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Identification of sleep disorders based on actigraphy data and sleep diaries
Molík, Miroslav ; Mekyska, Jiří (referee) ; Mikulec, Marek (advisor)
This master’s thesis deals with prediction of Parkinson's disease using sleep parameters from actigraphy and sleep diaries. The goal is to design a machine learning approach, which will be able to recognize pacients suffering from Parkinson's disease. For training dataset supplied by St. Anne's University Hospital Brno was used, which was variously modified for achieving best possible results. These adjustments were evaluated according to the results of the trained models and based on these results, two models (achieving test accuracies of 85 and 82%) were selected.
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Analysis of sleep EEG signal
Ježek, Martin ; Kozumplík, Jiří (referee) ; Rozman, Jiří (advisor)
Cílem této práce byl vývoj programu pro automatickou detekci arousalu v signálu spánkového EEG s použitím metod časově-frekvenční analýzy. Předmětem studie bylo 13 celonočních polysomnografických nahrávek (čtyři svody EEG, EMG, EKG a EOG), tj. celkově více než 100 hodin záznamu. Jednalo se o část dat z dřívějších výzkumných prací expertní lékařky v problematice spánku Dr. Emilie Sforzy, Ženeva, Švýcarsko, která rovněž poskytla základní hodnocení těchto dat. V záznamech bylo celkem označeno 1551 arousal událostí. Pro usnadnění výběru konkrétní metody časově-frekvenční analýzy byla následně vytvořena sada nástrojů pro vizualizaci jednotlivých signálů a jejich různých časově-frekvenčních vyjádření. S ohledem na závěry vizuální analýzy, charakter signálu EEG a efektivitu výpočetních metod byla pro analýzu vybrána waveletová transformace s mateřskou vlnkou Daubechies řádu 6. Jednotlivé svody EEG byly dekomponovány do šesti frekvenčních pásem. Z takto odvozených signálů a signálu EMG byly následně stanoveny ukazatele možné přítomnosti události arousalu. Tyto ukazatele byly dále váhovány lineárním klasifikátorem, jehož hodnoty vah byly optimalizovány pomocí genetického algoritmu. Na základě hodnoty lineárního klasifikátoru bylo rozhodnuto o přítomnosti události arousalu v daném svodě EEG – arousal byl detekován, jestliže hodnota klasifikátoru překročila danou mez na dobu více než 3 a méně než 30 vteřin. V celém záznamu pak byl arousal označen, byl-li detekován alespoň v jednom ze svodů EEG. Následně byly odvozeny míry senzitivity a selektivity detekce, jež byly rovněž základem pro stanovení fitness funkce genetického algoritmu. Pro učení genetického algoritmu byly vybrány první čtyři záznamy. Na základě takto optimalizovaných vah vznikl program pro automatickou detekci, který na celém souboru 13 záznamů dosáhl ve srovnání s expertním hodnocením míry senzitivity 76,09%, selektivity 53,26% a specificity 97,66%.
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Smart Nightstand Device
Vávra, Jan ; Žák, Jaromír (referee) ; Macháň, Ladislav (advisor)
Master’s thesis describes design of smart nightstand device. Aim of this system is to monitor and recognize stages of sleep with subsequent transfer of the data to alarm clock to provide the most comfortable awakening. The alarm clock is backed up by batteries. The system controls parameters of surrounding environment using advanced sensors. The device is equipped with a removable light part which is backed up by power supply for illumination during a potential power outage. A pad for wireless charging with standard Qi is also part of this system.
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Sleep quality assessment
Benáček, Petr ; Králík, Martin (referee) ; Ronzhina, Marina (advisor)
The topic of this bachelor thesis is an automatic sleep quality assessment using artificial neural network. To assess the quality of sleep were used the movement and heart rate data measured by Apple Watch smartwatch. From these data, statistical variables were calculated. Then were they used as an input to the neural networks. The goal was to automatically identify sleep and wakefulness. In this case, the sensitivity was 89 % and the specificity was 70 %. These values are comparable with other studies. Furthermore, the data were also divided into categories W (wakefulness), NON REM and REM. Parameters evaluating sleep quality, such as TST, % REM or sleep latency, were derived from the output of the neural networks created.
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Sleep apnea detection from ECG records
Trnková, Simona ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
The aim of this work is to propose an algorithm for the detection of sleep apnea from the respiratory signal that was extracted from the ECG signal. The work includes the theory of sleep medicine, methods for extracting the respiratory curve from the ECG signal and methods for detecting apnoeic sections. In the practical part, the algorithm for estimating the breathing curve and models classifying apnoeic sections are described and evaluated.
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Advanced Alarm Clock for Windows Phone 7
Zapletal, Josef ; Kajan, Rudolf (referee) ; Herout, Adam (advisor)
This bachelor thesis describes the development of mobile application for Windows Phone 7 focused on sleep and awakening the user. The application is very easy to use and uses built-in modules of advanced mobile phones, such as high resolution camera and the accelerometer. This thesis describes the main features of Windows Phone 7 platform, analysis of competing solutions, application concept and its implementation. Furthermore, this work describes the solution of various problems in the development and also provides examples of methods and tools. Finally, there is also a list of used libraries.
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Powerline control of home appliances
Letocha, René ; Mádr, Tomáš (referee) ; Kolka, Zdeněk (advisor)
The work deals with communication options, the power line and particularly the use of this technology in home automation to control heating and reduction in standby mode for selected domestic appliances. The issue is outlined in detail first and then examined in detail. The publication outlines a possible variant of such a device that can detect movement in the house and on the basis of such information to adjust the energy profile. The device is from its base designed to minimize the consumption of heat and electricity.
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Sleep quality assessment
Dokoupilová, Daniela ; Kozumplík, Jiří (referee) ; Ronzhina, Marina (advisor)
The topic of this bachelor thesis is quality sleep assessment using signals acquired from Apple Watch. From measured signals – heart rate and motion, were extracted parameters for sleep classification using statistical testing. These parameters were later used for training the support vector machine model. The model was first trained to classify Wake and Sleep, then also to classify Wake, REM and NREM stages. The accuracy of Wake/Sleep classification was about 80 %. The accuracy of Wake/REM/NREM classification exceeded 58 %. Finally, sleep quality parameters were calculated and compared to the data rated by a sleep expert. The outcome for Wake/Sleep classification was close to the expert evaluation. The model for Wake/REM/NREM classification was less accurate and differed mainly in parameters concerning Wake stage.
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Lůžkový nábytek pro děti
Štěpánková, Lucie
The diploma thesis deals with the design of children's bed furniture, specifically a baby bed. The work is divided into two parts - theoretical and practical. The theoretical part deals with ergonomics, typology, materials used and, last but not least, safety requirements and standards when designing children's furniture. The second, practical, part focuses on the overall process of designing and manufacturing a baby bed regarding to it‘s functionality, safety and design. In this part is documented the overall process from the initial sketches and visualizations to the selected variant, its drawing documentation and the production process. The output of the work is a functional prototype in M 1:1 together with the calculation of material costs and correction of the technical solution.
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Informovanost žáků SOŠ o rovnováze zdravého životního stylu
Kchýrová, Natálie
The Bachelor thesis "Awareness of healthy lifestyle balance for secondary school pupils" focuses on healthy lifestyle and its important components, containing a theoretical and practical part. In the theoretical part, the concept of a healthy lifestyle is defined and the essential aspects important to maintaining a healthy lifestyle are clarified. The practical part includes a questionnaire investigation which was carried out at the SSC to establish pupils' awareness and adherence to healthy lifestyles. A recommendation for teaching experience is given at the end of the work.
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