916 resultados para Frequency bands
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This paper extents the by now classic sensor fusion complementary filter (CF) design, involving two sensors, to the case where three sensors that provide measurements in different bands are available. This paper shows that the use of classical CF techniques to tackle a generic three sensors fusion problem, based solely on their frequency domain characteristics, leads to a minimal realization, stable, sub-optimal solution, denoted as Complementary Filters3 (CF3). Then, a new approach for the estimation problem at hand is used, based on optimal linear Kalman filtering techniques. Moreover, the solution is shown to preserve the complementary property, i.e. the sum of the three transfer functions of the respective sensors add up to one, both in continuous and discrete time domains. This new class of filters are denoted as Complementary Kalman Filters3 (CKF3). The attitude estimation of a mobile robot is addressed, based on data from a rate gyroscope, a digital compass, and odometry. The experimental results obtained are reported.
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Several clinical studies have reported that EEG synchrony is affected by Alzheimer’s disease (AD). In this paper a frequency band analysis of AD EEG signals is presented, with the aim of improving the diagnosis of AD using EEG signals. In this paper, multiple synchrony measures are assessed through statistical tests (Mann–Whitney U test), including correlation, phase synchrony and Granger causality measures. Moreover, linear discriminant analysis (LDA) is conducted with those synchrony measures as features. For the data set at hand, the frequency range (5-6Hz) yields the best accuracy for diagnosing AD, which lies within the classical theta band (4-8Hz). The corresponding classification error is 4.88% for directed transfer function (DTF) Granger causality measure. Interestingly, results show that EEG of AD patients is more synchronous than in healthy subjects within the optimized range 5-6Hz, which is in sharp contrast with the loss of synchrony in AD EEG reported in many earlier studies. This new finding may provide new insights about the neurophysiology of AD. Additional testing on larger AD datasets is required to verify the effectiveness of the proposed approach.
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Added stable gain (ASG) was measured to assess the differences in feedback reduction algorithms across six manufacturers, two earmold styles, ten audiograms, and three frequency bands.
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Three experiments measured constancy in speech perception, using natural-speech messages or noise-band vocoder versions of them. The eight vocoder-bands had equally log-spaced center-frequencies and the shapes of corresponding “auditory” filters. Consequently, the bands had the temporal envelopes that arise in these auditory filters when the speech is played. The “sir” or “stir” test-words were distinguished by degrees of amplitude modulation, and played in the context; “next you’ll get _ to click on.” Listeners identified test-words appropriately, even in the vocoder conditions where the speech had a “noise-like” quality. Constancy was assessed by comparing the identification of test-words with low or high levels of room reflections across conditions where the context had either a low or a high level of reflections. Constancy was obtained with both the natural and the vocoded speech, indicating that the effect arises through temporal-envelope processing. Two further experiments assessed perceptual weighting of the different bands, both in the test word and in the context. The resulting weighting functions both increase monotonically with frequency, following the spectral characteristics of the test-word’s [s]. It is suggested that these two weighting functions are similar because they both come about through the perceptual grouping of the test-word’s bands.
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Altered state theories of hypnosis posit that a qualitatively distinct state of mental processing, which emerges in those with high hypnotic susceptibility following a hypnotic induction, enables the generation of anomalous experiences in response to specific hypnotic suggestions. If so then such a state should be observable as a discrete pattern of changes to functional connectivity (shared information) between brain regions following a hypnotic induction in high but not low hypnotically susceptible participants. Twenty-eight channel EEG was recorded from 12 high susceptible (highs) and 11 low susceptible (lows) participants with their eyes closed prior to and following a standard hypnotic induction. The EEG was used to provide a measure of functional connectivity using both coherence (COH) and the imaginary component of coherence (iCOH), which is insensitive to the effects of volume conduction. COH and iCOH were calculated between all electrode pairs for the frequency bands: delta (0.1-3.9 Hz), theta (4-7.9 Hz) alpha (8-12.9 Hz), beta1 (13-19.9 Hz), beta2 (20-29.9 Hz) and gamma (30-45 Hz). The results showed that there was an increase in theta iCOH from the pre-hypnosis to hypnosis condition in highs but not lows with a large proportion of significant links being focused on a central-parietal hub. There was also a decrease in beta1 iCOH from the pre-hypnosis to hypnosis condition with a focus on a fronto-central and an occipital hub that was greater in high compared to low susceptibles. There were no significant differences for COH or for spectral band amplitude in any frequency band. The results are interpreted as indicating that the hypnotic induction elicited a qualitative change in the organization of specific control systems within the brain for high as compared to low susceptible participants. This change in the functional organization of neural networks is a plausible indicator of the much theorized "hypnotic-state". © 2014 Jamieson and Burgess.
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Introduction: Neuronal oscillations have been the focus of increasing interest in the neuroscientific community, in part because they have been considered as a possible integrating mechanism through which internal states can influence stimulus processing in a top-down way (Engel et al., 2001). Moreover, increasing evidence indicates that oscillations in different frequency bands interact with one other through coupling mechanisms (Jensen and Colgin, 2007). The existence and the importance of these cross-frequency couplings during various tasks have been verified by recent studies (Canolty et al., 2006; Lakatos et al., 2007). In this study, we measure the strength and directionality of two types of couplings - phase-amplitude couplings and phase-phase couplings - between various bands in EEG data recorded during an illusory contour experiment that were identified using a recently-proposed adaptive frequency tracking algorithm (Van Zaen et al., 2010). Methods: The data used in this study have been taken from a previously published study examining the spatiotemporal mechanisms of illusory contour processing (Murray et al., 2002). The EEG in the present study were from a subset of nine subjects. Each stimulus was composed of 'pac-man' inducers presented in two orientations: IC, when an illusory contour was present, and NC, when no contour could be detected. The signals recorded by the electrodes P2, P4, P6, PO4 and PO6 were averaged, and filtered into the following bands: 4-8Hz, 8-12Hz, 15-25Hz, 35-45Hz, 45-55Hz, 55-65Hz and 65-75Hz. An adaptive frequency tracking algorithm (Van Zaen et al., 2010) was then applied in each band in order to extract the main oscillation and estimate its frequency. This additional step ensures that clean phase information is obtained when taking the Hilbert transform. The frequency estimated by the tracker was averaged over sliding windows and then used to compare the two conditions. Two types of cross-frequency couplings were considered: phase-amplitude couplings and phase-phase couplings. Both types were measured with the phase locking value (PLV, Lachaux et al., 1999) over sliding windows. The phase-amplitude couplings were computed with the phase of the low frequency oscillation and the phase of the amplitude of the high frequency one. Different coupling coefficients were used when measuring phase-phase couplings in order to estimate different m:n synchronizations (4:3, 3:2, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1 and 9:1) and to take into account the frequency differences across bands. Moreover, the direction of coupling was estimated with a directionality index (Bahraminasab et al., 2008). Finally, the two conditions IC and NC were compared with ANOVAs with 'subject' as a random effect and 'condition' as a fixed effect. Before computing the statistical tests, the PLV values were transformed into approximately normal variables (Penny et al., 2008). Results: When comparing the mean estimated frequency across conditions, a significant difference was found only in the 4-8Hz band, such that the frequency within this band was significantly higher for IC than NC stimuli starting at ~250ms post-stimulus onset (Fig. 1; solid line shows IC and dashed line NC). Significant differences in phase-amplitude couplings were obtained only when the 4-8 Hz band was taken as the low frequency band. Moreover, in all significant situations, the coupling strength is higher for the NC than IC condition. An example of significant difference between conditions is shown in Fig. 2 for the phase-amplitude coupling between the 4-8Hz and 55-65Hz bands (p-value in top panel and mean PLV values in the bottom panel). A decrease in coupling strength was observed shortly after stimulus onset for both conditions and was greater for the condition IC. This phenomenon was observed with all other frequency bands. The results obtained for the phase-phase couplings were more complex. As for the phase-amplitude couplings, all significant differences were obtained when the 4-8Hz band was considered as the low frequency band. The stimulus condition exhibiting the higher coupling strength depended on the ratio of the coupling coefficients. When this ratio was small, the IC condition exhibited the higher phase-phase coupling strength. When this ratio was large, the NC condition exhibited the higher coupling strength. Fig. 3 shows the phase-phase couplings between the 4-8Hz and 35-45Hz bands for the coupling coefficient 6:1, and the coupling strength was significantly higher for the IC than NC condition. By contrast, for the coupling coefficient 9:1 the NC condition gave the higher coupling strength (Fig. 4). Control analyses verified that it is not a consequence of the frequency difference between the two conditions in the 4-8Hz band. The directionality measures indicated a transfer of information from the low frequency components towards the high frequency ones. Conclusions: Adaptive tracking is a feasible method for EEG analyses, revealing information both about stimulus-related differences and coupling patterns across frequencies. Theta oscillations play a central role in illusory shape processing and more generally in visual processing. The presence vs. absence of illusory shapes was paralleled by faster theta oscillations. Phase-amplitude couplings were decreased more for IC than NC and might be due to a resetting mechanism. The complex patterns in phase-phase coupling between theta and beta/gamma suggest that the contribution of these oscillations to visual binding and stimulus processing are not as straightforward as conventionally held. Causality analyses further suggest that theta oscillations drive beta/gamma oscillations (see also Schroeder and Lakatos, 2009). The present findings highlight the need for applying more sophisticated signal analyses in order to establish a fuller understanding of the functional role of neural oscillations.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Despite its high incidence, patellofemoral pain etiology remains unclear. No prior study has compared surface electromyography frequency domain parameters and surface electromyography time domain variables, which have been used as a classic analysis of patellofemoral pain. Thirty one women with patellofemoral pain and twenty eight pain-free women were recruited. Each participant was asked to descend a seven step staircase and data from five successful trials were collected. During the task, the vastus medialis and vastus lateralis muscle activities were monitored by surface electromyography. The data were processed and analyzed in four variables of the frequency domain (median frequency, low, medium and high frequency bands) and three time domain variables (Automatic, Cross-correlation and Visual Onset between the vastus medialis and vastus lateralis muscles). Reliability, Receiver Operating Characteristic curves and regression models were performed. The medium frequency band was the most reliable variable and different between the groups for both muscles, also demonstrated the best values of sensitivity and sensibility, 72% and 69% for the vastus medialis and 68% and 62% for the vastus lateralis, respectively. The frequency variables predicted the pain of individuals with patellofemoral pain, 26% for the vastus medialis and 20% for the vastus lateralis, being better than the time variables, which achieved only 7%. The frequency domain parameters presented greater reliability, diagnostic accuracy and capacity to predict pain than the time domain variables during stair descent and might be a useful tool to diagnose individuals with patellofemoral pain.
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We developed a geospatial model that calculates ambient high-frequency electromagnetic field (HF-EMF) strengths of stationary transmission installations such as mobile phone base stations and broadcast transmitters with high spatial resolution in the order of 1 m. The model considers the location and transmission patterns of the transmitters, the three-dimensional topography, and shielding effects by buildings. The aim of the present study was to assess the suitability of the model for exposure monitoring and for epidemiological research. We modeled time-averaged HF-EMF strengths for an urban area in the city of Basel as well as for a rural area (Bubendorf). To compare modeling with measurements, we selected 20 outdoor measurement sites in Basel and 18 sites in Bubendorf. We calculated Pearson's correlation coefficients between modeling and measurements. Chance-corrected agreement was evaluated by weighted Cohen's kappa statistics for three exposure categories. Correlation between measurements and modeling of the total HF-EMF strength was 0.67 (95% confidence interval (CI): 0.33-0.86) in the city of Basel and 0.77 (95% CI: 0.46-0.91) in the rural area. In both regions, kappa coefficients between measurements and modeling were 0.63 and 0.77 for the total HF-EMF strengths and for all mobile phone frequency bands. First evaluation of our geospatial model yielded substantial agreement between modeling and measurements. However, before the model can be applied for future epidemiologic research, additional validation studies focusing on indoor values are needed to improve model validity.Journal of Exposure Science and Environmental Epidemiology (2008) 18, 183-191; doi:10.1038/sj.jes.7500575; published online 4 April 2007.
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We explored and refined the hypothesis that during a first episode of acute schizophrenia a disorganization of brain functioning is present. A novel EEG measure was introduced, Global Field Synchronization (GFS), that estimates functional connectivity of brain processes in different EEG frequency bands. The measure was applied to EEG's from 11 never-treated, first-episode, young patients with an acute, positive, schizophrenic symptomatology and from 19 controls, residing in Bern, Switzerland. In comparison to age- and sex- matched controls, patients had significantly decreased GFS in the theta EEG frequency band, indicating a loosened functional connectivity of processes in this frequency. The result was confirmed in an independent, comparable patient group from Osaka, Japan (9 patients and 9 controls), thus making a total of 20 analyzed patients. Previous EEG research in healthy, awake subjects indicated a positive correlation of theta activity with memory functions. Thus, our result suggests a loss of mutual interdependence of memory functions in patients with acute schizophrenia, which agrees well with previous reports of working memory dysfunction in schizophrenia.
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Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency decomposition is a novel computerized EEG analysis method that combines previously available techniques from time-domain spatial EEG analysis and time-frequency decomposition of single-channel time series. It yields a new, physiologically and statistically plausible topographic time-frequency representation of human multichannel EEG. The original EEG is accounted by the coefficients of a large set of user defined EEG like time-series, which are optimized for maximal spatial smoothness and minimal norm. These coefficients are then reduced to a small number of model scalp field configurations, which vary in intensity as a function of time and frequency. The result is thus a small number of EEG field configurations, each with a corresponding time-frequency (Wigner) plot. The method has several advantages: It does not assume that the data is composed of orthogonal elements, it does not assume stationarity, it produces topographical maps and it allows to include user-defined, specific EEG elements, such as spike and wave patterns. After a formal introduction of the method, several examples are given, which include artificial data and multichannel EEG during different physiological and pathological conditions.
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27-Channel EEG potential map series were recorded from 12 normals with closed and open eyes. Intracerebral dipole model source locations in the frequency domain were computed. Eye opening (visual input) caused centralization (convergence and elevation) of the source locations of the seven frequency bands, indicative of generalized activity; especially, there was clear anteriorization of α-2 (10.5–12 Hz) and β-2 (18.5–21 Hz) sources (α-2 also to the left). Complexity of the map series' trajectories in state space (assessed by Global Dimensional Complexity and Global OMEGA Complexity) increased significantly with eye opening, indicative of more independent, parallel, active processes. Contrary to PET and fMRI, these results suggest that brain activity is more distributed and independent during visual input than after eye closing (when it is more localized and more posterior).
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The topic of this study was to evaluate state-dependent effects of diazepam on the frequency characteristics of 47-channel spontaneous EEG maps. A novel method, the FFT-Dipole-Approximation (Lehmann and Michel, 1990), was used to study effects on the strength and the topography of the maps in the different frequency bands. Map topography was characterized by the 3-dimensional location of the equivalent dipole source and map strength was defined as the spatial standard deviation (the Global Field Power) of the maps of each frequency point. The Global Field Power can be considered as a measure of the amount of energy produced by the system, while the source location gives an estimate of the center of gravity of all sources in the brain that were active at a certain frequency. State-dependency was studied by evaluating the drug effects before and after a continuous performance task of 25 min duration. Clear interactions between drug (diazepam vs. placebo) and time after drug intake (before and after the task) were found, especially in the inferior-superior location of the dipole sources. It supports the hypothesis that diazepam, like other drugs, has different effects on brain functions depending on the momentary functional state of the brain. In addition to the drug effects, clearly different source locations and Global Field Power were found for the different frequency bands, replicating earlier reports (Michel et al., 1992).
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We investigated brain electric field signatures of subjective feelings after chewing regular gum or gum base without flavor. 19-channel eyes-closed EEG from 20 healthy males before and after 5 minutes of chewing the two gum types in random sequence was source modeled in the frequency domain using the FFT-Dipole-Approximation. 3-dimensional brain locations and strengths (Global Field Power, GFP) of the equivalent sources of five frequency bands were computed as changes from pre-chewing baseline. Gum types differed (ANOVA) in pre-post changes of source locations for the alpha-2 band (to anterior and right after regular gum, opposite after gum base) and beta-2 band (to anterior and inferior after regular gum, opposite after gum base), and of GFP for delta-theta, alpha-2 and beta-1 (regular gum: increase, gum base: decrease). Subjective feeling changed to more positive values after regular gum than gum base (ANOVA).—Thus, chewing gum with and without taste-smell activates different brain neuronal populations.
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Improvements in neuroimaging methods have afforded significant advances in our knowledge of the cognitive and neural foundations of aesthetic appreciation. We used magnetoencephalography (MEG) to register brain activity while participants decided about the beauty of visual stimuli. The data were analyzed with event-related field (ERF) and Time-Frequency (TF) procedures. ERFs revealed no significant differences between brain activity related with stimuli rated as “beautiful” and “not beautiful.” TF analysis showed clear differences between both conditions 400 ms after stimulus onset. Oscillatory power was greater for stimuli rated as “beautiful” than those regarded as “not beautiful” in the four frequency bands (theta, alpha, beta, and gamma). These results are interpreted in the frame of synchronization studies.