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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
The monograph deals with the issues of improving the quality of electrocardiographic systems through optimization of methods of digital processing and intelligent analysis of electrocardiographic signals. The paper proposes informative criteria and methods for evaluating the quality of signal filtering algorithms, develops an effective multistage algorithm for noise suppression and forms a general approach to the selection of significant informative features for the diagnosis of myocardial infarction using electrocardiographic signal recordings in one lead.The solutions proposed in the monograph open up opportunities for building mobile analyzers of electrocardio-signals as part of medical info-communication systems. Such analyzers are able to perform automated express diagnostics of cardiovascular system diseases by means of self-learning intelligent algorithms. The proposed methods of digital filtering simplify the structure with the expansion of the dynamic range of recording electrocardiographic equipment.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
The monograph deals with the issues of improving the quality of electrocardiographic systems through optimization of methods of digital processing and intelligent analysis of electrocardiographic signals. The paper proposes informative criteria and methods for evaluating the quality of signal filtering algorithms, develops an effective multistage algorithm for noise suppression and forms a general approach to the selection of significant informative features for the diagnosis of myocardial infarction using electrocardiographic signal recordings in one lead.The solutions proposed in the monograph open up opportunities for building mobile analyzers of electrocardio-signals as part of medical info-communication systems. Such analyzers are able to perform automated express diagnostics of cardiovascular system diseases by means of self-learning intelligent algorithms. The proposed methods of digital filtering simplify the structure with the expansion of the dynamic range of recording electrocardiographic equipment.