National Repository of Grey Literature 93 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Muscle noise filtering in ECG signals
Fedorov, Vasilii ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This work deals with problematic of muscle noise filtration in ECG signals. It contains theoretical and practical parts. In theoretical part we first mentioned a topicality of ECG scanning and filtration. Then we got acquainted with the origin of ECG, it's properties, and types of noises, that typically occurring there. Further different known methods of linear and non-linear techniques in EMG filtration were discussed. After we got acquainted with wavelet transform and its possibilities practical part was carried out in environment MATLAB 2020b®. Wiener wavelet filter was implemented and supplemented by a threshold adaptive function. Parameters were optimized with brute force method in reduced range. The evaluation of the filter took place on a CSE database, where the results were compared with the authors of other methods. In result the filter shows good filtration capabilities and stability.
ECG and PPG derived respiration estimation
Chmela, Radek ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This work deals with the estimation of the respiratory curve from ECG and PPG signals. The first part deals with the description and monitoring of electrical activity of the heart, physiology and methodology of respiratory sensing and photoplethysmography. The second part deals with methods of extracting respiratory cycle information from ECG and PPG recordings. The third part deals with the algorithmic implementation and evaluation of individual procedures for estimating the breath curve from both of the above-mentioned signals on records from the web PhysioNet. In the last part, the algorithms are compared and evaluated.
Human activity classification
Müller, Jakub ; Smital, Lukáš (referee) ; Smíšek, Radovan (advisor)
This bachelor's thesis describes daily activity classification using accelerometric data. The first theoretical part summarizes the basics about daily activity and benefits that we get from monitoring it. In the next part of theory the principles of accelerometer inner workings are described. The last part of theory is dedicated to explaining the basics of neural networks and SVM. The aim of the practical part was to find a suitable dataset from a publicaly shared database, containing daily activity accelerometric data and also to collect our own data. Then performing classification using our own algorithm, optimizing it and finally evaluating the results.
Breathing Rate Estimation from the Electrocardiogram and Photoplethysmogram
Janáková, Jaroslava ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
The master thesis deals with the issue of gaining the respiratory rate from ECG and PPG signals, which are not only in clinical practice widely used measurable signals. The theoretical part of the work outlines the issue of obtaining a breath curve from these signals. The practical part of the work is focused on the implementation of five selected methods and their final evaluation and comparison.
ECG quality evaluation
Vencel, Michal ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
This seminar work deals with the topic of evaluating the quality of ECG signals. The introductory chapters explain the basic characteristics of ECG signals - measurement, the form of the measured signal, methods of analysis. The cardiac physiology and pathology is presented. The most common types of noise that occur in ECG signals are also mentioned. Further, the reader is acquainted with the importance of the issue of evaluating the quality of ECG signals. In the practical part of the work, two own methods for ECG quality evaluation are presented. First, a brief theoretical introduction to the techniques used in the creation of methoda is given, followed by a description of the principle of algorithms. In order to compare the functionality of the proposed methods, three more methods from other authors are presented. Their principle is briefly described. In the final chapter, all methods are subjected to functionality testing. The results are examined and all methods are compared with each other.
ECG based human authentication and identification
Waloszek, Vojtěch ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
In the past years, utilization of ECG for verification and identification in biometry is investigated. The topic is investigated in this thesis. Recordings from ECG ID database from PhysioNet and our own ECG recordings recorded using Apple Watch 4 are used for training and testing this method. Many of the existing methods have proven the possibility of using ECG for biometry, however they were using clinical ECG devices. This thesis investigates using recordings from wearable devices, specifically smart watch. 16 features are extracted from ECG recordings and a random forest classifier is used for verification and identification. The features include time intervals between fiducial points, voltage difference between fiducial points and PR intervals variability in a recording. The average performance of verification model of 14 people is TRR 96,19 %, TAR 84,25 %.
PPG signal quality estimation and analysis
Trnková, Simona ; Smital, Lukáš (referee) ; Němcová, Andrea (advisor)
This work focuses on the PPG signals, data acquisition using smartphones, signal characteristic, types of noise, quality estimation and analysis. The aim of the work is to design the alghoritm to signal quality estimation and test this alghoritm using analysis of PPG signals acquired by smartphones.
Biometric fingerprint identification
Dašek, Filip ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
In biometrics we use distinctive physical features for identification and verification of identity. The most famous technique is identification by fingerprints. This technique use unique structure created by papillary lines for unambiguous identification. Thesis contains methods which were created throughout the years for analysis and adjustments of fingerprint. The algorithm is based on compairng two pairs of minitua and calculating transform matrix for correct alignment. Algorithm is tested on dataset created from LivDet databases. Performance of algorithm is represented by value EER which is compared with EERs of other algorithms tested in FVC 2006.
Biometric fingerprint identification
Dašek, Filip ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
In biometrics we use distinctive physical features for identification and verification of identity. The most famous technique is identification by fingerprints. This technique use unique structure created by papillary lines for unambiguous identification. Thesis contains methods which were created throughout the years for analysis and adjustments of fingerprint. The algorithm is based on compairng two pairs of minitua and calculating transform matrix for correct alignment

National Repository of Grey Literature : 93 records found   1 - 10nextend  jump to record:
Interested in being notified about new results for this query?
Subscribe to the RSS feed.