ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

An embedded 1149.4 extension to support mixed-signal debugging

Debugging electronic circuits is traditionally done with bench equipment directly connected to the circuit under debug. In the digital domain, the difficulties associated with the direct physical access to circuit nodes led to the inclusion of resources providing support to that activity, first at the printed circuit level, and then at the integrated circuit level. The experience acquired with those solutions led to the emergence of dedicated infrastructures for debugging cores at the system-on-chip level. However, all these developments had a small impact in the analog and mixed-signal domain, where debugging still depends, to a large extent, on direct physical access to circuit nodes. As a consequence, when analog and mixed-signal circuits are integrated as cores inside a system-on-chip, the difficulties associated with debugging increase, which cause the time-to-market and the prototype verification costs to also increase. The present work considers the IEEE1149.4 infrastructure as a means to support the debugging of mixed-signal circuits, namely to access the circuit nodes and also an embedded debug mechanism named mixed-signal condition detector, necessary for watch-/breakpoints and real-time analysis operations. One of the main advantages associated with the proposed solution is the seamless migration to the system-on-chip level, as the access is done through electronic means, thus easing debugging operations at different hierarchical levels.

Lettuce (Lactuca sativa L.) leaf-proteome profiles after exposure to cylindrospermopsin and a microcystin-LR/cylindrospermopsin mixture: A concentration-dependent response

The intensification of agricultural productivity is an important challenge worldwide. However, environmental stressors can provide challenges to this intensification. The progressive occurrence of the cyanotoxins cylindrospermopsin (CYN) and microcystin-LR (MC-LR) as a potential consequence of eutrophication and climate change is of increasing concern in the agricultural sector because it has been reported that these cyanotoxins exert harmful effects in crop plants. A proteomic-based approach has been shown to be a suitable tool for the detection and identification of the primary responses of organisms exposed to cyanotoxins. The aim of this study was to compare the leaf-proteome profiles of lettuce plants exposed to environmentally relevant concentrations of CYN and a MC-LR/CYN mixture. Lettuce plants were exposed to 1, 10, and 100 lg/l CYN and a MC-LR/CYN mixture for five days. The proteins of lettuce leaves were separated by twodimensional electrophoresis (2-DE), and those that were differentially abundant were then identified by matrix-assisted laser desorption/ionization time of flight-mass spectrometry (MALDI-TOF/TOF MS). The biological functions of the proteins that were most represented in both experiments were photosynthesis and carbon metabolism and stress/defense response. Proteins involved in protein synthesis and signal transduction were also highly observed in the MC-LR/CYN experiment. Although distinct protein abundance patterns were observed in both experiments, the effects appear to be concentration-dependent, and the effects of the mixture were clearly stronger than those of CYN alone. The obtained results highlight the putative tolerance of lettuce to CYN at concentrations up to 100 lg/l. Furthermore, the combination of CYN with MC-LR at low concentrations (1 lg/l) stimulated a significant increase in the fresh weight (fr. wt) of lettuce leaves and at the proteomic level resulted in the increase in abundance of a high number of proteins. In contrast, many proteins exhibited a decrease in abundance or were absent in the gels of the simultaneous exposure to 10 and 100 lg/l MC-LR/CYN. In the latter, also a significant decrease in the fr. wt of lettuce leaves was obtained. These findings provide important insights into the molecular mechanisms of the lettuce response to CYN and MC-LR/CYN and may contribute to the identification of potential protein markers of exposure and proteins that may confer tolerance to CYN and MC-LR/CYN. Furthermore, because lettuce is an important crop worldwide, this study may improve our understanding of the potential impact of these cyanotoxins on its quality traits (e.g., presence of allergenic proteins).

Detection of cardiac biomarker proteins using a disposable based on a molecularly imprinted polymer grafted onto graphite

A low-cost disposable was developed for rapid detection of the protein biomarker myoglobin (Myo) as a model analyte. A screen printed electrode was modified with a molecularly imprinted material grafted on a graphite support and incorporated in a matrix composed of poly(vinyl chloride) and the plasticizer o-nitrophenyloctyl ether. The protein-imprinted material (PIM) was produced by growing a reticulated polymer around a protein template. This is followed by radical polymerization of 4-styrenesulfonic acid, 2-aminoethyl methacrylate hydrochloride, and ethylene glycol dimethacrylate. The polymeric layer was then covalently bound to the graphitic support, and Myo was added during the imprinting stage to act as a template. Non-imprinted control materials (CM) were also prepared by omitting the Myo template. Morphological and structural analysis of PIM and CM by FTIR, Raman, and SEM/EDC microscopies confirmed the modification of the graphite support. The analytical performance of the SPE was assessed by square wave voltammetry. The average limit of detection is 0.79 ��g of Myo per mL, and the slope is ���0.193��������0.006 ��A per decade. The SPE-CM cannot detect such low levels of Myo but gives a linear response at above 7.2 ��g��������mL���1, with a slope of ���0.719��������0.02 ��A per decade. Interference studies with hemoglobin, bovine serum albumin, creatinine, and sodium chloride demonstrated good selectivity for Myo. The method was successfully applied to the determination of Myo urine and is conceived to be a promising tool for screening Myo in point-of-care patients with ischemia.

Backside-surface imprinting as a new strategy to generate specific plastic antibody materials

A backside protein-surface imprinting process is presented herein as a novel way to generate specific synthetic antibody materials. The template is covalently bonded to a carboxylated-PVC supporting film previously cast on gold, let to interact with charged monomers and surrounded next by another thick polymer. This polymer is then covalently attached to a transducing element and the backside of this structure (supporting film plus template) is removed as a regular ���tape���. The new sensing layer is exposed after the full template removal, showing a high density of re-binding positions, as evidenced by SEM. To ensure that the templates have been efficiently removed, this re-binding layer was cleaned further with a proteolytic enzyme and solution washout. The final material was named MAPS, as in the back-side reading of SPAM, because it acts as a back-side imprinting of this recent approach. It was able to generate, for the first time, a specific response to a complex biomolecule from a synthetic material. Non-imprinted materials (NIMs) were also produced as blank and were used as a control of the imprinting process. All chemical modifications were followed by electrochemical techniques. This was done on a supporting film and transducing element of both MAPS and NIM. Only the MAPS-based device responded to oxLDL and the sensing layer was insensitive to other serum proteins, such as myoglobin and haemoglobin. Linear behaviour between log(C, ��g mL���1) versus charged tranfer resistance (RCT, ��) was observed by electrochemical impedance spectroscopy (EIS). Calibrations made in Fetal Calf Serum (FCS) were linear from 2.5 to 12.5 ��g mL���1 (RCT = 946.12 �� log C + 1590.7) with an R-squared of 0.9966. Overall, these were promising results towards the design of materials acting close to the natural antibodies and applied to practical use of clinical interest.

A label-free DNA aptamer-based impedance biosensor for the detection of E. coli outer membrane proteins

A label-free DNA aptamer-based impedance biosensor for the detection of E. coli outer membrane proteins (OMPs) was developed. Two single stranded DNA sequences were tested as recognition elements and compared. The aptamer capture probes were immobilized, with and without 6-mercapto-1-hexanol (MCH) on a gold electrode. Each step of the modification process was characterized by Faradaic impedance spectroscopy (FIS). A linear relationship between the electron-transfer resistance (Ret) and E. coli OMPs concentration was demonstrated in a dynamic detection range of 1 �� 10���7���2 �� 10���6 M. Moreover, the aptasensor showed selectivity despite the presence of other possible water contaminates and could be regenerated under low pH condition. The developed biosensor shows great potential to be incorporated in a biochip and used for in situ detection of E. coli OMPs in water samples.

Myoelectric Signal Monitoring System

The Electromyography (EMG) is an important tool for gait analyzes and disorders diagnoses. Traditional methods involve equipment that can disturb the analyses, being gradually substituted by different approaches, like wearable and wireless systems. The cable replacement for autonomous systems demands for technologies capable of meeting the power constraints. This work presents the development of an EMG and kinematic data capture wireless module, designed taking into account power consumption issues. This module captures and converts the analog myoeletric signal to digital, synchronously with the capture of kinetic information. Both data are time multiplexed and sent to a PC via Bluetooth link. The work carried out comprised the development of the hardware, the firmware and a graphical interface running in an external PC. The hardware was developed using the PIC18F14K22, a low power family of microcontrollers. The link was established via Bluetooth, a protocol designed for low power communication. An application was also developed to recover and trace the signal to a Graphic User Interface (GUI), coordinating the message exchange with the firmware. Results were obtained which allowed validating the conceived system in static and with the subject performing short movements. Although it was not possible to perform the tests within more dynamic movements, it is shown that it is possible to capture, transmit and display the captured data as expected. Some suggestions to improve the system performance also were made.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.