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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.
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Classification of free living data sensed with Faros
Šalamoun, Jan ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
Topic of this master thesis is classification of free living data sensed with Faros. Faros is small compatible device which measure ECG and 3-axes accelerometric data. The first part of master thesis is find out how automatically measure free living activities by accelerometer and ECG. In next part was measured data of 8 activities from 10 probands. Automatic algorithms are made for this data in Matlab. This algorithms were used for this datasets and compare with manually recorded references. In the end of master thesis data were statistically evaluated.
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Classification of free living data
Rychtárik, Martin ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
The topic of this bachelor thesis is classification of free living data, captured by the accelerometer sensor of a smart phone. The first part of the thesis deals with the possibilities of recording daily activity using accelerometer and subsequent classification by neural network. In the next section, the data of eight different daily activities were recorded on ten people. An algorithm containing a neural network was created for the data in the MATLAB programming environment to automatically identify the activities. In the last part of the work the algorithm classification was compared with manually recorded reference and the results were statistically evaluated.
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Jsou osobnostní rysy hraboše polního provázány s denním rytmem pohybové aktivity?
KUBÍKOVÁ, Pavlína
In this study, the relationship between personality traits and daily activity of Common voles (Microtus arvalis) was investigated. Thirty four voles were captured for tests from the wild and kept separately under stable light (L:D, 12:12) and ambient temperature (19 ? 1 oC) laboratory conditions. Voles were subjected to Open Field (OF) tests to determine their personality traits on locomotor activity and shy-bold gradients. They were then monitored in the PhenoTyper boxes, where their activity was recorded for seven days. In this thesis, it was found that more locomotor active and bold individuals in the OF test are also more active in the PhenoTyper box, are more prone to periodicity and regular ultradian rhythms, and have more activity in the dark. Shy individuals are often immobile (most often in the dark), which weakens the periodicity of their ultradian rhythms. Thus, greater boldness in the common vole leads to greater nocturnal activity, and shyness rather to greater nocturnal immobility. The personality traits were associated with daily activity, periodicity, and ultradian rhythms.
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The influence of epilepsy on the activities of daily life for children
Konečná, Eliška ; Nikodemová, Hana (advisor) ; Tomová, Šárka (referee)
The bachelor's thesis on the topic "Influence of epilepsy on the activities of children's daily life" is focused on the daily activities of children with epilepsy. Epilepsy as a disease is a relatively common diagnosis, which to some extent affects the lives not only of patients but also of their immediate surroundings. The aim of this bachelor thesis was to find out and map how children in the younger school age range to adolescents with epilepsy are limited in everyday activities. In the theoretical part of the work, attention is paid to existing knowledge about the problem of the disease, its causes, symptoms, diagnosis and treatment. Furthermore, the quality of life, where this concept is defined and the definition of the concept of daily activity. To obtain data, a questionnaire of our own creation was created, focusing on daily activities. The questionnaire contains a total of 26 items, to which the respondents answered individual questions, which were then analyzed and evaluated. The empirical part contains goals, working hypotheses, methodology and organization of the survey, characteristics and description of the examined sample. There is a presentation of the results of a questionnaire survey, which was attended by 44 respondents, the survey itself took place with the prior agreement of the legal...
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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.
|
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Classification of free living data
Rychtárik, Martin ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
The topic of this bachelor thesis is classification of free living data, captured by the accelerometer sensor of a smart phone. The first part of the thesis deals with the possibilities of recording daily activity using accelerometer and subsequent classification by neural network. In the next section, the data of eight different daily activities were recorded on ten people. An algorithm containing a neural network was created for the data in the MATLAB programming environment to automatically identify the activities. In the last part of the work the algorithm classification was compared with manually recorded reference and the results were statistically evaluated.
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Classification of free living data sensed with Faros
Šalamoun, Jan ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
Topic of this master thesis is classification of free living data sensed with Faros. Faros is small compatible device which measure ECG and 3-axes accelerometric data. The first part of master thesis is find out how automatically measure free living activities by accelerometer and ECG. In next part was measured data of 8 activities from 10 probands. Automatic algorithms are made for this data in Matlab. This algorithms were used for this datasets and compare with manually recorded references. In the end of master thesis data were statistically evaluated.
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