[Specific features of QRS-complex identification algorithms for real-time ECG systems].

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiology

Background:

• Accurate identification of QRS complexes is crucial for real-time electrocardiogram (ECG) analysis.
• Existing QRS detection algorithms vary in performance and suitability for computer-aided systems.
• Specific requirements for real-time ECG systems necessitate optimized QRS detection methods.

Purpose of the Study:

• To review and classify existing QRS detection algorithms.
• To identify the most suitable QRS detection methods for real-time computer-aided ECG systems.
• To propose a novel algorithm for efficient QRS complex identification.

Main Methods:

• Literature review and classification of QRS detection algorithms.
• Analysis of requirements for real-time ECG signal processing.
• Development and implementation of a frequency-time based QRS detection algorithm.
• Integration of the algorithm into a laboratory computerized ECG system.

Main Results:

• A structured classification of QRS detection algorithms is presented.
• A new frequency-time detection algorithm effectively isolates QRS complexes from real-time ECG data.
• The proposed algorithm facilitates efficient digital signal processing using optimized libraries.
• Successful integration of the algorithm into an existing ECG system.

Conclusions:

• The proposed frequency-time algorithm offers an effective solution for real-time QRS detection in ECG systems.
• This method enhances the accuracy and efficiency of digital signal processing for cardiac monitoring.
• The algorithm's integration demonstrates its practical applicability in clinical settings.