This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured EMG signal should be cleaned of different factors like power network interference and ECG heartbeat. Unfortunately, there are no completed studies showing full multistage signal processing of EMG recordings. In this article, the authors propose an original algorithm to perform muscle activity measurements based on raw measurements. The effectiveness of the proposed algorithm for EMG signal measurement was validated by a portable EMG system developed as a part of the EU research project and EMG raw measurement sets. Examples of removing the parasitic interferences are presented for each stage of signal processing. Finally, it is shown that the proposed processing of EMG signals enables cleaning of the EMG signal with minimal loss of the diagnostic content.

The extension for high-performance STFT (Short-Time Fourier Transform) algorithm written entirely in Java language for non-parallel computations is presented in the current paper. This solution could compete with the best available and most common algorithms supplied by libraries such as FFTW or JTransform. The main idea was to move complex computations and expensive functions to the program generation phase. Thus, only core and essential operations were executed during the runtime phase. Furthermore, new approach allows to eliminate the necessity for a rearrangement operation that uses the bit-reversal permutation technique. This article presents a brief description of the STFT solution that was worked out as an extension for the original application, in order to increase its efficiency. The solution remains a Stockham algorithm adapted using metaprogramming techniques and entails an additional reduction its execution time. Performance tests and experiments were conducted using a Java Platform and JMH library, which allowed for accurate execution time measurements. Major aspects of the Java VM like warm-up effects were also taken into consideration. Solution was applied into Electrical Capacitance Tomography measurement system in order to measure the material changes during the silo discharging industrial process.

Edge detection is a fundamental step in many computer vision systems, particularly in image segmentation and feature detection. There are a lot of algorithms for detecting edges of objects in images. This paper proposes a method based on local gradient estimation to detect metallic droplet image edges and compare the results to a contour line obtained from the active contour model of the same images, and to results from crowdsourcing to identify droplet edges at specific points. The studied images were taken at high temperatures, which makes the segmentation process particularly difficult. The comparison between the three methods shows that the proposed method is more accurate than the active contour method, especially at the point of contact between the droplet and the base. It is also shown that the reliability of the data from the crowdsourcing is as good as the edge points obtained from the local gradient estimation method.

The use of UT and EIT technologies gives the opportunity to develop new, effective, minimally invasive diagnostic methods for urology. The introduction of new diagnostic methods into medicine requires the development of new tools for collecting, processing and analysing the data obtained from them. Such system might be seen as a part of the electronic health record EHR system. The digital medical data management platform must provide the infrastructure that will make medical activity possible and effective in the presented scope. The solution presented in this article was implemented using the newest computer technologies to obtain advantages such as mobility, versatility, flexibility and scalability. The architecture of the developed platform, technological stack proposals, database structure and user interface are presented. In the course of this study, an analysis of known and available standards such as Hl7, RIM, DICOM, and tools for collecting medical data was performed, and the results obtained using them are also presented. The developed digital platform also falls into an innovative path of creating a network of sensors communicating with each other in the digital space, resulting in the implementation of the IoT (Internet of Things) vision. The issues of building software based on the architecture of microservices were discussed emphasizing the role of message brokers. The selected message brokers were also analysed in terms of available features and message transmission time.

In this paper, a case-study of the auto-focus algorithm for correcting image distortions caused by gas flow in high-temperature measurements of surface phenomena is presented. This article shows results of proposed algorithm and methods for increasing its accuracy.