A microcontroller-based portable electrocardiograph recorder

We describe a low cost portable Holter design that can be implemented with off-the-shelf components. The recorder is battery powered and includes a graphical display and keyboard. The recorder is capable of acquiring up to 48 hours of continuous electrocardiogram data at a sample rate of up to 250 Hz.     

Diagnosis of learner dropout based on learning styles for online distance learning

The amount of data generated by computer systems in Online Distance Learning (ODL) contains rich information. One example of this information we define as the Learner Learning Trail (LLT), which is the sequence of interactions between the students and the virtual environment. Another example is the Learner Learning Style (LLS), which is associated with the student behavior and choices during the learning process. This information can be used to identify learner behavior and learning style. We perceived, after the study of related literature, that the research field of learner diagnosis for ODL does not apply the conjoint use of LLT and LLS. In this article, we propose a model capable of integrating data generated from the behavior of students in ODL with cognitive aspects of them, such as their Learning Styles, by crossing LLT with LLS. We also propose the CPAD method (Collect, Preprocessing, Analysis, Diagnosis), which is implemented by collecting the raw data regarding learning activities, preprocessing the data into structured time sequences, analyzing the sequences regarding the learning styles and using this analysis to diagnose the learner behavior. We selected the dropout to investigate, once the dropout rate in ODL is a real problem in universities around the world. In addition, the dropout is a student decision which can be associated with previous students behaviors. We performed a study with 202 learners to evaluate if learning styles are capable of explaining aspects of the student behavior. The results suggest that Sequential/Global learning style dimension is more capable of explaining the dropout than the other dimensions. Also, we performed four classification experiments to verify how the dimensions of Felder-Silverman Learning Style Model influence the learner diagnosis. We perceived that the Sequential/Global dimension could provide a higher accuracy average with lower variation independently of the diagnosis technique.     

An anisotropic microsphere-based approach for fiber orientation adaptation in soft tissue

Evolutionary processes in biological tissue, such as adaptation or remodeling, represent an enterprising area of research. In this paper, we present a multiscale model for the remodeling of fibered structures, such as bundles of collagen fibrils. With this aim, we introduce a von Mises statistical distribution function to account for the directional dispersion of the fibrils, and we remodel the underlying fibrils by changing their orientation. To numerically compute this process, we make use of the microsphere approach, which provides a useful multiscale tool for homogenizing the microstructure behavior, related to the fibrils of the bundle, in the macroscale of the problem. The results show how the fibrils respond to the stimulus by reorientation of their structure. This process leads to a stiffer material eventually reaching a stationary state. These results are in agreement with those reported in the literature, and they characterize the adaptation of biological tissue to external stimuli.     

Extraction and analysis of T waves in electrocardiograms during atrial flutter

Analysis of T waves in the ECG is an essential clinical tool for diagnosis, monitoring, and follow-up of patients with heart dysfunction. During atrial flutter, this analysis has been so far limited by the perturbation of flutter waves superimposed over the T wave. This paper presents a method based on missing data interpolation for eliminating flutter waves from the ECG during atrial flutter. To cope with the correlation between atrial and ventricular electrical activations, the CLEAN deconvolution algorithm was applied to reconstruct the spectrum of the atrial component of the ECG from signal segments corresponding to TQ intervals. The locations of these TQ intervals, where the atrial contribution is presumably dominant, were identified iteratively. The algorithm yields the extracted atrial and ventricular contributions to the ECG. Standard T-wave morphology parameters (T-wave amplitude, T peak-T end duration, QT interval) were measured. This technique was validated using synthetic signals, compared to average beat subtraction in a patient with a pacemaker, and tested on pseudo-orthogonal ECGs from patients in atrial flutter. Results demonstrated improvements in accuracy and robustness of T-wave analysis as compared to current clinical practice.     

Rayleigh mixture model for plaque characterization in intravascular ultrasound

Vulnerable plaques are the major cause of carotid and coronary vascular problems, such as heart attack or stroke. A correct modeling of plaque echomorphology and composition can help the identification of such lesions. The Rayleigh distribution is widely used to describe (nearly) homogeneous areas in ultrasound images. Since plaques may contain tissues with heterogeneous regions, more complex distributions depending on multiple parameters are usually needed, such as Rice, K or Nakagami distributions. In such cases, the problem formulation becomes more complex, and the optimization procedure to estimate the plaque echomorphology is more difficult. Here, we propose to model the tissue echomorphology by means of a mixture of Rayleigh distributions, known as the Rayleigh mixture model (RMM). The problem formulation is still simple, but its ability to describe complex textural patterns is very powerful. In this paper, we present a method for the automatic estimation of the RMM mixture parameters by means of the expectation maximization algorithm, which aims at characterizing tissue echomorphology in ultrasound (US). The performance of the proposed model is evaluated with a database of in vitro intravascular US cases. We show that the mixture coefficients and Rayleigh parameters explicitly derived from the mixture model are able to accurately describe different plaque types and to significantly improve the characterization performance of an already existing methodology.     

Motion Compensated Three-Dimensional Frequency Selective Extrapolation for improved error concealment in video communication

During transmission of video data over error-prone channels the risk of getting severe image distortions due to transmission errors is ubiquitous. To deal with image distortions at decoder side, error concealment is applied. This article presents Motion Compensated Three-Dimensional Frequency Selective Extrapolation, a novel spatio-temporal error concealment algorithm. The algorithm uses fractional-pel motion estimation and compensation as initial step, being followed by the generation of a model of the distorted signal. The model generation is conducted by an enhanced version of Three-Dimensional Frequency Selective Extrapolation, an existing error concealment algorithm. Compared to this existent algorithm, the proposed one yields an improvement in concealment quality of up to 1.64 dB PSNR. Altogether, the incorporation of motion compensation and the improved model generation extends the already high extrapolation quality of the underlying Frequency Selective Extrapolation, resulting in a gain of more than 3 dB compared to other well-known error concealment algorithms.     

A framework for network quality monitoring in the VoIP environment

Monitoring speech quality in Voice over IP (VoIP) networks is important to ensure a minimal acceptable level of speech quality for IP calls running through a managed network. Information such as packet loss, codec type, jitter, end‐to‐end delay and overall speech quality enables the network manager to verify and accurately tune parameters in order to adjust network problems. The present article proposes the deployment of a monitoring architecture that collects, stores and displays speech quality information about concluded voice calls. This architecture is based on our proposed MIB (Management Information Base) VOIPQOS, deployed for speech quality monitoring purposes. Currently, the architecture is totally implemented, but under adjustment and validation tests. In the future, the VOIPQOS MIB can be expanded to automatically analyze collected data and control VoIP clients and network parameters for tuning the overall speech quality of ongoing calls. Copyright © 2006 John Wiley & Sons, Ltd.     

Detection of Channel Variations to Improve Channel Estimation Methods

In current digital communication systems, channel information is typically acquired by supervised approaches that use pilot symbols included in the transmit frames. Given that pilot symbols do not convey user data, they penalize throughput spectral efficiency, and transmit energy consumption of the system. Unsupervised channel estimation algorithms could be used to mitigate the aforementioned drawbacks although they present higher computational complexity than that offered by supervised ones. This paper proposes a simple decision method suitable for slowly varying channels to determine whether the channel has suffered a significant variation, which requires to estimate the matrix of the recently changed channel. Otherwise, a previous estimate is used to recover the transmitted symbols. The main advantage of this method is that the decision criterion is only based on information acquired during the time frame synchronization, which is carried out at the receiver. We show that the proposed criterion provides a considerable improvement of computational complexity for both supervised and unsupervised methods, without incurring in a penalization in terms of symbol error ratio. Specifically, we consider systems that make use of the popular Alamouti code. Performance evaluation is accomplished by means of simulated channels as well as making use of indoor wireless channels measured using a testbed.     

Adaptive Turbo Coded Modulation for Shallow Underwater Acoustic Communications

In this paper the performance of a wireless communications system over shallow underwater acoustic channels is investigated when adaptive modulation and coding techniques with receiver diversity are used. It is assumed that the communication system experiences Ricean shadowed fading. We obtain the analytical figures of the proposed rate-adaptive transmission schemes, emphasizing in the spectral efficiency and the average bit error rate. These analytical expressions are compared to Monte-Carlo simulations corroborating the analytical results.     

Wireless Sensor Networks in IPv4/IPv6 Transition Scenarios

The wireless sensor networks (WSNs) concept was appeared in the middle of 90s and have been a subject under intensive research in the past few years. Several factors have contributed to this, but the potential for application of WSNs in almost every aspect of day-to-day life is the predominant one. This type of networks has been developed using proprietary solutions instead of standard solutions. More recently, the importance of standards motivated the use of IETF standards in WSNs, making the Internet integration easier. However, more efforts are necessary in order to provide a full integration. The WSNs use mainly IPv6 protocol, but the IPv4 is the predominant one in the Internet. As a consequence, IPv4 to IPv6 transition mechanisms must be provided to allow the interaction between all Internet connected devices independently of the supported IP version. It is also critical to provide a standard application interface to make easier the application development and independently of the hardware platform used. The RESTfull Web services can provide this standard interface. So, combine RESTfull Web services with IPv4 to IPv6 transition mechanisms can increase the WSN services dissemination. The transition mechanisms and the REST Web services are supported in the gateway in order to save the wireless sensor device resources’. The smartphone with Internet connectivity can also be the drive to the WSNs growth, because user-friendly applications can be used to retrieve and collect sensed data. This paper proposes a solution based on REST web services to permit the interaction between a mobile application and the IPv6 compliant WSN.