QRS Complex Detection via Dual-Slope ECG Signal Processing
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Solution Overview
Problem
Traditional methods for detecting the QRS complex in electrocardiogram (ECG) signals face challenges due to full-band interference and large amplitude T waves, leading to false detections and high computational loads, making real-time analysis difficult.
Innovation Solution
An electrocardiogram detection device employing a dual-slope method in conjunction with a power frequency notch filter and a second-order infinite impulse response (IIR) high-pass filter to preprocess ECG signals, followed by a dual-slope processing technique to enhance the visibility of the R wave peak, thereby improving detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional filtering methods (low-pass, high-pass, band-pass) are used to remove noise, then noise reduction is achieved, but full-band interference signals cannot be completely filtered out and false detections occur due to large amplitude T waves
Solution Approach 1:
The patent changes the processing parameter from traditional filtering to dual-slope processing method. This method transforms the ECG signal by calculating the difference between adjacent sampling points, effectively suppressing full-band interference signals including power frequency noise and EMG signals while preserving the QRS complex morphology for accurate detection
Solution Approach 2:
The patent segments the ECG signal processing into distinct stages: preprocessing with dual-slope method to suppress noise, followed by separate detection of R wave peaks and T wave peaks. This segmentation allows independent optimization of detection algorithms for different wave components, improving overall detection reliability
2Measurement precision
If neural network algorithm, template matching algorithm, TROIKA algorithm, hidden Markov model and Hilbert-Huang transform are used, then detection accuracy may be improved, but the entire ECG signals need to be processed at the same time and the calculation-load is huge making real-time analysis difficult
Solution Approach 1:
The patent extracts only the essential features needed for QRS complex detection by using dual-slope processing to enhance R wave prominence and implementing separate peak detection algorithms. This extraction approach avoids the computational burden of processing entire ECG signals with complex algorithms like neural networks or Hilbert-Huang transform, enabling real-time analysis while maintaining detection accuracy
Solution Approach 2:
The patent performs preliminary signal processing using the dual-slope method before detection, which pre-enhances the R wave peaks and suppresses noise. This preliminary action simplifies subsequent detection steps and reduces computational load during real-time processing, avoiding the need for heavy post-processing algorithms
Data Source
AI summary
A QRS complex detection method is provided. The method includes collecting an ECG signal and filtering the ECG signal by using at least one preset filter. The filtered ECG signal is processed using a dual-slope method. Once R wave peak is detected from the processed ECG signal, a position of a QRS complex is outputted based on the R wave peak.