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Physiocrate: A SignalPlant Toolbox for Respiratory, Blood Pressure and EMG Signal Analysis
Nejedlý, Petr ; Virgala, Jan
The paper presented here describes the SignalPlant library for analysis of physiological signals. This library contains plugins for analysis of continuous blood pressure (BP), respiratory signals (RESP) and electromyographic signals (EMG). Its principal advantages are real-time previews of results, ease of use and a multi-thread approach. The library is available free and open- source under an MIT license as part of the SignalPlant project at https://signalplant.codeplex.com.
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Signal analysis options on Arduino platform
Havlíček, Michal ; Zuth, Daniel (referee) ; Huzlík, Rostislav (advisor)
The aim of this bachelors thesis is to analyse signal with Arduino platform by creation of program which is able to perform calculations of signal´s mean value, efficiency value, Fourier transform and subsequent export of these results into computes. Furthermore it examines testing of this program and evaluation of possible limitations with usage of Arduino platform.
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Analysis of Thick Film Amperometrical Sensors Signal and Its Usage for Measurement and Characterization of Enzymes
Ondruch, Vít ; Kizek, René (referee) ; Masojídek,, Jiří (referee) ; Vrba, Radimír (advisor)
V práci je popsán princip synchronní detekce (SD), který byl uplatněn při měření s biosenzory. Metoda SD umožňuje dosažení výrazně lepšího poměru signálu k šumu, vyššího limitu detekce a celkové zlepšení robustnosti měření. Uplatnění SD při měření s biosenzory umožní zlepšit analýzu jeho odezvy a umožní odstranění nežádoucích interferencí nebo šumů, které mohou být způsobeny například mícháním roztoku, elektromagnetickými vlivy nebo parazitními proudy. SD také umožňuje rozložit získaný signál na odezvu stimulace a na dlouhodobý signál jiného procesu, a dále také identifikovat jevy druhého řádu. Pro identifikaci stimulačního signálu ve výstupním signálu měření byl na základě lineárního statistického modelu vyvinut specializovaný software. SD byla ověřena na modelovém případu výstupního signálu biosenzoru s aplikovaným komplexem fotosystému II (PSII) a jeho odezvě na stimulaci světlem. Odezva PSII se řídí kinetikou prvního řádu a může být také ovlivněna inhibitory. Kinetické konstanty vazby herbicidu na PSII závisí lineárně na koncentraci herbicidu. To umožňuje jejich měření také při nízkých koncentracích herbicidu.
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Measurement and analysis of dynamic properties of rotating machine parts
Gofroň, Vojtěch ; Hadaš, Zdeněk (referee) ; Houška, Pavel (advisor)
Diploma thesis focuses on measurement and analysis of shaft motion, torque, angular velocity and vibration. First part of the thesis deals with general issue of acquiring a digital signal. Next part describes suitable sensors for each measurement type, and data acquisition hardware. The last theoretical part describes methods for measurement data analysis and vibration diagnostics. Practical part of the thesis describes shaft motion and torque measurements made on laboratory equipment, and vibration measurement made on real machine system. Each measurement includes measurement data analysis and evaluation.
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Measurement and signal processing with myRio kit
Heteš, Marek ; Spáčil, Tomáš (referee) ; Kšica, Filip (advisor)
This thesis deals with research of options for data acquisition and signal analysis, of the myRIO kit and LabVIEW platform. Next it describes the design of application for data acquisition and signal analysis, and the last chapter of this thesis is about testing and a practical demonstration of our application.
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Signal Analysis
Vávra, Pavel ; Keprt, Jiří (referee) ; Beneš, Petr (advisor)
This thesis deals with problem of analysis signal acquiring measurement of uniformity motion harmonic drive and planetary gearboxes. In introduction part are explain some features of FFT and concept of cepstrum. Further is present overview of most often measured parameters of these gearboxes and needed formulas, which express connections among particular mechanical parts of gearboxes. The next part deals with description of SW program unit generated in LabView environment, which is output product of work and makes analysis on measured courses.
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Train Identification System at Railway Switches And Crossings Using Advanced Machine Learning Methods
Krč, Rostislav ; Vorel,, Jan (referee) ; Plášek, Otto (referee) ; Podroužek, Jan (advisor)
This doctoral thesis elaborates possibilities of automatic train type identification in railway S&C using accelerometer data. Current state-of-the-art was considered, including requirements stated by research projects such as S-Code, In2Track or Turnout 4.0. Conducted experiments considered different architectures of artificial neural networks (ANN) and statistically evaluated multiple use case scenarios. The resulting accuracy reached up to 89.2% for convolutional neural network (CNN), which was selected as a suitable baseline architecture for further experiments. High generalization capability was observed as models trained on data from one location were able to classify locomotive types in the other location. Further experiments evaluated the effect of signal filtering and denoising. Evaluation of allocated memory and processing time for pre-trained models proved feasibility for in-situ application with regard to hardware restrictions. Due to a limited amount of available accelerometer data, distribution grid power demand data were utilized for further refinement of the proposed CNN architecture. Deep multi-layer architecture with regularization techniques such as dropout or batch normalization provides state-of-the-art performance for time series classification problems. Class activation mapping (CAM) allowed an explanation of decisions made by the neural network. Presented results proved that train type identification directly in the S&C is possible. The CNN was selected as optimal architecture for this task due to high classification accuracy, automatic filtration, and pattern recognition capabilities, allowing for the incorporation of the end-to-end learning strategy. Moreover, direct on-site application of pre-trained models is feasible with respect to limitations of in-situ hardware. This thesis contributes to understanding the train type identification problem and provides a solid theoretical background for future research.
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Processing of signals from fiber optic sensors
Sikora, Vojtěch ; Urban, František (referee) ; Čučka, Milan (advisor)
First two chapters of this paper deals with the division of optical fiber sensors, digital signal processing and includes price comparison of four experimental sensors. In chapter three analysis, description and evaluation of measurment has been demonstrated on Mach - Zehnder interferometer. Last chapter is about application for signal analysis from vibration sensors. Description contains snippets from source code and graphical user interface. This paper includes three fields - fiber optics, digital signal processing and creation of application - and thanks to them it provides solid basis for study of optic fiber sensors.
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Measurement of the respiratory sounds
Gottvald, Martin ; Rychtárik, Milan (referee) ; Kolář, Radim (advisor)
Respiratory sounds measurment This thesis deals with respiratory sounds analysis and measurment using digitalizing measuring cards and LabView environment. The anatomy of respiratory system is described, including each of its fractions and disturbances related to the respiratory system. The design of respiratory sounds amplifier is described, but wasn´t used considering the interferences of measured signal caused by the power-line frequency which results in substantial distortions. That's why, the previously recorded respiratory sounds were used for analysis in Matlab. The measuring program was designed in LabView, which alows signal recording from using acquisition card input and further processing.
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Recognition of musical recordings
Masár, Igor ; Horka, Michal (referee) ; Sigmund, Milan (advisor)
This thesis analyzes the specific audio signal-music. It describes the basic methods of analysis of musical signals. The following are mentioned the most common music file formats and the possibility of cross transfer. There are explained terms of music theory, which are also present in this work. They are described and created three ways of detecting melody. It is selected optimal algorithm based on the successful detection of the reference melodies recordings. User interface is created in MATLAB GUI allows recognition of recordings. This interface is tested on few melodies.
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