[QRS detection based on difference method].

Area of Science:

• Cardiovascular signal processing
• Biomedical engineering
• Medical instrumentation

Context:

• Accurate detection of the QRS complex in electrocardiograms (ECG) is crucial for diagnosing cardiac arrhythmias.
• Traditional methods often suffer from low accuracy due to interference from other ECG waves (P, T) and noise.
• Complex algorithms like wavelet methods can lead to high computational demands.

Purpose:

• To propose a novel difference method for QRS complex detection in ECG signals.
• To improve detection accuracy and reduce computational complexity compared to existing methods.
• To address the limitations of traditional and wavelet-based QRS detection techniques.

Summary:

• A difference method is presented that utilizes the ECG's difference function to effectively minimize interference from P waves, T waves, and other noise.
• This approach overcomes the accuracy limitations of conventional methods and the computational burden of wavelet algorithms.
• Experimental validation using the MIT-BIH arrhythmia database demonstrates robust performance across various challenging ECG morphologies.

Impact:

• Achieves a detection accuracy rate exceeding 99% for QRS complex identification.
• Shows excellent adaptability to diverse and ill-conditioned ECG waveforms.
• Successfully integrated into a clinical '12 lead ECG system', showcasing practical applicability and improved diagnostic capabilities.