The statistical processing of electromyographic signal examination performed in the time domain ensures mostly correct classification of pathology; however, because of an ambiguity of most temporal parameter definitions, a diagnosis can include a significant error that strongly depends on the neurologist's experience. Then, selected temporal parameters are determined for each run, and their mean values are calculated. In the final stage, these mean values are compared with a standard and, including additional clinical information, a diagnosis is given. An inconvenience of this procedure is high time consumption that arises from the necessity of determination of many parameters. Additionally, an ambiguity in determination of basic temporal parameters can cause doubts when parameters found by the physician are compared with standard parameters determined in other research centers. In this paper, we present a definition for spectral discriminant that directly enables a unique diagnosis to be made. An essential advantage of the suggested discriminant is a precise and algorithmically realized definition that enables an objective comparison of examination results obtained by physicians with different experiences or working in different research centers. A suggestion of the standard for selected muscle based on a population of 70 healthy cases is presented in the Results section.

The area of military operations is a big challenge for medical support. A particularly important factor that allows medical services to react quickly in the case of mass casualties is the ability to rapidly evacuation of wounded soldiers from a battlefield. To meet this requirement, an effective medical evacuation system is essential. The paper presented the architecture of the electronically supported decision support system for medical evacuation during military operations. The system can also be used by other services such as police or fire service. The system meets the requirements for tactical combat casualty care procedures and is composed of following elements: measurement subsystem, data transmission subsystem and analysis and inference subsystem. The system, based on the continuous monitoring of selected soldiers’ vital signs and biomedical signals, automatically proposes a medical segregation of wounded soldiers (medical triage). The information on the triage was visualized using the Headquarters Management System for medical personnel (first responders, medical officers, medical evacuation groups) and for commanders, if required. All elements of the architecture were described in the paper.

Artery stiffness is a risk factor for cardiovascular disease (CVD). The measurement of pulse wave velocity (PWV) between the carotid artery and the femoral artery (cfPWV) is considered the gold standard in the assessment of arterial stiffness. A relationship between cfPWV and regional PWV has not been established. The aim of this study was to evaluate the influence of gender on arterial stiffness measured centrally and regionally in the geriatric population. The central PWV was assessed by a SphygmoCor XCEL, and the regional PWV was assessed by a new device through the photoplethysmographic measurement of multi-site arterial pulse wave velocity (MPPT). The study group included 118 patients (35 males and 83 females; mean age 77.2 ± 8.1 years). Men were characterized by statistically significantly higher values of cfPWV than women (cfPWV 10.52 m/s vs. 9.36 m/s; p = 0.001). In the measurement of regional PWV values using MPPT, no such relationship was found. Gender groups did not statistically differ in the distribution of atherosclerosis risk factors. cfPWV appears to be more accurate than regional PWV in assessing arterial stiffness in the geriatric population.

This article concerns an autocorrelation algorithm for determining a pulse wave delay. The pulse wave delay is defined as difference between the characteristic points i.e. the difference between the R wave in the electrocardiogram signal (ECG) and distinctive point in the photoplethysmogram (PPG) waveform. Obtaining values of the characteristic points (time stamps) are realized by correlation function. The known values of the time stamps can be used to estimate change of blood pressure. In the proposed algorithm using the autocorrelation function is calculated signal pattern. Then, this pattern is used for further correlation calculations. In the algorithm all the time is analysed the quality of the measured signal. In the next part of article was described method of measurement and the results calculated the time of the characteristic points to determine the pulse wave delay.