IEEE transactions on bio-medical engineering
-
IEEE Trans Biomed Eng · Nov 2004
Comparative StudyAdaptive denoising of event-related functional magnetic resonance imaging data using spectral subtraction.
A new adaptive signal-preserving technique for noise suppression in event-related functional magnetic resonance imaging (fMRI) data is proposed based on spectral subtraction. The proposed technique estimates a parametric model for the power spectrum of random noise from the acquired data based on the characteristics of the Rician statistical model. This model is subsequently used to estimate a noise-suppressed power spectrum for any given pixel time course by simple subtraction of power spectra. ⋯ Moreover, we demonstrate that further analysis using principal component analysis and independent component analysis shows a significant improvement in both convergence and clarity of results when the new technique is used. Given its simple form, the new method does not change the statistical characteristics of the signal or cause correlated noise to be present in the processed signal. This suggests the value of the new technique as a useful preprocessing step for fMRI data analysis.
-
IEEE Trans Biomed Eng · Nov 2004
Long-term characterization of firing dynamics of spontaneous bursts in cultured neural networks.
Extracellular action potentials were recorded from developing dissociated rat neocortical networks continuously for up to 49 days in vitro using planar multielectrode arrays. Spontaneous neuronal activity emerged toward the end of the first week in vitro and from then on exhibited periods of elevated firing rates, lasting for a few days up to weeks, which were largely uncorrelated among different recording sites. On a time scale of seconds to minutes, network activity typically displayed an ongoing repetition of distinctive firing patterns, including short episodes of synchronous firing at many sites (network bursts). ⋯ This pattern persisted for the rest of the culture period. Throughout the recording period, active sites showed highly persistent temporal relationships within network bursts. These longitudinal recordings of network firing have, thus, brought to light a reproducible pattern of complex changes in spontaneous firing dynamics of bursts during the development of isolated cortical neurons into synaptically interconnected networks.
-
IEEE Trans Biomed Eng · Oct 2004
Comparative StudyA new methodology for determining point-of-gaze in head-mounted eye tracking systems.
The ability to determine point-of-gaze with respect to an observed scene provides significant insight into human cognitive processes, since shifts in gaze position are generally guided by shifts in attentional focus. Using a head-mounted eye tracking system, a new methodology based on four or more point correspondences in two views was developed to reconstruct the subject's point-of-gaze. ⋯ Analysis of normalization techniques that reduce the sensitivity of the homography algorithm to input errors suggests that the point correspondences should be arranged in a radially symmetric distribution around the area to be scanned. The new methodology was used in a clinical study on visual selective attention and mood disorders; this study showed that depressed subjects spent significantly more time looking at images with dysphoric themes than normal control subjects.
-
IEEE Trans Biomed Eng · Sep 2004
Comparative Study Clinical TrialBlind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals.
Electromyographic (EMG) recordings detected over the skin may be mixtures of signals generated by different active muscles due to the phenomena related to volume conduction. Separation of the sources is necessary when single muscle activity has to be detected. Signals generated by different muscles may be considered uncorrelated but in general overlap in time and frequency. ⋯ The ratio between root-mean-square values of the signals from the two sources detected over one of the muscles increased from (mean +/- standard deviation) 2.33 +/- 1.04 to 4.51 +/- 1.37 and from 1.55 +/- 0.46 to 2.72 +/- 0.65 for wrist flexion and rotation, respectively. This increment was statistically significant. It was concluded that the BSS approach applied is promising for the separation of surface EMG signals, with applications ranging from muscle assessment to detection of muscle activation intervals, and to the control of myoelectric prostheses.
-
IEEE Trans Biomed Eng · Sep 2004
Comparative Study Clinical TrialClassification of anatomical structures in MR brain images using fuzzy parameters.
We present an algorithm that automatically segments and classifies the brain structures in a set of magnetic resonance (MR) brain images using expert information contained in a small subset of the image set. The algorithm is intended to do the segmentation and classification tasks mimicking the way a human expert would reason. The algorithm uses a knowledge base taken from a small subset of semiautomatically classified images that is combined with a set of fuzzy indexes that capture the experience and expectation a human expert uses during recognition tasks. ⋯ The algorithm uses low-level image processing techniques on a pixel basis for the segmentations, then validates or corrects the segmentations, and makes the final classification decision using higher level criteria measured by the set of fuzzy indexes. We use single-echo MR images because of their high volumetric resolution; but even though we are working with only one image per brain slice, we have multiple sources of information on each pixel: absolute and relative positions in the image, gray level value, statistics of the pixel and its three-dimensional neighborhood and relation to its counterpart pixels in adjacent images. We have validated our algorithm for ease of use and precision both with clinical experts and with measurable error indexes over a Brainweb simulated MR set.