set, which originates from a given 'seed' protein used as starting-point. The integrated data and the concept of our approach provide reliable functional modules. We give proofs based on yeast data that our method manages to give accurate results in terms both of structural coherency, as well as functional consistency.
Publisher: Oxford University Press (OUP)
Date: 16-11-2006
Abstract: The primary somatosensory cortex (SI) exhibits a detailed topographic organization of the hand and fingers, which has been found to undergo plastic changes following modifications of the sensory input. Although the spatial properties of these changes have been extensively investigated, little is known about their temporal dynamics. In this study, we adapted the paradigm of finger webbing, in which 4 fingers are temporarily webbed together, hence modifying their sensory feedback. We used magnetoencephalography, to measure changes in the hand representation in SI, before, during, and after finger webbing for about 5 h. Our results showed a decrease in the Euclidean distance (ED) between cortical sources activated by electrical stimuli to the index and small finger 30 min after webbing, followed by an increase lasting for about 2 h after webbing, which was followed by a return toward baseline values. These results provide a unique frame in which the different representational changes occur, merging previous findings that were only apparently controversial, in which either increases or decreases in ED were reported after sensory manipulation for relatively long or short duration, respectively. Moreover, these observations further confirm that the mechanisms that underlie cortical reorganization are extremely rapid in their expression and, for the first time, show how brain reorganization occurs over time.
Publisher: Springer Science and Business Media LLC
Date: 03-1993
DOI: 10.1007/BF00120392
Publisher: Springer International Publishing
Date: 2014
Publisher: Elsevier BV
Date: 07-2008
DOI: 10.1016/J.CLINPH.2008.02.021
Abstract: Aim of the current study is to provide electrophysiological evidence about the effects of moderate hypobaric hypoxia on human visual cognition. We investigate ERPs at occipitoparietal cortical areas in an ultra-rapid categorical discrimination task with psychomotor responses under the conditions of normoxia vs. moderate hypobaric hypoxia. Subjects had to produce motor response upon the categorization of target images containing animals, while suppress it for nontarget images containing only nonanimals. Statistical analysis on peak litudes and latencies of ERP components indicated significant: (i) attenuation of P1 and enhancement of N1-P3 litudes, (ii) delay of P2 latency for both stimuli whereas the delay of P3 latency only for nontargets, (iii) reduction in behavioral performance rates only for nontargets. For both categorical stimuli, impairment of early visual sensory and compensation through late cognitive processes was noticed. For targets, compensatory discrimination-categorization processes (reflected on P3 litudes) were sufficient to override our mild transient hypoxic challenge. For nontargets, differential P3 latencies and behavioral performance manifested the early impeding effects of systemic hypoxaemia. Evoked brain responses allow for early detection of subtle electrophysiological modulations coupled to cognitive-behavioral alterations, assessment of 'functional' hypobaric hypoxic sensitivity thresholds for 'altinauts' and reveal the susceptibilities of complex visuocognitive processes even to moderate hypoxic insults.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2004
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2003
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IOP Publishing
Date: 02-1998
DOI: 10.1088/0967-3334/19/1/007
Abstract: This study proposes a wavelet transform based technique to assess the beat-to-beat variation of the QRS signal in post-myocardial infarction patients with sustained monomorphic ventricular tachycardia. Recent electrophysiological investigations suggested that the diminished synchrony between the normal myocardium and the scarred arrhythmogenic tissue bordering a myocardial infarction area gives rise to beat-variable ECG signal components. Using a mathematical model of small variations in a largely repetitive waveform, we show that the inherent alignment errors (trigger jitter) of the high-resolution ECG (HRECG) can artificially increase the value of the time-domain beat-to-beat variance, making it less valuable as a marker of beat-variable signal components. To overcome this drawback, we propose the wavelet based approach which discriminates between the different factors responsible for the beat variability (the alignment error and the beat-variable signal components). The Morlet wavelet transform is performed on HRECG signals from normal in iduals (control group) and postmyocardial infarction patients with documented ventricular tachycardia. Electrical variability is quantitatively assessed via the beat-to-beat wavelet variance measurements. A marker of arrhythmogenic induced variance which achieves a good performance in discrimination of ventricular tachycardia patients from normal subjects was found between 200 Hz and 300 Hz. This finding is in agreement with the proposed mathematical model which states that the useful part of the time-frequency map is shifted upward in a precise mathematical way, as the variance induced by the beat-variable arrhythmogenic signals depend on the frequency characteristics of the first derivative of these signals. We conclude that the dynamics of the arrhythmogenic substrate as revealed by the beat-to-beat wavelet variance can be a new estimator of ventricular tachycardia risk.
Publisher: Elsevier BV
Date: 1990
DOI: 10.1016/0021-9290(90)90060-G
Abstract: The ability to monitor the healing of bone fractures is crucially important in their treatment. The aim of the present study was to develop and validate an objective method for monitoring fracture healing based on bone vibrational response. An analytic model was formulated, with which the mechanical parameters at the fracture site could be studied in relation to both lateral and axial bone vibration. Non-uniformities in the stiffness of the bone at the fracture site can be detected since they produce shifting of the vibration and the phase spectrum and result in strong coupling between the lateral and axial vibration response spectra. The validity of the model was tested in experiments using fresh cadaver tibiae with transverse osteotomy and materials simulating fracture callus. The results of the study of vibration litude and phase angle and the coupling of axial and lateral vibration in these experiments confirm our analytic projection. Preliminary results of in vivo investigations using the described method are encouraging.
Publisher: Elsevier BV
Date: 07-2001
DOI: 10.1016/S0165-0270(01)00366-1
Abstract: In experiments involving small animals, the electroencephalogram (EEG) recorded during severe injury and accompanying resuscitation exhibit the strong presence of electrocardiogram (ECG). For improved quantitative EEG (qEEG) analysis, it is therefore imperative to remove ECG interference from EEG. In this paper, we validate the use of independent component analysis (ICA) to effectively suppress the interference of ECG from EEG recordings during normal activity, asphyxia and recovery following asphyxia. Two channels of EEG from five rats were recorded continuously for 2 h. Simultaneous recording of one channel ECG was also made. Epochs of 4 s and 1 min were selected from baseline, asphyxia and recovery (every 10 min) and their independent components and power spectra were calculated. The improvement in normalized power spectrum of EEG obtained for all animals was 7.71+/-3.63 db at the 3rd minute of recovery and dropped to 1.15+/-0.60 db at 63rd minute. The application of ICA has been particularly useful when the power of EEG is low, such as that observed during early brain hypoxic-asphyxic injury. The method is also useful in situations where accurate indications of EEG signal power and frequency content are needed.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 07-2013
Publisher: Elsevier BV
Date: 04-2019
Publisher: MDPI AG
Date: 20-12-2022
Abstract: Cardiac arrest (CA) remains the leading cause of coma, and early arousal recovery indicators are needed to allocate critical care resources properly. High-frequency oscillations (HFOs) of somatosensory evoked potentials (SSEPs) have been shown to indicate responsive wakefulness days following CA. Nonetheless, their potential in the acute recovery phase, where the injury is reversible, has not been tested. We hypothesize that time-frequency (TF) analysis of HFOs can determine arousal recovery in the acute recovery phase. To test our hypothesis, eleven adult male Wistar rats were subjected to asphyxial CA (five with 3-min mild and six with 7-min moderate to severe CA) and SSEPs were recorded for 60 min post-resuscitation. Arousal level was quantified by the neurological deficit scale (NDS) at 4 h. Our results demonstrated that continuous wavelet transform (CWT) of SSEPs localizes HFOs in the TF domain under baseline conditions. The energy dispersed immediately after injury and gradually recovered. We proposed a novel TF-domain measure of HFO: the total power in the normal time-frequency space (NTFS) of HFO. We found that the NTFS power significantly separated the favorable and unfavorable outcome groups. We conclude that the NTFS power of HFOs provides earlier and objective determination of arousal recovery after CA.
Publisher: Springer Science and Business Media LLC
Date: 2002
Publisher: Elsevier BV
Date: 03-1997
DOI: 10.1016/S0168-5597(97)96681-8
Abstract: This technical note describes a robust version of moving averages, that enables reliable monitoring of the evoked potential (EP) signals. A cluster analysis (CA) procedure is introduced to robustify the signal averaging (SA). It is implemented via a Hopfield neural network (HNN), which performs selection of the trials forming a cluster around the current state of the EP signal. The core of this cluster serves as an estimate of the instantaneous EP. The effectiveness of the method, indicated by application to real data, and its computation efficiency, due to the use of simple matrix operations, makes it very promising for clinical observations.
Publisher: IOP Publishing
Date: 20-10-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 05-1997
DOI: 10.1016/S1386-5056(97)00019-1
Abstract: The fetal heart rate (FHR) signal provides valuable information for fetal development and well-being. However, the FHR traces derived from present-day ultrasound cardiotocographs are not of the desired quality. The paper applies the wavelet transform (WT) in order to denoise effectively the FHR signal. The denoising procedure analyses the evolution of the WT maxima across scales. The singularities of the signal create wavelet maxima with different properties from those of the induced noise. Since it is difficult to formulate precise rules that distinguish between the wavelet maxima of the FHR signal from those of the noise we have trained a neural network for this classification task. The neural network draws out successfully the noise induced wavelet maxima. An improved FHR signal can be obtained from the coarser wavelet approximation signal component and the filtered wavelet maxima by means of the inverse dyadic wavelet transform. Also, feature extraction and processing algorithms can be defined on the denoised wavelet coefficients (instead of on the original signal).
Publisher: Elsevier BV
Date: 1996
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2001
DOI: 10.1109/10.900247
Abstract: We developed a two-dimensional ventricular tissue model in order to probe the determinants of electrocardiographic (ECG) morphology during acute and chronic ischemia. Hyperkalemia was simulated by step changes in [K+]out, while acidosis was induced by reducing Na+ and Ca2+ conductances. Hypoxia was introduced by its effect on potassium activity. During the initial moments of ischemia, ECG changes were characterized by increases in QRS litude and ST segment shortening, followed in the advanced phase by ST baseline elevation, T conformation changes, widening of the QRS and significant decreases in QRS litude in spite of an enlarged Q. During each phase, potential proarrhythmic mechanisms were investigated. The presence of unexcitable regions of simulated myocardial infarction led to polymorphic ECG. We also observed a nonuniform deflection of the ST segment from beat to beat. We used similar protocols to explore the responses of infarcted myocardium after impairment resolving. We found that despite irreversible uncoupling of the necrotic region, the restored normal ionic concentrations produced an isopotential ST segment and monomorphic ECG complexes, while an enlarged Q wave was still visible. In summary, these numerical experiments indicate the possibility to track in the ECG pathologic changes following the altered electrophysiology of the ischemic heart.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
Publisher: Springer Science and Business Media LLC
Date: 2002
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: IEEE
Date: 10-2007
Publisher: Elsevier BV
Date: 02-2000
DOI: 10.1016/S1388-2457(99)00248-5
Abstract: The scalp recorded transient visual evoked potential (VEP) represents the massed activity of a large number of neurons of the human visual cortex. Animal studies show that intracerebrally-recorded high frequency electrical activity represents binding between neurons participating in a cooperative response. We evaluated the relationship between scalp recorded high frequency activity and transient VEPs elicited by a repetitive (grating) pattern. Stimuli were 1 and 4 cycles/degree sinusoidal gratings, presented in an on/off mode. Following conventional averaging, the discrete wavelet transform (DWT) was applied. Multi-resolution decomposition was used to ide the responses into 6 orthogonal frequency bands. The results show that high frequency oscillatory activity in the beta and gamma frequency range is closely related in time to the N70 peak of the simultaneous VEP. Power in both bands is modulated by spatial frequency. Beta range response to hemifield stimulation recorded over a chain of electrodes over the occipital area lateralizes in the same manner as N70, while gamma range activity is insensitive to lateralization and is more closely linked to foveal stimulation. This dissociation between beta and gamma range activity suggests that different bands of high frequency oscillatory activity in humans, linked to visual stimulation, may represent different aspects of visual processing.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: World Scientific Pub Co Pte Lt
Date: 10-1996
DOI: 10.1142/S0218127496001132
Abstract: We characterise a model of the sinoatrial node, the pacemaker of the heart, by its response to brief current pulses by a family of phase transition curves. These circle maps are used to describe the effects of acetylcholine on the sensitivity of the pacemaker to perturbations.
Publisher: IOP Publishing
Date: 02-06-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1997
DOI: 10.1109/12.559800
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Elsevier BV
Date: 02-2013
DOI: 10.1016/J.ULTRAS.2012.09.010
Abstract: Modulated low-frequency shear waves can be non-invasively generated locally within a medium, by the oscillatory acoustic radiation force resulting from the interference of two focused quasi-CW ultrasound beams of slightly different frequencies. The propagation of such shear waves within a viscoelastic medium is known to be affected by the dispersive effects of viscosity. Specifically, a low-frequency (LF) spectral component was shown to arise with increased viscosities and higher modulation frequencies and appear as a 'slow' wave at the end of the shear waveform. In this paper, the shear dispersion characteristics are studied based on the Pseudo-Wigner-Ville distribution (PWVD) in the time-frequency domain. The ridges of the PWVD are then extracted and used to calculate the frequency-dependent shear speed, by identifying the LF dispersive component both in time and frequency. Using numerical simulations, it is shown that this way of estimating the shear dispersion is more efficient and robust than the conventional phase-delay Fourier method. Thus, more accurate estimates of the local shear modulus and viscosity of the propagating medium could be achieved. The effects of noise on the proposed method are also discussed.
Publisher: MDPI AG
Date: 07-02-2023
DOI: 10.3390/APP13042129
Abstract: Mental workload has a major effect on the in idual’s performance in most real-world tasks, which can lead to significant errors in critical operations. On this premise, the analysis and assessment of mental workload attain high research interest in both the fields of Neuroergonomics and Neuroscience. In this work, we implemented an EEG experimental design consisting of two distinct mental tasks (mental arithmetic task, n-back task), each with two conditions of complexity (low and high) to investigate the task-related and task-unrelated workload effects. Since mental workload is an intricate phenomenon involving multiple brain areas, we performed a graph theoretical analysis estimating the Phase Locking Index (PLI) in four frequency bands (delta, theta, alpha, beta). The brainwave-dependent network results show statistically significant reductions in clustering coefficient, characteristic path length, and small-worldness metrics with higher workload in both tasks across several bands. Moreover, functional connectivity analysis indicates a task-independent fashion of the brain topological re-organization with increasing mental load. These results revealed how the brain network is re-organized with increasing mental workload in a task-independent way. Finally, the network metrics were used as classification features, leading to high performance in workload level discrimination.
Publisher: S. Karger AG
Date: 18-12-1999
DOI: 10.1159/000013818
Abstract: This paper describes a wavelet-transform-based system for the V wave identification in brainstem auditory evoked potentials (BAEP). The system combines signal denoising and rule-based localization modules. The signal denoising module has the potential of effective noise reduction after signal averaging. It analyses adaptively the evolution of the wavelet transform maxima across scales. The singularities of the signal create wavelet maxima with different properties from those of the induced noise. A non-linear filtering process implemented with a neural network extracts out the noise-induced maxima. The filtered wavelet details are subsequently analysed by the rule-based localization module for the automatic identification of the V wave. In the first phase, it implements a set of statistical observations as well as heuristic criteria used by human experts in order to classify the IV–V complex. At the second phase, using a multiscale focusing algorithm, the IV and V waves are positioned on the BAEP signal. Our experiments revealed that the system provides accurate results even for signals exhibiting unclear IV–V complexes.
Publisher: Elsevier BV
Date: 03-2002
Publisher: IEEE
Date: 10-2011
Publisher: Elsevier BV
Date: 1998
DOI: 10.1016/S0730-725X(97)00218-X
Abstract: A new method using magnetic resonance phase images for the assessment of trabecular bone structure has recently been proposed. To test this method, a mathematical model is developed which calculates the phase distribution in gradient echo acquired phase images of a structure of Pyrex glass rods immersed in a copper sulfate solution. Several experiments were performed using a phantom built in the same way as the structure used in the mathematical model. The results from the model are compared with those from the phantom tests, and the influence of resolution and bone area fraction on the phase dispersion is studied. The good correlation between theoretical and experimental results shows that phase variance increases with increasing resolution and bone density. However, the dependence of variance on bone density is less prominent for large pixel sizes.
Publisher: Cold Spring Harbor Laboratory
Date: 25-05-2020
DOI: 10.1101/2020.05.22.20109330
Abstract: A major challenge for controlling a prosthetic arm is communication between the device and the user’s phantom limb. We show the ability to enhance utees’ phantom limb perception and improve movement decoding through targeted transcutaneous electrical nerve stimulation (tTENS). Transcutaneous nerve stimulation experiments were performed with four utee participants to map phantom limb perception. We measured myoelectric signals during phantom hand movements before and after utees received sensory stimulation. Using electroencephalogram (EEG) monitoring, we measure the neural activity in sensorimotor regions during phantom movements and stimulation. In one participant, we also tracked sensory mapping over 2 years and movement decoding performance over 1 year. Results show improvements in the utees’ ability to perceive and move the phantom hand as a result of sensory stimulation, which leads to improved movement decoding. In the extended study with one utee, we found that sensory mapping remains stable over 2 years. Remarkably, sensory stimulation improves within-day movement decoding while performance remains stable over 1 year. From the EEG, we observed cortical correlates of sensorimotor integration and increased motor-related neural activity as a result of enhanced phantom limb perception. This work demonstrates that phantom limb perception influences prosthesis control and can benefit from targeted nerve stimulation. These findings have implications for improving prosthesis usability and function due to a heightened sense of the phantom hand.
Publisher: Springer Science and Business Media LLC
Date: 11-1987
DOI: 10.1007/BF02588648
Abstract: To investigate the outcome of IVF following intracytoplasmic sperm injection (ICSI) from ejaculate, percutaneous epididymal sperm aspiration (PESA) and testicular sperm extraction (TESE), with subsequent blastocyst culture and single blastocyst transfer. Single blastocyst transfer was performed after ejaculate ICSI (oligozoospermia) in 587 patients, TESE/PESA (azoospermia) in 31 patients, and standard IVF in 680 women. There were only minor differences in IVF characteristics between the standard IVF and the PESA-TESE couples. Couples where ejaculate ICSI were performed seemed to represent a slightly poorer prognostic group. A viable fetus after the 12th gestational week, i.e. ongoing pregnancy, was present in 41.4% after ICSI/ET, 51.6% after PESA-TESE/ET and in 40.4% after standard IVF/ET (no significant differences). Single blastocyst transfer after ejaculate ICSI or after PESA/TESE appears to give similar results as conventional IVF blastocyst culture.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-1995
DOI: 10.1109/10.376138
Abstract: The ensemble average of Pattern Shift Visual Evoked Potentials (PSVEP) signals is seriously affected by random latency variations encountered in each in idual sweep which is modeled as a continuous signal with linear segments and well-shaped triangular peaks. This effect is causing the smoothed peaks of the averaged PSVEP waveforms. It is our objective to restore the degraded peaks and provide accurate information about their exact location. The method used is based on nonlinear filtering of the FIR-Median Hybrid (FMH) type and is recommended as a postfiltering process to the well-known averaging methods of recovering PSVEP signals from noise by time-locking to stimuli. The new technique, tested in signals from clinical observations, has proven very promising.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2012
Publisher: Wiley
Date: 09-2009
Abstract: EuroKUP (Urine and Kidney Proteomics www.eurokup.org) is a COST (European Cooperation in the field of Scientific and Technical research: www.cost.esf.org Action fostering a multi-disciplinary network of investigators from 25 countries and focusing on facilitating translational proteomic research in kidney diseases. Four Working Groups focusing respectively on defining clinically important research questions in kidney diseases, kidney tissue proteomics, urine proteomics and bioinformatics have been generated. The EuroKUP members had their second combined Working Group and Management Committee (MC) meeting in Nafplio, Greece from March 29 to 30, 2009. This report summarizes the main presentations, discussions and agreed action points during this meeting. These refer to the design of collaborative projects and clinical center networks for specific kidney diseases establishment of guidelines for kidney tissue proteomics analysis by laser-based imaging- and laser capture microdissection-MS development and characterization of a "standard" urine specimen to be used for assessment of platform capability and data comparability in clinical proteomics applications definition of statistical requirements in biomarker discovery studies and development of a specialized kidney and urine ontology. Various training activities are planned involving training schools on laser capture microdissection- and imaging-MS, workshops on ontologies as well as short-term travel grants for junior investigators.
Publisher: Hindawi Limited
Date: 2004
DOI: 10.1002/CFG.444
Abstract: Gene expression datasets are large and complex, having many variables and unknown internal structure. We apply independent component analysis (ICA) to derive a less redundant representation of the expression data. The decomposition produces components with minimal statistical dependence and reveals biologically relevant information. Consequently, to the transformed data, we apply cluster analysis (an important and popular analysis tool for obtaining an initial understanding of the data, usually employed for class discovery). The proposed self-organizing map (SOM)-based clustering algorithm automatically determines the number of ‘natural’ subgroups of the data, being aided at this task by the available prior knowledge of the functional categories of genes. An entropy criterion allows each gene to be assigned to multiple classes, which is closer to the biological representation. These features, however, are not achieved at the cost of the simplicity of the algorithm, since the map grows on a simple grid structure and the learning algorithm remains equal to Kohonen’s one.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Elsevier BV
Date: 1999
DOI: 10.1016/S1386-5056(98)00102-6
Abstract: Many studies on the physiology of the cardiovascular system revealed that nonlinear chaotic dynamics govern the generation of the heart rate signal. This is also valid for the fetal heart rate (FHR) variability, where however the variability is affected by many more factors and is significantly more complicated than for the adult case. Recently an adaptive wavelet denoising method for the Doppler ultrasound FHR recordings has been introduced. In this paper the performance and reliability of that method is confirmed by the observation that for the wavelet denoised FHR signal, a deterministic nonlinear structure, which was concealed by the noise, becomes apparent. It provides strong evidence that the denoising process removes actual noise components and can therefore be utilized for the improvement of the signal quality. Hence by observing after denoising a significant improvement of the 'chaoticity' of the FHR signal we obtain strong evidence for the reliability and efficiency of the wavelet based denoising method. The estimation of the chaoticity of the FHR signal before and after the denoising is approached with three nonlinear analysis methods. First, the rescaled scale analysis (RSA) technique reveals that the denoising process increases the Hurst exponent parameter as happens when additive noise is removed from a chaotic signal. Second, the nonlinear prediction error evaluated with radial basis function (RBF) prediction networks is significantly lower at the denoised signal. The significant gain in predictability can be attributed to the drastic reduction of the additive noise from the signal by the denoising algorithm. Moreover, the evaluation of the correlation coefficient between actual and neural network predicted values as a function of the prediction time displays characteristics of chaos only for the denoised signal. Third, a chaotic attractor, reconstructed with the embedding dimension technique, becomes evident for the denoised signal, while it is completely obscured for the original signals. The correlation dimension of the reconstructed attractor for the denoised signal tends to reach a value independent of the embedding dimension, a sign of deterministic chaotic signal. In contrast for the original signal the correlation dimension increases steadily with the embedding dimension, a fact that indicates strong contribution of noise.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institution of Engineering and Technology (IET)
Date: 2007
Abstract: Reverse engineering problems concerning the reconstruction and identification of gene regulatory networks through gene expression data are central issues in computational molecular biology and have become the focus of much research in the last few years. An approach has been proposed for inferring the complex causal relationships among genes from microarray experimental data, which is based on a novel neural fuzzy recurrent network. The method derives information on the gene interactions in a highly interpretable form (fuzzy rules) and takes into account the dynamical aspects of gene regulation through its recurrent structure. To determine the efficiency of the proposed approach, microarray data from two experiments relating to Saccharomyces cerevisiae and Escherichia coli have been used and experiments concerning gene expression time course prediction have been conducted. The interactions that have been retrieved among a set of genes known to be highly regulated during the yeast cell-cycle are validated by previous biological studies. The method surpasses other computational techniques, which have attempted genetic network reconstruction, by being able to recover significantly more biologically valid relationships among genes.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2016
Publisher: Wiley
Date: 12-2009
Publisher: Springer International Publishing
Date: 2014
Publisher: Wiley
Date: 11-2009
Publisher: Springer Science and Business Media LLC
Date: 16-08-2016
Publisher: Springer Science and Business Media LLC
Date: 02-2003
DOI: 10.1114/1.1541013
Abstract: Our approach is motivated by the need to generate a rigorous measure of the degree of disorder (or complexity) of the EEG signal in brain injury. Entropy is a method to quantify the order/disorder of a time series. It is the first time that a time-dependent entropy (TDE) is used in the quantification of brain injury level. The TDE was sensitive enough to monitor the significant changes in the subject's brain rhythms during recovery from global ischemic brain injury. Among the different entropy measures, we used Tsallis entropy. This entropy is parametrized and is able to match with the particular properties of EEG, like long-range rhythms, spikes, and bursts. The method was tested in a signal composed of segments of synthetic signals (Gaussian and uniform distributions) and segments of real signals. The real signal segments were extracted from normal EEG, EEG recordings from early recovery, and normal EEG corrupted by simulated spikes and bursts. Adult Wistar rats were subjected to asphyxia-cardiac arrest for 3 and 5 min. The TDE detected the pattern of ischemia-induced EEG alterations and was able to discriminate the different injury levels. Two parameters seem to be good descriptors of the recovery process the mean entropy and the variance of the estimate followed opposite trends, with the mean entropy decreasing and its variance increasing with injury.
Location: Greece
Start Date: 2016
End Date: 12-2021
Amount: $560,000.00
Funder: Australian Research Council
View Funded Activity