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Digital processing and intelligent analysis of ECG

About Digital processing and intelligent analysis of ECG

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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  • Language:
  • English
  • ISBN:
  • 9786206235095
  • Binding:
  • Paperback
  • Pages:
  • 136
  • Published:
  • July 15, 2023
  • Dimensions:
  • 150x9x220 mm.
  • Weight:
  • 221 g.
Delivery: 1-2 weeks
Expected delivery: April 30, 2025

Description of Digital processing and intelligent analysis of ECG

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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