A. F. da Rocha

Development of a Matlab software for analysis of heart rate variability

The analysis of heart rate variability (HRV) signals is an important tool for studying the autonomic nervous system, as it allows the evaluation of the balance between the sympathetic and parasympathetic influences on heart rhythm. This paper presents a tool for analysis of HRV called ECGLab, which was developed in Matlab language in order to help research on HRV by making the analysis process faster and easier. The software obtains the HRV signal by using an automatic QRS detection algorithm. The user can inspect the ECG and correct mistakes in the detection process, and also identify ectopic beats. Importing RR intervals from previously typed ASCII files is also possible. Some of the most popular HRV analysis techniques were implemented: statistical and time series analysis, spectral analysis (using FFT, autoregressive and Lomb methods), Poincare plot analysis and sequential trend analysis.

A New Wavelet-Based Algorithm for Compression of Emg Signals

Despite the growing interest in the transmission and storage of electromyographic signals for long periods of time, only a few studies dealt with the compression of these signals. In this article we propose a novel algorithm for EMG signal compression using the wavelet transform. For EMG signals acquired during isometric contractions, the proposed algorithm provided compression factors ranging from 50 to 90%, with an average PRD ranging from 1.4 to 7.5%. The proposed method uses a new scheme for normalizing the wavelet coefficients. The wavelet coefficients are quantized using dynamic bit allocation, which is carried out by a Kohonen Neural Network. After the quantization, these coefficients are encoded using an arithmetic encoder. The compression results using the proposed algorithm were compared to other algorithms based on the wavelet transform. The proposed algorithm had a better performance in compression ratio and fidelity of the reconstructed signal.

A new biomechanical hand prosthesis controlled by surface electromyographic signals

This paper describes the development of a low-cost hand prosthesis for use in patients with an amputated hand due to congenital problems or to trauma wound, who possess a part or the forearm endowed with muscular activity. The paper covers the constructive aspects of both mechanical and electronic designs. The prototype is controlled by electromyographic signals measured at the remaining part of the injured limb of the patient. The EMG signals are measured at the surface of the skin, at a point that is close to a working muscle of the amputated arm. The prosthesis allows the patient to hold objects by means of a three finger clamp. The prosthesis presented an excellent performance in preliminary tests with an amputated patient. These tests showed that the prosthesis had a very good performance regarding force and speed.

Adaptive Knee Joint Control for an Active Amputee Prosthesis

This work presents the design and evaluation of knee joint controllers for an above-knee prosthesis. The prototype is a three degree of freedom prosthesis which is planned to be controlled in part by EMG thigh signals, in part by a predictive trajectory generator based on multisensorial data such that the foot can be correctly positioned with respect the floor. There is described a simplified non-linear dynamic model for the knee opening angle. The model parameter identification is made using a least squares batch estimator. Based on the estimated non-linear model, two strategies for joint controllers are designed: PID and model reference adaptive controller. The PID design follows a root locus approach with experimental tuning. Preliminary tests were performed in a platform built for the prosthesis under development. The results discussed in this paper reveals the difficulty in controlling such a nonlinear plant.

A surgical device for radiofrequency ablation of large liver tumors.

Radiofrequency ablation has become an accepted treatment option of patients with primary and metastatic liver tumors. We propose an ablation electrode array consisting of 4-8 blade shaped electrodes arranged in a circular geometry for the treatment of large liver tumors. We developed a 3D code based on the finite difference method for evaluating the effect of different numbers of electrodes (4, 6 and 8) and electrode distance on lesion size. The configuration with six electrodes can ablate a volume of 70 x 70 x 40 mm(3) in approximately 5 min, with tissue temperature above 50 degrees C throughout the treatment volume. We then performed an experimental study in polyacrylamide gel in order to validate the theoretical results. The average temperature error between the simulation and the experiment was 3.8% at the center of the electrode array. This study shows that the proposed device potentially allows more rapid treatment of large tumors than current radiofrequency ablation devices.

A Framework for Automated Evidence Gathering with Mobile Systems Using Bayesian Networks

This article presents a framework that allows the automated gathering of medical evidence, using a methodology based on Bayesian networks (BN). For such purpose, system software and a programming methodology were developed. The proposed methodology is generic and can be applied to different contexts (application domains) were evidence gathering is executed in mobile devices.

Algoritmo de Máxima Verossimilhança para a Estimação da Velocidade de Condução Média de Sinais Eletromiográficos de Superfície

Surface electromyographic signals may be acquired using multi-channel electrodes, allowing the estimation of important characteristics, like the motor unit or single fiber conduction velocity (CV). This work presents an algorithm to minimize the mean square error of the estimation of the delay between signals from different channels spaced between one another by the inter-electrode distance (IED). Considering the CV constant during voluntary isometric contractions of low intensity, and knowing the IED, the estimation of the delay between adjacent channels allows the direct calculation of the mean CV. In this work, in order to increase accuracy, the problem is moved to the frequency domain. A numeric method is presented to accelerate the mean square error minimization time. As a result, it was observed that the use of more channels within the calculations leads to smaller variances of the CV estimative, if all the channels considered are located between the innervation zone and the tendon region.

Coding of Echocardiographic Image by Selection of the Normalization Matrix Using Fuzzy Logic

This article presents an algorithm for compression of echocardiographic images. The algorithm is based on the JPEG algorithm and uses a fuzzy inference system to adapt the normalization process of the transformed coefficients through the analysis of the local characteristics of echocardiographic images. The images considered in this paper were acquired in actual echocardiography exams. The proposed encoder guarantees a maximum local signal-to-noise ratio, which is adapted to the characteristics of each sub-block of the image

Including affectivity requirements in embedded systems

This paper proposes an embedded system development process capable to deal with affectivity requirements. It is supported by W3C tools, such as EmotionML and SysML. These tools should be used to specify cognition and affectivity as system requirements. The proposed process is based on three different integration models: Sparxs [1], Wolfs System Development Process [4] and Russells Intelligent Agent Specification [5]. In order to validate this proposal a pet robot case study has been built. This application can be useful in many non-critical domestic applications, such as assistive robots for capturing attention of autistic children and robot therapy for elders. Moreover, it represents a futuristic embedded system design space for applying affective computing.

A new heuristics/GA-based algorithm for the management of the S-DRWA in IP/WDM networks

This work presents the design and validation of a new hybrid Heuristic-Genetic Algorithm (HGA) for the management of the Survivability Dynamic Routed and Wavelength Assignment (S-DRWA), based on lightpath protection sharing, and applied on a IP/WDM transport network.