O.V.Melnik - Dr.Sc. (Eng.), Professor, Department of Information-Measurement and Biomedical Engineering, Ryazan State Radio Engineering University. E-mail: omela111@yandex.ru

When evaluating the functional status of the human during daily activities on the basis of electrocardiosignal processing one of the most important tasks is to identify the earliest signs of myocardial abnormalities that may make its debut against the background of increased physical or psycho-emotional stress, such as coronary heart disease. The method of formation of informative parameters of the ST-segment of electrocardiosignal form based on calculation of the spectral coefficients in the basis of Walsh functions is described. A set of decision rules for types of ST-segment form classification on the basis of given informative parameters is formulated. An algorithm for detecting signs of coronary heart disease is developed, which makes it possible, in contrast to the known analogues, implement detailed classification of different types of ischemic and non-specific changes in electrocardiosignal ST-segment and can be implemented with the use of handheld devices and software applications making assessment of the human functional status in real-time time.

 

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