New real-time heartbeat detection method using the angle of a single-lead electrocardiogram

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiology

Background:

• Accurate real-time heartbeat detection is crucial for continuous cardiac monitoring.
• Existing algorithms may be complex or require multi-lead electrocardiogram (ECG) data.
• Developing efficient, single-lead ECG analysis methods is essential for portable healthcare devices.

Purpose of the Study:

• To introduce a new, real-time heartbeat detection algorithm based on the geometric angle of single-lead ECG signals.
• To evaluate the algorithm's performance against established databases and compare it with existing literature methods.
• To demonstrate the algorithm's suitability for real-time application in healthcare and medical devices.

Main Methods:

• A novel index, the geometric angle between consecutive ECG signal samples, was used to represent signal slope.
• The algorithm involves three main steps: high-frequency noise elimination, angle calculation, and adaptive thresholding for R-wave detection.
• Performance was validated using the MIT-BIH arrhythmia, QT, European ST-T, and T-wave alternans databases, along with synthesized ECG signals.

Main Results:

• The algorithm achieved high accuracy: 99.95% sensitivity and 99.95% positive predictivity.
• A low fail detection rate of 0.10% was recorded across the evaluated databases.
• The method demonstrated comparable or superior performance to existing literature techniques.

Conclusions:

• The proposed geometric angle-based algorithm provides a simple, fast, and effective method for real-time heartbeat detection using single-lead ECG.
• No post-processing is required, enhancing its efficiency for practical implementation.
• The algorithm is well-suited for integration into various real-time healthcare and medical monitoring devices.