The research team has developed a complex system that is capable to record and analyse various psychophysiological data. This article represents the program created in NI DIAdem which can automatically identify illnesses and generate reports based on the input and saved parameters. The created program can import data from different types of file formats. It is converted and saved in a new standardized format for further processing. It can play-back the processed data synchronized with adjustable speed, and visualize them on customized display areas. It can analyse the data based on the input parameters and the pre-defined mathematical equations. The program displays the input and calculated parameters, the results and the detected illnesses on automatically generated reports.

Our research team has developed a system and methodology for measuring psycho-physiological parameters, which can be used to determine the level of fatigue and fitness of the person being measured. This article describes the electroencephalography (EEG) part of this system. This article covers the technical and mathematical background of EEG measurement, the selection and implementation of the measurement tool in the development environment, and the development of the measurement and processing algorithm. The result is a system that can detect, digitize, and process the digitized signal from the brain, and save the processed signal in an XML database.

In this project an ECG measurement and wave identification system was made. The measuring system hardware is based on a Texas Instruments ADS1298ECG amplifier and analog-to-digital converter board. The measurement and processing software was created in LabVIEW environment using the built-in functions of the Biomedical toolkit. Initially, the theory behind heartbeat and its effect on the skin surface potential are presented. Then the measurement techniques of these are described. The research group provide information on the mathematical background of how the ECG curve is processed and the waves are identified. The HRV analysis, the statistical analysis of identified R waves are described. Subsequently, publications dealing with electrocardiographic examinations in various fields will be presented. Then an overview of the specifications of the amplifiers used in this work and the capabilities of their original software are given. The final device structure is presented. The system validation process and the properties of the reference devices are illustrated.