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Classification of ECG by artificial neural networks
Loviška, David ; Vítek, Martin (referee) ; Hrubeš, Jan (advisor)
The aim of project with name Classification ECG by artificial neural networks is simplify and speed up working a doctor. That reaches created program that the is capable simply and almost at once classify EKG signal using artificial neuronal nets. Created program will give to the doctor basic information about used electrocardiogram, as are time period and amplitude signal in single surveyed sections. Subsequently will program warn doctor about abnormalities from normal. Part of program is also graphic window with painted signal and on him in color points and partitions marked by program behind special. In next phase program alone classifies gained data and designating without doctor diagnose that doctor can evaluate and in case agreeable it sign and place for true diagnose patient. This program is also fit for data reading from bigger of the number of hours as far as days. It is concerned primarily Holter ECG monitoring.
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Classification of ECG by artificial neural networks
Loviška, David ; Vítek, Martin (referee) ; Hrubeš, Jan (advisor)
The aim of project with name Classification ECG by artificial neural networks is simplify and speed up working a doctor. That reaches created program that the is capable simply and almost at once classify EKG signal using artificial neuronal nets. Created program will give to the doctor basic information about used electrocardiogram, as are time period and amplitude signal in single surveyed sections. Subsequently will program warn doctor about abnormalities from normal. Part of program is also graphic window with painted signal and on him in color points and partitions marked by program behind special. In next phase program alone classifies gained data and designating without doctor diagnose that doctor can evaluate and in case agreeable it sign and place for true diagnose patient. This program is also fit for data reading from bigger of the number of hours as far as days. It is concerned primarily Holter ECG monitoring.
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Pectoris angina as a symptom of acute myocardial infarction in urgent care
ŠVORC, Jaroslav
This dissertation deals with the topic of stenocardia as the symptom of an acute myocardial infarction in prehospital emergency care. The goal of my work is to map the time lag from the first symptoms of an acute myocardial infarction to giving an urgent non-hospital first aid. The introductory part summarizes basic terms of anatomy and physiology of the considered system. The theoretical part of my work includes an ischemic disease and the most frequent risk factors which patients bear. The theoretical part is mainly dedicated to an acute myocardial infarction, i.e. its origin, symptoms, diagnostics, and treatment. The final part deals with issues concerning education of a patient from a medical rescuer's point of view. My work also involves a research part including the file of patients with diagnosed acute myocardial infarction. I nave got the data using retrospective analysis of the outgoing cards of the patients of the Medical Rescue Service Team of Ústí Region, with diagnoses of an acute myocardial infarction. The data has been processed into a table from which other graphs and tables in research part result. It observes the time lag from the first symptoms of an acute myocardial infarction to calling for help and giving an urgent non-hospital first aid. I also follow the main symptoms of an acute myocardial infarction (pain, propagation of pain). The research part results into conclusion, that the majority of patients calls for Medical Rescue Service Team within 3 hours after appearing the first symptoms of stenocardia. The patients mainly call for help within 1 hour after the first problems appear in this 3 hours interval.
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