Francisco Vaz

A CMOS IC for portable EEG acquisition systems

This paper presents a monolithic low-power, low-noise analog front-end electroencephalogram (EEG) acquisition system. It draws only 500 /spl mu/A from a standard 9 V battery, making it suitable for use in portable systems. Although fabricated in a standard CMOS technology, using current feedback techniques it achieves a CMRR of 100 dB while the total input noise referred to input is kept as low as 1.5 /spl mu/V (RMS).

Registration and fusion of intensity and range data for 3D modelling of real world scenes

A novel technique combining intensity and range data is presented. Passive (intensity based) and active (range based) techniques used for 3D reconstruction have their limitations and separately, none of these techniques can solve all the problems inherent to the modelling of real environments. Our technique aims to demonstrate how both intensity and range data can be registered and combined into a long-range 3D system. The procedure needs an initial estimation for internal and external camera parameters for two or more intensity images. The technique uses passive triangulation of the intensity data to refine the initial camera calibrations and ensure a good registration of range and video data sets. Once a reliable calibration is achieved, corresponding points from the intensity images are triangulated and introduced in the original range data. With our technique, it is possible to complete the models in areas where data is missing or to increase the resolution in areas of high interest and 3D contents.

Perception maps for the local navigation of a mobile robot: a neural network approach

Sensorial perception is a key issue for the problem of robot local navigation, that is, the immediate or short-range motion planning, reacting only to the free space around the robot, without requiring a pre-defined trajectory plan. Therefore, local navigation requires no environment model and relies entirely on sensorial data. Commonly used sensors such as ultrasonic ranging devices, are known for their associated problems: specular reflections and crosstalk, essentially. However if sensors are used in an appropriate number and geometric lay-outs, the resulting spatial redundancy offers the possibility of overcoming some of those problems. This paper deals with these problems by means of special perception maps using ultrasound data. A generalised grid serves as the base of maps, and its cells have simply binary values: free or occupied. The relation between the topology of the perception map and the environment is a determinant factor for accurate reasoning. A 3-layer feed-forward neural network is used to perform the mapping between sensorial scans and grid occupancy. It was verified that the neural network handles most of the situations of specular reflections, and gives good perception maps for mid-range distances. Changes in environment, such as obstacles in vehicles trajectory, have also been detected, which stresses the networks ability to generalise.<<ETX>>

Automatic registration of laser reflectance and colour intensity images for 3D reconstruction

Abstract The objective of the work presented in this paper is to generate complete, high-resolution models of real world scenes from passive intensity images and active range sensors. In previous work, an automatic method has been developed in order to compute 3D models of real world scenes from laser range data. The aim of this project is to improve these existing models by fusing range and intensity data. The paper presents different techniques in order to find correspondences between the different sets of data. Based on these control points, a robust camera calibration is computed with a minimal user intervention in order to avoid the fastidious point and click phase that is still necessary in many systems. The intensity images are then re-projected into the laser coordinate frame to produce an image that combines the laser reflectance and the available video intensity images into a colour texture map.

Spectrum of Doppler ultrasound signals from nonstationary blood flow

A new formulation for the Doppler signal generation process in pulsatile flow has been developed enabling easier identification and quantification of the mechanisms involved in spectral broadening and the development of a simple estimation formula for the measured rms spectral width. The accuracy of the estimation formula was tested by comparing it with the spectral widths found by using conventional spectral estimation on simulated Doppler signals from pulsatile flow. The influence of acceleration, sample volume size, and time window duration on the Doppler spectral width was investigated for flow with blunt and parabolic velocity profiles passing through Gaussian-shaped sample volumes. Our results show that, for short duration windows, the spectral width is dominated by window broadening and that acceleration has a small effect on the spectral width. For long duration windows, the effect of acceleration must be taken into account. The size of the sample volume affects the spectral width of the Doppler signal in two ways: by intrinsic broadening and by the range of velocities passing through it. These effects act in opposite directions. The simple spectral width estimation formula was shown to have excellent agreement with widths calculated using the model and indicates the potential for correcting not only for window and nonstationarity broadening but also for intrinsic broadening.

A study on the best order for autoregressive EEG modelling

The autoregressive (AR) model is a widely used tool in electroencephalogram (EEG) analysis. The dependence of the AR model on both the segment length and several characteristic EEG patterns is addressed. The best AR model order is computed with three different criteria. The results show that the Rissanen criteria provides the more consistent order estimate for the EEG patterns considered. This study shows that for our data set, a 5th order AR model represents adequately 1- or 2-s EEG segments with the exception of featureless background, where higher order models are necessary.

Blood and wall signal simulator for Doppler ultrasound signal analysis algorithm development

Doppler ultrasound instruments, used for the detection and monitoring of vascular disease, require a means of separating the large, low frequency Doppler signal from the vessel wall from the signal arising from blood followed by a means of analysing he blood flow signal in order to characterise the flow conditions. This is normally achieved by using a high-pass filter that removes the signal reflected from the vessel wall. Unfortunately, the filter also removes the low frequency Doppler signals arising from slow moving blood. A better signal segmentation method that reduces the loss of signal from slowly moving blood is needed to permit the measurement of lower blood velocities. A signal simulator that generates Doppler signals that include the contributions from blood and vessel wall will be very useful for the development of new Doppler signal segmentation methods. This work presents a new simulator incorporating the contribution of blood and vessel wall movements; the characteristics of the simulator output signal are similar to those found in practice.

Combining intensity and range images for 3D modelling

This paper presents a process combining range and intensity based techniques, in order to get better 3D models than those obtained using these techniques separately. The procedure needs an initial estimation for internal and external camera parameters for two or more intensity images. The technique uses passive triangulation to refine initial camera calibrations and ensure a good registration of range and video data sets. Afterwards, corresponding points from the intensity images are triangulated and introduced in the original range cloud of points. The objective is to complete the models in areas where data is missing or to increase the resolution in areas of high interest and 3D contents.

Doppler power spectrum from a Gaussian sample volume

A closed-form expression for the Doppler power spectrum due solely to the range of blood velocities passing through a Gaussian sample volume placed anywhere in a vessel under conditions of axisymmetric flow, uniform backscatter and negligible intrinsic spectral broadening has been derived. The formulation presented here allows the independent specification of the sample volume position and width, in the three dimensions, and enables simple estimations of spectral shape for pulsed wave Doppler systems. Simpler expressions were derived for the cases of symmetric sample volume projections onto the vessel cross-section and/or sample volumes centred in the vessel. Closed form expressions were derived for mean frequency and spectral width in the case of a symmetric sample volume projection centred in the vessel. The effects of sample volume size and position on the Doppler spectral width and mean frequency are shown for a range of velocity profiles.

Simulation of human speech production applied to the study and synthesis of European Portuguese

A new articulatory synthesizer (SAPWindows), with a modular and flexible design, is described. A comprehensive acoustic model and a new interactive glottal source were implemented. Perceptual tests and simulations made possible by the synthesizer contributed to deepening our knowledge of one of the most important characteristics of European Portuguese, the nasal vowels. First attempts at incorporating models of frication into the articulatory synthesizer are presented, demonstrating the potential of performing fricative synthesis based on broad articulatory configurations. Synthesis of nonsense words and Portuguese words with vowels and nasal consonants is also shown. Despite not being capable of competing with mainstream concatenative speech synthesis, the anthropomorphic approach to speech synthesis, known as articulatory synthesis, proved to be a valuable tool for phonetics research and teaching. This was particularly true for the European Portuguese nasal vowels.