AP23485820 "Improving the signal quality and prediction accuracy of a portable cardiac analyzer in the diagnosis of heart diseases"

Relevance

The system will improve the accuracy and reliability of diagnosis of cardiovascular diseases. The new algorithms will improve the quality of ECG signal processing, reducing interference levels and improving the detection of cardiac pathologies, which will allow detecting disorders at an earlier stage and ensuring accurate diagnosis. It is expected that the diagnostic accuracy will increase to 95%, which will reduce the need for repeated studies. Process automation will save medical workers time and speed up the diagnostic process, improving the overall efficiency of the medical services provided.

Purpose

The aim of the work is to improve the accuracy and reliability of the diagnosis of cardiovascular diseases by developing new methods for processing and analyzing electrocardiographic (ECG) signals.

Expected and achieved results

The results obtained include the development and testing of new algorithms for processing ECG signals to increase resistance to interference, automatically identify informative segments, and accurately segment key signal components. The novelty of the work lies in the use of neural networks and adaptive filtering methods for the accurate diagnosis of cardiovascular diseases, which significantly improves the quality of ECG analysis and increases the reliability of diagnosis.

Research team members with their identifiers (Scopus Author ID, Researcher ID, ORCID, if available) and links to relevant profiles