A time domain binaural model based on spatial feature extraction for the head-related transfer function

A complex-valued head-related transfer function (HRTF) can be represented as a real-valued head-related impulse response (HRIR). The interaural time and level cues of HRIRs are extracted to derive the binaural model and also to normalize each measured HRIR. Using the Karhunen–Loeve expansion, normalized HRIRs are modeled as a weighted combination of a set of basis functions in a low-dimensional subspace. The basis functions and the space samples of the weights are obtained from the measured HRIR. A simple linear interpolation algorithm is employed to obtain the modeled binaural HRIRs. The modeled HRIRs are nearly identical to the measured HRIRs from an anesthetized live cat. Typical mean-square errors and cross-correlation coefficients between the 1816 measured and modeled HRIRs are 1% and 0.99, respectively. The real-valued operations and linear interpolating in the model are very effective for speeding up the model computation in real-time implementation. This approach has made it possible to simulate real free-field signals at the two eardrums of a cat via earphones and to study the neuronal responses to such a virtual acoustic space (VAR). ©1997 Acoustical Society of America.published_or_final_versio

Adaptive thresholding by variational method

When using thresholding method to segment an image, a fixed threshold is not suitable if the background is uneven. Here, we propose a new adaptive thresholding method using variational theory. The method requires only one parameter to be selected and the adaptive threshold surface can be found automatically from the original image.published_or_final_versio

A fast deformable region model for brain tumor boundary extraction

We present a modified deformable region model for extraction of a brain tumor boundary in 2D MR images. The deformable region model tolerates a rough initial plan when compared with the active contour model. However, it is time consuming to compute and compare the gray level distribution of the object and all its boundary points. Using a point sampling technique, the number of boundary point processed is greatly reduced. Performance of our modified deformable region model is evaluated on a MR image. The modified model is fast while similar results are obtained.published_or_final_versio

Visual evoked potential estimation by eigendecomposition

In this paper an eigendecomposition method is presented to estimate evoked potentials (EP). Taking into account of the characteristic of evoked potentials, the method uses two observations both of which contain desired EP signal and undesired EEG signal. If the desired and undesired signal are uncorrelated (i.e. they are orthgonal) and the signal-to-noise-ratios (SNR) of each observations are different, we can use the eigendecomposition method to separate EP signal from EEG. Visual evoked potentials (VEP) of humans have been estimated and good results obtained by this method.published_or_final_versio

A Fast Signal-Dependent Time-Frequency Representation

In last few years, in order to overcome same limitations of the short time Fourier transform (STFT), while avoiding the cross-terms that make the Wigner distribution difficult to interpret, some signal-dependent time-frequency representations (SDTFR) have been proposed. In this paper, the authors introduce a computationally efficient signal-dependent time-frequency method which is suitable for on-line analysis. This SDTFR uses a Gaussian window (GW) similar to STFT, but varies the parameter σ of the GW with time to achieve high signal concentration and high resolution in time. The parameter σ can be automatically calculated by the slope of instantaneous frequency (IF) and instantaneous bandwidth (IB) at that time.published_or_final_versio

Fast detection of venous air embolism in Doppler heart sound using the wavelet transform

The introduction of air bubbles into the systemic circulation can result in significant morbidity. Real-time monitoring of continuous heart sound in patients detected by precordial Doppler ultrasound is, thus, vital for early detection of venous air embolism (VAE) during surgery. In this study, the multiscale feature of wavelet transforms (WT's) is exploited to examine the embolic Doppler heart sound (DHS) during intravenous air injections in dogs. As both humans and dogs share similar physiological conditions, the authors' methods and results for dogs are expected to be applicable to humans. The WT of DHS at scale 2 j(j=1,2) selectively magnified the power of embolic, but not the normal, heart sound. Statistically, the enhanced embolic power was found to be sensitive (P<0.01 at 0.01 ml of injected air) and correlated significantly (P<0.0005, τ=0.83) with the volume of injected air from 0.01 to 0.10 ml. A fast detection algorithm of O(N) complexity with unit complexity constant for VAE was developed (processing speed=8 ms per heartbeat), which confirmed the feasibility of real-time processing for both humans and dogs.published_or_final_versio

Fibrillary glomerulonephritis: a case report

Fibrillary glomerulonephritis is a recently recognised condition. The usual presentation is heavy proteinuria. The diagnosis is established by demonstration of the characteristic Congo-red negative, randomly arranged microfibrils in the glomeruli by electron microscopy. At present, there is no proven effective treatment for this condition and the prognosis is generally poor. The first case of fibrillary glomerulonephritis diagnosed in Hong Kong is reported here in a 38-year-old woman.published_or_final_versio

Volume Estimation by Wavelet Transform of Doppler Heart Sound During Venous Air-Embolism in Dogs

The Doppler heart sound signals detected by the precordial Doppler ultrasound method under simulated sub clinical and clinically significant venous air embolism were studied in anesthetized dogs. Signal processing using wavelet transform enhanced the contrast of embolic to normal signal, facilitating automatic detection and extraction of embolic signal simply by thresholding. Linear relationship of good correlation coefficient was obtained in log-log scale between the subclinical volume of injected air and the corresponding embolic signal power in all dogs. The calibration curve was found to be good estimate of the volume of embolic air during simulated clinically significant venous air embolism. Hence, we overcame the need of constant human attention for detecting venous air embolism and the lack of quantitative information on the volume of embolic air in the traditional precordial Doppler ultrasound method by the present approach.published_or_final_versio

Wavelet analysis of head-related transfer functions

The directional-dependent information in the head-related transfer function (HRTF) is important for the study of human sound localization system and the synthesis of virtual auditory signals. Its time-domain and frequency-domain characteristics have been widely studied by researchers. The purpose of this paper is to explore the ability of discrete wavelet transform to describe the time-scale characteristics of HRTFs. Both the time-domain characteristics and energy distribution of different frequency subbands were studied. Discrete wavelet analysis is found to be a new direction-dependence information showing the relation of the characteristics of the HRTFs to sound source directions.published_or_final_versio