Hana Charvátová

Interactive software application for calculation of non-stationary heat conduction in a cylindrical body

In this paper we present software application used for the study of heat transfer problems that is a part of education of subject Process Engineering taught at the Tomas Bata University in Zlín. The application speeds up calculation of non‐stationary heat conduction and visualizes temperature distribution in the cylindrical body.

Video processing and 3D modelling of chest movement using MS Kinect depth sensor

General methods of video processing and three dimensional modelling have a wide range of applications in engineering, archaeology and spacial objects study. The paper is devoted to applications of these methods in biomedicine and neurology using MS Kinect depth sensor for non-contact monitoring of breathing. A special attention is paid to visualization of results and motion mapping over the selected chest area. The proposed methodology applies digital signal processing methods and functional transforms for acquired data de-noising, spectral analysis, and feature selection. Suggested method uses further the local polynomial approximation to detect extremal values of spectral components. The results verify the correspondence between the evaluations of the breathing frequency obtained from the thorax movement recorded by the depth sensor. The study proves that simple depth sensors can be used for non-contact detection of breathing frequency and for the three dimensional modelling of the chest movement. The proposed non-contact method enables to analyse breathing for diagnostic purposes and monitoring in the home environment as a component of assisted living technologies. General methodology studied form a contribution to the use of video sequences or sets of images for spacial objects modelling, their recognition, possible three dimensional printing or analysis of time evolution of their features.

Physiological and GPS data fusion

The paper deals with fusion of physiological and GPS data acquired during cycling and their analysis using general methods of multichannel signal processing. Experimental data were acquired during 17 identical cycling routes each about 12 km long including more then 1100 segments of the length 60 s recorded with the varying sampling period. The proposed algorithm includes their initial analysis, de-nosing using selected digital filters, interpolation and resampling in the first stage followed by evaluation of the cross-correlation between the heart rate and the altitude gradient of positioning data recorded by the GPS system. Results obtained present (i) relation between the heart rate and the slope with the positive regression coefficient 6.04 and (ii) the heart rate and speed with the negative regression coefficient -1.67 over all segments analyzed.

Breathing Analysis Using Thermal and Depth Imaging Camera Video Records

The paper is devoted to the study of facial region temperature changes using a simple thermal imaging camera and to the comparison of their time evolution with the pectoral area motion recorded by the MS Kinect depth sensor. The goal of this research is to propose the use of video records as alternative diagnostics of breathing disorders allowing their analysis in the home environment as well. The methods proposed include (i) specific image processing algorithms for detecting facial parts with periodic temperature changes; (ii) computational intelligence tools for analysing the associated videosequences; and (iii) digital filters and spectral estimation tools for processing the depth matrices. Machine learning applied to thermal imaging camera calibration allowed the recognition of its digital information with an accuracy close to 100% for the classification of individual temperature values. The proposed detection of breathing features was used for monitoring of physical activities by the home exercise bike. The results include a decrease of breathing temperature and its frequency after a load, with mean values −0.16 °C/min and −0.72 bpm respectively, for the given set of experiments. The proposed methods verify that thermal and depth cameras can be used as additional tools for multimodal detection of breathing patterns.

Multimodal breathing analysis in the evaluation of physical load

The paper presents specific methods of processing of multimodal data recorded during physical activities by depth MS Kinect cameras, thermal imaging cameras and heart rate sensors. All video data and heart rate signals used in the present study were recorded in the home environment. The proposed methodology includes the detection of the chest breathing area for breathing motion analysis used by the MS Kinect. For the thermal image processing the static and dynamic selection of regions of interests was performed in associated sets of images to find time evolution of respiratory signals and their temperature changes. Signal de-noising by finite impulse filters is applied both for breathing and heart rate data. Correlation analysis is used in the data processing stage to find the time relation between individual physiological variables. Results include relations between signals acquired during physical activities and they show how simple sensors can be used to increase the accuracy of standard diagnostical tools in biomedicine as well.

A Diffusion Model Of Bath Washing Extraction Of A Porous Material And An Evaluation Of Its Conformity With The Real Process

In this paper, the focus is on the definition of the mathematical conditions needed to ensure that the presented diffusion model of the extraction of a bound biopolymer impurity into the wash liquid during the bath-washing process of that porous material will be in satisfactory accordance with the real washing process from a certain calculated time. The numerical computation of the space-time volume concentration field course in the porous material by means of a diffusion model, which is mentioned in the contribution, is very helpful for the optimization of the washing processes in the chemical and tanning industries.