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Visualization and analysis of retinal pulsatile phenomena
Plavcová, Daniela ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Retinal blood flow can be a reflection of the state of the vascular system, but it can also indicate changes in intracranial pressure. For that reason, video sequences are taken from the retina, which can be processed to examine this area. This work deals with the analysis and visualization of pulsations on the retina, representing the change in light attenuation during one hearth cycle, and the search for suitable parameters describing connections and differences between data, whether in the form of signals, images or video sequences.
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Photoplethysmography using a smartphone
Dräxler, Vladislav ; Němcová, Andrea (referee) ; Janoušek, Oto (advisor)
This work is focused on the PPG technology using a smartphone, from the acquisition of the photoplethysmographic curve, through the preprocessing of the PPG signal, the calculation of the parameters to the quality assessment. The practical part contains a measurement protocol under different experimental conditions, an algorithm for obtaining a photoplethysmographic curve from video recordings obtained by measurement, and further deals with determining various parameters and evaluating the quality of the obtained PPG signal. The output of the work is an optimal acquisition protocol for scanning the PPG curve.
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Advanced sleep quality estimation
Benáček, Petr ; Ředina, Richard (referee) ; Filipenská, Marina (advisor)
This thesis deals with the assessment of sleep quality using modern deep learning methods. The thesis describes metrics for automatic classification of sleep stages. A selected database of sleep data is discussed. Due to the low number of data in the wakefulness phase, different methods of data augmentation are described and implemented. Models based on 1D convolutional networks are the basis for the classification. As a result, models for binary classification and classification of 3 and 4 sleep phases are prepared. Finally, sleep quality metrics are calculated using these models and the results are compared with the literature.
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HRV analysis based on PPG signal
Martinů, Žaneta ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The thesis deals with the detection of systolic and diastolic peaks of pulse waves in a photoplethysmographic database. The detectors are implemented in MATLAB. The following part of the thesis uses the signal delineation of the photoplethysmographic signal to determine pulse rate variability. The final part of the thesis evaluates the use of pulse rate variability and compares it to the heart rate variability.
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Advanced methods for sleep quality assessment
Doležalová, Anna ; Králík, Martin (referee) ; Ronzhina, Marina (advisor)
This diploma thesis is focused on advanced sleep assessment using deep learning. Metrics for sleep assessment and their use are described here. There are hearth rate and accelerometer data from Apple Watch used for classification. The basis for the classification was a model composed of 1D convolution networks in combination with recurrent neural network. LSTM and GRU were used as recurrent networks. Models were taught to classify into two, three and five phases. At last the resulting methods are compared.
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Ppg Signal Quality Assessment And Heart Rate Estimation
Vargová, Enikö
The presented paper describes an algorithm for signal quality assessment based on clusteranalysis and also an algorithm for heart rate estimation from PPG signals. This work includesa database which comprises 48 PPG signals collected by a smartphone and 48 ECG signals recordedby an ECG recorder. The accuracy of the quality assessment is 97,5 % on the training set and87,5 % on the test set. The average deviation of the estimated heart rate is 1,39889 bpm.
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PPG signal quality assessment and heart rate estimation
Vargová, Enikö ; Vítek, Martin (referee) ; Němcová, Andrea (advisor)
This work deals with photoplethysmographic (PPG) signals, their processing, quality assessment, estimation of heart rate from PPG signals and the ability to record biological signals with smartphones. The aim of this work is to record PPG signals using a smartphone and reference ECG signals using an ECG recorder. The work also includes the design of two algorithms, one for signal quality assessment and the other for heart rate estimation from PPG signals.
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Analysis of pulse wave propagation in aorta
Tichoň, Dušan ; Klas, Roman (referee) ; Burša, Jiří (advisor)
The aim of this diploma thesis is to assess the applicability of pulse wave propagation monitoring in the cardiovascular system in the field of prediction and early diagnosis of abdominal aortic aneurysm (AAA). The very first part is focused on description of heart and blood vessels with its pathological changes in presence of aneurysm. For this reason, current methods of monitoring and surgical treating of AAA were mentioned. Due to their difficult clinical use widely in the population, new methods based on pulse wave monitoring were presented. Using an analytical approach we estimated the difference in the arrival of the pulse wave at measurable locations between healthy and pathological aorta in the order of miliseconds. By experimental monitoring using photoplethysmographic sensors, we observed significant changes of pulse wave velocity with respect to the mechanical properties of the artery wall (mainly associated with age), which we tried to implement by hyperelastic material models used in computational simulations of pulse wave proagation on simplified geometries by fluid structure interaction method. These analyzes should verify applicability of FSI simulations in further development of diagnostic methods of AAA.
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