Parallel programming in biomedical signal processing

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Fractional discrete-time signal processing: scale conversion and linear prediction

Nonlinear Dynamics, Vol. 29

Fractional signal processing: scale conversion

In Proceedings of the “ECCTD '01 - European Conference on Circuit Theory and Design, Espoo, Finland, August 2001

A signal processing view of differintegration

Proceedings of the European Control Conference, ECC’01, Porto, Portugal, September 2001

Time series morphological analysis applied to biomedical signals events detection

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

Introduction to fractional linear systems. Part 1 : continuous-time case

IEE Proceedings - Vision, Image, and Signal Processing, Vol. 147, nº 1

Introduction to fractional linear systems. Part 2: discrete-time case

IEE Proceedings - Vision, Image, and Signal Processing, Vol. 147, nº 1

Algorithms for time series clustering applied to biomedical signals

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

Long-term biosignals visualization and processing

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Design and development of a microfluidic platform for use with colorimetric gold nanoprobe assays

Due to the importance and wide applications of the DNA analysis, there is a need to make genetic analysis more available and more affordable. As such, the aim of this PhD thesis is to optimize a colorimetric DNA biosensor based on gold nanoprobes developed in CEMOP by reducing its price and the needed volume of solution without compromising the device sensitivity and reliability, towards the point of care use. Firstly, the price of the biosensor was decreased by replacing the silicon photodetector by a low cost, solution processed TiO2 photodetector. To further reduce the photodetector price, a novel fabrication method was developed: a cost-effective inkjet printing technology that enabled to increase TiO2 surface area. Secondly, the DNA biosensor was optimized by means of microfluidics that offer advantages of miniaturization, much lower sample/reagents consumption, enhanced system performance and functionality by integrating different components. In the developed microfluidic platform, the optical path length was extended by detecting along the channel and the light was transmitted by optical fibres enabling to guide the light very close to the analysed solution. Microfluidic chip of high aspect ratio (~13), smooth and nearly vertical sidewalls was fabricated in PDMS using a SU-8 mould for patterning. The platform coupled to the gold nanoprobe assay enabled detection of Mycobacterium tuberculosis using 3 8l on DNA solution, i.e. 20 times less than in the previous state-of-the-art. Subsequently, the bio-microfluidic platform was optimized in terms of cost, electrical signal processing and sensitivity to colour variation, yielding 160% improvement of colorimetric AuNPs analysis. Planar microlenses were incorporated to converge light into the sample and then to the output fibre core increasing 6 times the signal-to-losses ratio. The optimized platform enabled detection of single nucleotide polymorphism related with obesity risk (FTO) using target DNA concentration below the limit of detection of the conventionally used microplate reader (i.e. 15 ng/μl) with 10 times lower solution volume (3 μl). The combination of the unique optical properties of gold nanoprobes with microfluidic platform resulted in sensitive and accurate sensor for single nucleotide polymorphism detection operating using small volumes of solutions and without the need for substrate functionalization or sophisticated instrumentation. Simultaneously, to enable on chip reagents mixing, a PDMS micromixer was developed and optimized for the highest efficiency, low pressure drop and short mixing length. The optimized device shows 80% of mixing efficiency at Re = 0.1 in 2.5 mm long mixer with the pressure drop of 6 Pa, satisfying requirements for the application in the microfluidic platform for DNA analysis.

Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).

On the HHT, its problems, and some solutions

Mechanical Systems and Signal Processing, Vol.22, Number 6

A coherent approach to non-integer order derivatives

Signal Processing, vol. 86, nº 10