Biomedical subjects

H Witte

Publications and source records attributed to H Witte.

At least 19 recordsLinked to original sources

PubMed2006

Time-variant parametric estimation of transient quadratic phase couplings between heart rate components in healthy neonates.

The heart rate variability (HRV) can be taken as an indicator of the coordination of the cardio-respiratory rhythms. Bispectral analysis using a direct (fast Fourier transform based) and time-invariant approach has shown the occurrence of a quadratic phase coupling (QPC) between a low-frequency (LF: 0.1 Hz) and a high-frequency (HF: 0.4-0.6 Hz) component of the HRV during quiet sleep in healthy neonates. The low-frequency component corresponds to the Mayer-Traube-Hering waves in blood pressure and the high-frequency component to the respiratory sinus arrhythmia (RSA). Time-variant, parametric estimation of the bispectrum provides the possibility of quantifying QPC in the time course. Therefore, the aim of this work was a parametric, time-variant bispectral analysis of the neonatal HRV in the same neonates used in the direct, time-invariant approach. For the first time rhythms in the time course of QPC between the HF component and the LF component could be shown in the neonatal HRV.

Arrhythmia, Sinus↗

PubMed2006

Electrical stimulation of the energy metabolism in yeast cells using a planar Ti-Au-electrode interface.

We report on the influence of dielectric pulse injection on the energy metabolism of yeast cells with a planar interdigitated electrode interface. The energy metabolism was measured via NADH fluorescence. The application of dielectric pulses results in a distinct decrease of the fluorescence, indicating a response of the energy metabolism of the yeast cells. The reduction of the NADH signal significantly depends on the pulse parameters, i.e., amplitude and width. Furthermore, the interface is used to detect electrical changes in the cell-electrolyte system, arising from glucose-induced oscillations in yeast cells and yeast extract, by dielectric spectroscopy at 10 kHz. These dielectric investigations revealed a beta(1)-dispersion for the system electrolyte/yeast cells as well as for the system electrolyte/yeast extract. In agreement with control measurements we obtained a glycolytic period of 45 s for yeast cells and of 11 min for yeast extract.

Electric Conductivity↗

PubMed2006

Sensor, signal, and image informatics - state of the art and current topics.

OBJECTIVES: The number of articles published annually in the fields of biomedical signal and image acquisition and processing is increasing. Based on selected examples, this survey aims at comprehensively demonstrating the recent trends and developments. METHODS: Four articles are selected for biomedical data acquisition covering topics such as dose saving in CT, C-arm X-ray imaging systems for volume imaging, and the replacement of dose-intensive CT-based diagnostic with harmonic ultrasound imaging. Regarding biomedical signal analysis (BSA), the four selected articles discuss the equivalence of different time-frequency approaches for signal analysis, an application to Cochlea implants, where time-frequency analysis is applied for controlling the replacement system, recent trends for fusion of different modalities, and the role of BSA as part of a brain machine interfaces. To cover the broad spectrum of publications in the field of biomedical image processing, six papers are focused. Important topics are content-based image retrieval in medical applications, automatic classification of tongue photographs from traditional Chinese medicine, brain perfusion analysis in single photon emission computed tomography (SPECT), model-based visualization of vascular trees, and virtual surgery, where enhanced visualization and haptic feedback techniques are combined with a sphere-filled model of the organ. RESULTS: The selected papers emphasize the five fields forming the chain of biomedical data processing: (1) data acquisition, (2) data reconstruction and pre-processing, (3) data handling, (4) data analysis, and (5) data visualization. Fields 1 and 2 form the sensor informatics, while fields 2 to 5 form signal or image informatics with respect to the nature of the data considered. CONCLUSIONS: Biomedical data acquisition and pre-processing, as well as data handling, analysis and visualization aims at providing reliable tools for decision support that improve the quality of health care. Comprehensive evaluation of the processing methods and their reliable integration in routine applications are future challenges in the field of sensor, signal and image informatics.

Diagnostic Imaging↗

PubMed2006

Time-variant analysis of fast-fMRI and dynamic contrast agent MRI sequences as examples of 4-dimensional image analysis.

OBJECTIVES: Image sequences with time-varying information content need appropriate analysis strategies. The exploration of directed information transfer (interactions) between neuronal assemblies is one of the most important aims of current functional MRI (fMRI) analysis. Additionally, we examined perfusion maps in dynamic contrast agent MRI sequences of stroke patients. In this investigation, the focus centers on distinguishing between brain areas with normal and reduced perfusion on the basis of the dynamics of contrast agent inflow and washout. METHODS: Fast fMRI sequences were analyzed with time-variant Granger causality (tvGC). The tvGC is based on a time-variant autoregressive model and is used for the quantification of the directed information transfer between activated brain areas. Generalized Dynamic Neural Networks (GDNN) with time-variant weights were applied on dynamic contrast agent MRI sequences as a nonlinear operator in order to enhance differences in the signal courses of pixels of normal and injured tissues. RESULTS: A simple motor task (self-paced finger tapping) is used in an fMRI design to investigate directed interactions between defined brain areas. A significant information transfer can be determined for the direction primary motor cortex to supplementary motor area during a short time period of about five seconds after stimulus. The analysis of dynamic contrast agent MRI sequences demonstrates that the trained GDNN enables a reliable tissue classification. Three classes are of interest: normal tissue, tissue at risk for death, and dead tissue. CONCLUSIONS: The time-variant multivariate analysis of directed information transfer derived from fMRI sequences and the computation of perfusion maps by GDNN demonstrate that dynamic analysis methods are essential tools for 4D image analysis.

Cerebrovascular Circulation↗

PubMed2005

Musculoskeletal support of lumbar spine stability.

Using a biomechanical model and experimental data the self-stabilising behaviour of antagonistic trunk muscles was analyzed. The biomechanical model is constituted of a pair of antagonistic Hill-type muscles, their geometric arrangement with respect to the spine, and the instantaneous centre of rotation in frontal plane. Using Ljapunov's theory, the stability of certain motion and loading situations was analyzed. Applying a sensitivity analysis, the influence of different muscle properties and the geometric arrangement on stability was investigated. The simulations revealed that the stability of spinal movements depended primarily on the geometrical arrangement of muscles and the position of the centre of rotation of the spine, the latter was affected in turn by the activities of the profound muscles. To stabilize the situations simulated oblique muscle arrangements were necessary. In order to define an instantaneous centre of rotation in the lower region of the spine negative attachment angles (medio-lateral decline) of muscles were necessary, corresponding to the real anatomy of obliquus externus muscles. More cranially located instantaneous centres of rotation required positive attachment angles for stability, corresponding to obliquus internus or multifidus muscles. Furthermore, the fibre-type distribution of muscles influenced the stability of the system, i.e. a high percentage of fast-twitch-fibres supported the stabilisation. Conclusions drawn from the simulations were supported by experimental data. Sudden loads and quick-release perturbations with two different amplitudes were applied to the upper body of ten male subjects. In comparison to sudden load situations preactivation of muscles due to an external load, i.e. quick-release perturbation, led to significantly less dependency of the amplitude of deflection on the amplitude of the perturbation. This observation relates to the self-stabilising properties of the musculoskeletal system. In conclusion, training seems to be advantageous if directed towards not only enhancing the endurance capacity of the muscles, but also increasing the cross-sectional area of oblique fast-twitch-fibres. Training should also improve the co-ordination of deep and superficial trunk muscles. These findings may influence physiotherapy and training programs for low back pain patients.

Journal Article↗

PubMed2005

Methods for parameter identification in oscillatory networks and application to cortical and thalamic 600 Hz activity.

Directed information transfer in the human brain occurs presumably by oscillations. As of yet, most approaches for the analysis of these oscillations are based on time-frequency or coherence analysis. The present work concerns the modeling of cortical 600 Hz oscillations, localized within the Brodmann Areas 3b and 1 after stimulation of the nervus medianus, by means of coupled differential equations. This approach leads to the so-called parameter identification problem, where based on a given data set, a set of unknown parameters of a system of ordinary differential equations is determined by special optimization procedures. Some suitable algorithms for this task are presented in this paper. Finally an oscillatory network model is optimally fitted to the data taken from ten volunteers.

Cerebral Cortex↗

PubMed2005

Time-variant parametric estimation of transient quadratic phase couplings during electroencephalographic burst activity.

OBJECTIVES: Electroencephalographic burst activity characteristic of burst-suppression pattern (BSP) in sedated patients and of burst-interburst pattern (BIP) in the quiet sleep of healthy neonates have similar linear and non-linear signal properties. Strong interrelations between a slow frequency component and rhythmic, spindle-like activities with higher frequencies have been identified in previous studies. Time-varying characteristics of BSP and BIP prevent a definite patternrelated analysis. A continuous estimation of the bispectrum is essential to analyze these patterns. Parametric bispectral approaches provide this opportunity. METHODS: The adaptation of an AR model leads to a parametric bispectrum by using the transfer function of the estimated AR filter. Time-variant parametric bispectral approaches require an estimation of AR parameters which consider higher order moments to preserve phase information. Accordingly, a time-variant parametric estimation of the bispectrum was introduced. Data driven simulations were performed to provide optimal parameters. BSP (12 patients) and BIP (6 neonates) were analyzed using this novel approach. RESULTS: Significant differences in the time course of burst pattern during BSP and burst-like pattern before the onset of BSP could be shown. A rhythmic quadratic phase coupling (period 10 sec) was identified during BIP in all neonates. CONCLUSION: Quadratic phase couplings during BSP increases in the time course depending on depth of sedation. The visually detected burst activity in BIP is only the temporarily observable EEG correlate of a hidden neural process. Time-variant bispectral approaches offer the possibility of a better characterization of underlying neural processes leading to improved diagnostic tools used in clinical routine.

Algorithms↗

PubMed2004

Dyslexia: the possible benefit of multimodal integration of fMRI- and EEG-data.

Biological research about dyslexia has been conducted using various neuroimaging methods like functional Magnetic Resonance Imaging (fMRI) or Electroencephalography (EEG). Since language functions are characterized by both distributed network activities and speed of processing within milliseconds, high temporal as well as high spatial resolution of activation profiles are of interest: "where" can dyslexia specific activations be detected and "when" do language processes start to diverge between dyslexics and controls? Due to the network character of language processing, fMRI-constrained distributed source models based on EEG-data were computed for multimodal data integration. First single-case results show that this method could be a promising approach for the understanding of a repeatedly described experimental finding for dyslexia like that of an overactivation in inferior frontal language areas. Multimodal data analysis for the subjects presented here could probably demonstrate that inferior frontal overactivations are the consequence of a phonological deficit and could represent ongoing articulation processes used to solve phonologically challenging tasks.

Adolescent↗

PubMed2004

On the spatio-temporal organisation of quadratic phase-couplings in 'tracé alternant' EEG pattern in full-term newborns.

OBJECTIVE: The time courses of quadratic phase-coupling (QPC) of electroencephalographic burst and interburst patterns of the 'trace alternant' (TA) in full-term newborns have been quantified. METHODS: Using the Gabor expansion, a fast Fourier transformation based method, biamplitude, bicoherence and phase-bicoherence time courses of both burst and interburst patterns have been determined (common average reference EEG recordings). With a frequency resolution of 0.25 Hz and a frequency grid of 1-1.5 <==> 3.5-4.5 Hz (region-of-interest), a number of 15 frequency pairs result. These pairs have been investigated. RESULTS: The burst and the interburst patterns are characterized by temporally and topographically different QPC profiles. All differences are dominant at the electrode Fp1 followed by Fp2. There is a significant difference (combined multiple and global test strategy) in the QPC characteristics between both patterns within the time period from 0.75 to 1.5 s after the pattern onset at electrode Fp1. The maximal QPC in burst patterns (especially at Fp1) can be observed during this time period. In contrast to this finding, maximal QPC in interburst patterns (at Fp1) are reached immediately after the onset and at 3 s. Summarising all findings, a QPC-rhythm of 0.1 Hz during TA can be assumed. CONCLUSIONS: It can be assumed that the QPC rhythm of the TA is generated by a pattern-spanning time-variant phase-locking process and there are indications for a possible correspondence between the QPC rhythm and vegetative rhythms. SIGNIFICANCE: This study showed that advanced, time-variant analysis methods quantifying QPC rhythms are able to add new scientific information to the understanding of nature, characteristics and significance of TA in the neonatal EEG.

Algorithms↗

PubMed2002

[What influence do size and placement of patella resurfacing have on knee endoprosthesis?].

The aim of this study was to document the changes in retropatellar pressure, contact area and forces due to different sizes and placement of the patella resurfacing in knee arthroplasty. Six cadaver specimens (after Thiel fixation) were examined after the implantation of the total knee arthroplasty Genesis I. The patella sizes "small" and "medium" were placed as the "onlay" version, centered as well as off-centered by 0.4 cm in all four directions. Pressure and area measurements were done with Fuji pressure measuring film, which was placed between the patellar fascia of the femur and the patella in a defined position. The pressure was measured by applying a predetermined force for 5 s. The examinations were done with 60 degrees knee flexion and a force of 280 N. In our results there were no significant differences between, patella sizes. No significant differences for the medial, distal and proximal placement were found for the small patella. The lateral placement led to a significant decrease in the contact area (P = 0.0277), maximum pressure (P = 0.0422) and force (P = 0.0277). The average pressure did not change significantly (P = 0.1159). For the medium size patella there were no significant differences for medial or distal placement. The comparison of lateral and central placement revealed a significant decrease in the contact area (P = 0.0446). Comparing distal and proximal positioning, a significant increase in contact area and significant decrease in force were found (P = 0.0277 and P = 0.0277 respectively). In conclusion, the choice of small or medium patella resurfacing does not seem to have a significant influence. In comparison to the results without patella implants, the implantation of the small patella caused a significant decrease in the retropatellar contact area (P = 0.03) and force (P = 0.03). Average and maximum pressure did not change significantly (P = 0.6 and P = 0.35) even though pressure increased slightly. For the medium size, maximum pressure (P = 0.03) increased significantly and force decreased significantly (P = 0.0277) whereas contact area and average pressure increased slightly. The results of the different placements of the patella implant do not support the recommendation for a medial shift. However, at least the lateralized implantation led to a reduction of contact area and force as well as to a slight increase of pressure which is considered as unfavorable.

Aged↗

PubMed2002

Prediction of movement following noxious stimulation during 1 minimum alveolar anesthetic concentration isoflurane/nitrous oxide anesthesia by means of middle latency auditory evoked responses.

This paper investigates the applicability of generalized dynamic neural networks for the design of a two-valued anesthetic depth indicator during isoflurane/nitrous oxide anesthesia. The indicator construction is based on the processing of middle latency auditory evoked responses (MLAER) in combination with the observation of the patient's movement reaction to skin incision. The framework of generalized dynamic neural networks does not require any data preprocessing, visual data inspection or subjective feature extraction. The study is based on a data set of 106 patients scheduled for elective surgery under isoflurane/nitrous oxide anesthesia. The processing of the measured MLAER is performed by a recurrent neural network that transforms the MLAER signals into signals having a very uncomplex structure. The evaluation of these signals is self-evident, and yields to a simple threshold classifier. Using only evoked potentials before the pain stimulus, the patient's reaction could be predicted with a probability of 81.5%. The MLAER is closely associated to the patient's reaction to skin incision following noxious stimulation during 1 minimum alveolar anesthetic concentration isoflurane/nitrous oxide anesthesia. In combination with other parameters, MLAER could contribute to an objective and trustworthy movement prediction to noxious stimulation.

Anesthetics, Inhalation↗

PubMed2002

[Brief causal relations in EEG based on adaptive Granger causality].

Commonly, coherence and correlation are used to describe interrelations between EEG signals. But, on this basis, the investigation of causality or direction of interrelations is not possible. The general idea of causality between two signals may be expressed in terms of upgrading the predictability of one signal bye the knowledge of the past of the other signal. The best established approach in this context is the so-called Granger causality. The study present an adaptive estimation of Granger causality, which allows to detect dynamic causal relations within time intervals of less 100 ms. The time-variant Granger causality is applied to EEG data of the Stroop task. It could be shown, that conflict situation generates a dense web of directed interactions from posterior to anterior cortical areas.

Adult↗

PubMed2002

[Time variant bispectral analysis based on adaptive recursive Fourier transformation].

An appropriate investigation of quadratic phase couplings (QPC) in non-stationary signals requires time-variant methods of bispectral analysis. A new approach for time-variant estimation of power spectrum and bispectrum based on an adaptively, recursively estimated Fourier transform (ADFT) is presented in this paper. A reduced calculation effort and the possibility of the calculation of the bispectrum for selected frequency triples are important advantages of this method. Because of the recursive calculation, the ADFT is convenient for analysing ongoing signals. This will be demonstrated for simulated and real biomedical signals.

Electroencephalography↗

PubMed2002

Pneumatized spaces, sinuses and spongy bones in the skulls of primates.

The earliest attempts to understand the "pneumatized spaces" in the skulls of primates in general were focussed on the hollow spaces and the epithelium which covers their surfaces. More recent approaches consider the sinuses as a means to optimise skull architecture. Still, many attempts to get hold of the meaning of the intriguing pneumatized spaces circle around the air filled volumes they enclose. Here, we would like to reverse the approach and focus our biomechanic interpretation on the walls surrounding the big, empty, or at least not mechanically resistant spaces, and their mechanical properties. As a working hypothesis, we consider not only the walls of the more or less closed cavities, or sinuses, but also the braincase, the orbits, and the nasal channel as thin-walled shells of which we know that they can carry surprisingly large loads with a minimum of material. Details of the wall's profiles fit with this approach. From the same viewpoint, the bubble-like, air-filled cavernous systems in the ethmoid or temporal bones, and the marrow-filled spongy substance in the upper jaw are looked at as honeycomb-structures, which provide mechanical properties that are biologically advantageous and allow the saving of weight.

Animals↗

PubMed2001

Effect of different extraction procedures on the yield and pattern of Se-species in bacterial samples.

Investigations are described to extract Se-species from a bacterial sample. The five extraction methods investigated were: hot water, protease, lysozyme, lysozyme-protease, and HCl hydrolysis. The extraction efficiency was determined by comparing the total amounts of selenium in the sample after pressure digestion with the amounts extracted by the different methods described. Efficiencies were found to be only 1% (hot water), ca. 8% (protease, HCl hydrolysis) or ca. 12% (lysozyme, lysozyme-protease). The Se-peak patterns were compared after investigating the extracts with strong anion exchange chromatography-inductively coupled plasma mass spectrometry (SAX-ICP-MS). Most promising were the lysozyme-assisted procedures, which showed the highest diversity of species. Here, in the protease-lysozyme approach, the protease seemed to break down species that had been extracted by lysozyme from the bacterial wall (murein sacculus). The other approaches seemed not to extract many species. Hot water extraction was completely unsuitable, extracting only low amounts of a single, unknown species.

Bacteria↗

PubMed2001

Instantaneous multivariate EEG coherence analysis by means of adaptive high-dimensional autoregressive models.

This study presents an efficient algorithm for the fitting of multivariate autoregressive models (MVAR) with time-dependent parameters to multidimensional signals. Thereby, the dimension of the model may be chosen to equal the number of signal channels. The autoregressive (AR) parameter matrices are estimated by an extension of the recursive least squares (RLS) algorithm with forgetting factor. The estimation procedure includes a single trial as well as an ensemble mean approach. The latter approach allows the simultaneous fit of one mean MVAR model to a set of single trials, each of them representing the measurement of the same task. A particular advantage of this ensemble mean approach is that it requires only a low computation effort in comparison to well known procedures applied to single trials. Furthermore, the ensemble mean approach is linked with a high adaptation capability. The properties of the estimator are investigated using simulated time series. It can be demonstrated that the adaptation capability of the estimation (measured by its adaptation speed and variance) does not depend on the model dimension. The mean MVAR fit is applied to 19-dimensional EEG data, recorded during an elementary comparison procedure. The calculation of ordinary and multiple coherence is discussed. The sensitivity of the multiple instantaneous EEG coherence will be demonstrated.

Algorithms↗

PubMed2001

Phylogenetic relationships within terrestrial mites (Acari: Prostigmata, Parasitengona) inferred from comparative DNA sequence analysis of the mitochondrial cytochrome oxidase subunit I gene.

Partial DNA and amino acid sequences translated from the mitochondrial cytochrome subunit I gene (408 bp) of 17 mite species have been used for analyzing the phylogenetic relationships within the terrestrial Parasitengona (Trombidia). Due to mutational saturation of the third codon position, only first and second codon positions and amino acid sequences were analyzed, applying neighbor-joining, maximum-parsimony, and maximum-likelihood tree-building methods. The reconstructed trees revealed similar topologies of taxa; however, the phylogenetic relationships could be convincingly resolved only within several trombidioid taxa. The proposed basic relationships within the Parasitengona, in particular those of Calyptostomatoidea, Smarididae, and Erythraeidae, were poorly supported in bootstrap tests. A comparison of the presented gene tree with a phylogenetic tree based upon traditional characters revealed only few contradictions in nodes only weakly supported by morphological data. The most astonishing result is the proposed early derivative position of Microtrombidiidae within the terrestrial Parasitengona.

Animals↗

PubMed2001

Pitfalls in the clustering of neuroimage data and improvements by global optimization strategies.

In this paper, we examined three vector quantization (VQ) methods used for the unsupervised classification (clustering) of functional magnetic resonance imaging (fMRI) data. Classification means that each brain volume element (voxel), according to a given scanning raster, was assigned to one group of voxels based on similarity of the fMRI signal patterns. It was investigated how the VQ methods can isolate a cluster that describes the region involved in a particular brain function. As an example, word processing was stimulated by a word comparison task. VQ analysis methodology was verified using simulated fMRI response patterns. It was demonstrated in detail that VQ based on global rather than local optimization of the objective function yielded a higher performance. Performance was measured in statistically relevant series of VQ attempts using several indices for goodness, reliability and efficiency of VQ solutions. Furthermore, it was shown that a poor local optimization caused either an underestimation or an overestimation of the stimulus-induced brain activation. However, this was not observed if the cluster analysis was based upon a global optimization strategy.

Adult↗