Focusing on the enhancement of electrocardiographic systems, this monograph presents innovative methods for digital processing and intelligent analysis of ECG signals. It introduces criteria for assessing signal filtering algorithms and develops a multistage noise suppression algorithm. The work emphasizes selecting key features for diagnosing myocardial infarction using single-lead recordings. Additionally, it explores the potential for mobile ECG analyzers within medical communication systems, capable of automated diagnostics through self-learning algorithms, while improving filtering methods and equipment dynamics.
