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A novel approach is proposed to deal with the problem of detecting the single trial ERP using a modified RBF neural network, rational Gaussian network. The Gaussian RBF is normalized to obtain optimal behavior of noise suppression even at low SNR. The performance of the proposed scheme is also evaluated with both MSE and the tracking ability. Several experimental results with real ERP signals provide...
We describe multiresolution Bayesian tests for spike detection in multielectrode recordings. We derive results for single channel and multi electrode data, and show that the use of the array model substantially improves the detection performance. The effect of signal and noise spatial correlation characteristics is also discussed. Our approach focuses on blind signal detection without any assumptions...
The present study provides further insights into the chaotic nature of the ventilatory behaviour in spontaneously breathing healthy humans by applying the noise titration method to ventilatory flow signals gathered in this setting. In five subjects with normal breathing pattern and end-tidal CO2, the noise titration method gave a positive noise limit ranged from 6 to 43%. Our study shows that the...
Current alarm strategies for physiological monitoring depend on predetermined thresholds without consideration for the heterogeneity between patients or intraoperative variations. To improve upon this situation, we developed an adaptive change point detection scheme to automatically notify the clinician when a change of clinical significance has occurred in the respiratory variables. We modeled end-tidal...
A software approach has been developed for detecting electrocautery noise in the electrocardiogram (ECG) using a wavelet decomposition of the signal. With this approach, a clinical monitoring expert system can be forewarned of potential artefacts in trend values derived from the ECG, allowing it to proceed with caution when making decisions based on these trends. In 15 operations spanning 38.5 hours...
The main purpose of this paper is to develop a theoretical tool in order to fundamentally characterize the performance of Myocardial elastography and identify the optimal parameters to be used for the more reliable detection of ischemia or infarction. A complete representation of the left-ventricular function throughout an entire cardiac cycle was previously demonstrated through the use of a 3D finite-element...
The performances of support vector regression estimation were analyzed. It was found that the insensitive factor epsiv can affect the performance of support vector regression estimation significantly. The noise inside the sample data should be considered in determining the insensitive factor epsiv when support vector regression was employed. A novel support vector regression based on non-uniform lost...
We investigated the source localization performance of the Laplacian weighted minimum norm (LWMN) estimate technique in a realistic geometry (RG) head model in the present study. We simulated current sources at different brain regions with various noise levels. The present results show there is no obvious depth dependency on the three-dimensional (3D) source estimation. The average source localization...
The article presents a concept of balance among image points based on the correlation of points and then develops a new binarization method for gray scale image, which can be used in vessel extraction of DSA images. A point is in balance only when its resistance counteracts the influence from the neighborhood, while noise breaks down such balance. By restoring the balance of every single point, the...
Microwave breast tumor detection uses the electrical property contrast between normal tissues and malignancies to detect the latter in an early development stage. However, previous works on the microwave imaging uses 2-D or more complicated models of the breast and electromagnetic wave propagation. We present a computationally efficient and physically instructive electromagnetic wave channel modeling...
Deblurring in the presence of non-Gaussian noise is a hard problem, specially in ultrasonic and CT images. In this paper, a new method of image restoration, using complex wavelet transform, has been devised and applied to deblur in the presence of high speckle noise. It has been shown that the new method outperforms the Weiner filtering and Fourier-wavelet regularized deconvolution (ForWaRD) methods...
There is considerable recent interest in both (i) modelling the retinal ganglion cells, so that the models can generate output that approximates the actual response of the retina (such models will help design retinal prosthetics); and (ii) understanding how relevant information is encoded in the spike patterns generated by the ganglion cells (these neuronal codes will help understand how the brain...
Extraction of relevant features that capture the invariant characteristics specific to each brain state is very important in order to implement a suitable brain-computer interface (BCI) system. This paper presents an algorithm called one-versus-the-rest (OVR), which is an extension of a well-known method called common spatial patterns (CSP) to multi-class case, to extract signal components specific...
This paper aims to analyze the dynamic characteristics of the postural sway measurements, the curves of the velocity and acceleration of the postural sway measurements were used. The curves of smoothed velocity and acceleration were got through the filter of Haar wavelet packet decomposing function. At the increasing of age, the velocity and acceleration of the postural sway measurements are increasing,...
Poor local contrast is a nettlesome problem in biomedical image analysis. The multiscale method based on mathematical morphology has been successfully used in local contrast enhancement. However, the computational time is high. In this paper, the existing method is much improved by using few feature levels in an efficient way. The new algorithm is tested by experiments. Compared with the previous...
This paper presents an efficient lossless compression scheme designed for the fMRI data volume. An fMRI time series is composed of trend, noise and external stimulus response, which have different characteristics in wavelet domain. Reversible integer wavelet transform is applied to the fMRI time series. The smooth trend signals are extracted from the low frequency wavelet bands and they are coded...
Automatic contouring for breast tumors using medical ultrasound (US) imaging may assist physicians, without relevant experience, in making correct diagnoses. This study utilizes the watershed transform and active contour model (ACM) to overcome the natural properties of US images, speckle, noise and tissue-related textures, to segment the breast tumors precisely. The watershed transform is performed...
This paper proposes a real-time algorithm estimating clinical useful parameters from the maximum frequency curve of ultrasound Doppler spectrum. Traditional methods always apply some pre-calculations to the frequency waveform, for instance, filtering or scaling transformation, which have limitations on real-time features detection and waveform display. In this paper, we propose and maintain a process...
Image's noise, edge and contrast are the important factors that influence image's quality. If a method of image enhancement is solely applied to the degraded medical digital image, image's quality is improved in part, if a combined method of image enhancement is applied to the degraded medical digital image, it can increase the image's quality greatly
The aim of this study is to investigate dynamic characteristics of late wave of auditory evoked potentials (AEPs) in synaptic malfunction rat model. Two dynamic characteristics relative to cognitive function were investigated which are dynamic latency and dynamic amplitude of P1. Synaptic malfunction model was made by Sprague-Dawley rats via microinjecting beta-amyloid protein (A-beta) into hippocampal...
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