Arrhythmia detection algorithms require the exact and instantaneous detection of fiducial points in the ECG signal. These fiducial points (QRS-complex, P- and T-wave) correspond to distinct cardiac contraction phases. The performance evaluation of different fiducial points detection algorithms require the existence of large databases (DBs) encompassing reference annotations. Up to last year, P- and T-wave annotations were only available for the QT DB. This was addressed by Elgendi et al. who provided P- and T-wave annotations to the MIT-BIH arrhythmia DB. A variety of ECG fiducial points detection algorithms exists in literature, whereas, to the best knowledge of the authors, we could not identify any single-lead algorithm ready for instantaneous P- and T-wave detection. In this work, we present three P- and T-wave detection algorithms: a revised version for QRS detection using line fitting capable to detect P- and T-wave, an expeditious version of a wavelet based ECG delineation algorithm, and a fast naive fiducial points detection algorithm. The fast naive fiducial points detection algorithm performed best on both DBs with sensitivities ranging from 73.0% (P-wave detection, error interval of ± 40 ms) to 89.4% (T-wave detection, error interval of ± 80 ms). As this algorithm detects a wave event in every search window, it has to be investigated how this affects arrhythmia detection algorithms. The reference Matlab implementations are available for download to encourage the development of high-accurate and automated ECG processing algorithms for the integration in daily life using mobile computers.

Far too many people are dying from stroke or other heart related diseases each year. Early detection of abnormal heart rhythm could trigger the timely presentation to the emergency department or outpatient unit. Smartphones are an integral part of everyone;s life and they form the ideal basis for mobile monitoring and real-time analysis of signals related to the human heart. In this work, we investigated the performance of arrhythmia classification systems using only features calculated from the time instances of individual heart beats. We built a sinusoidal model using N (N = 10, 15, 20) consecutive RR intervals to predict the (N+1)th RR interval. The integration of the innovative sinusoidal regression feature, together with the amplitude and phase of the proposed sinusoidal model, led to an increase in the mean class-dependent classification accuracies. Best mean class-dependent classification accuracies of 90% were achieved using a Naïve Bayes classifier. Well-performing realtime analysis arrhythmia classification algorithms using only the time instances of individual heart beats could have a tremendous impact in reducing healthcare costs and reducing the high number of deaths related to cardiovascular diseases.

Some current object-oriented analysis methods provide use cases. Scenarios or similar concepts to describe functional requirements for software systems. The authors introduced the use case point method to measure the size of large-scale software systems based on such requirements specifications. With the measured size and the measured effort the real productivity can be calculated in terms of delivered functionality. In the status report they summarize the experiences made with size metrics and productivity rates at a major Swiss banking institute. They analyzed the quality of requirements documents and the measured use case points in order to test and calibrate the use case point method. Experiences are based on empirical data of a productivity benchmark of 23 measured projects (quantitative analysis), 64 evaluated questionnaires of project members and 11 post benchmark interviews held with selected project managers (qualitative analysis).

Most current object modeling methods and tools have weaknesses both in the concepts of hierarchical decomposition and in the visualization of these hierarchies. Some methods do not support hierarchical decomposition at all. Those methods which do employ tools that provide explosive zoom as the only means for the visualization of hierarchies. The authors present an approach for the visualization of hierarchical object models based on the notion of fisheye views. This concept integrates local detail and global context of a view in the same diagram and eases navigation in hierarchical structures without offending the principle of abstraction. The work is part of an effort to create a method and language called ADORA that provides strong support for hierarchical decomposition.