R-wave Detection in ECG Signals Using Wavelet Singular Point Monitoring Method

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Resource Overview

An example of detecting R-waves in ECG signals using wavelet singularity detection, which can also be applied to singularity monitoring in other signals. The implementation involves wavelet transform decomposition and modulus maximum analysis for precise feature extraction.

Detailed Documentation

This article provides an example of using wavelet singularity detection method to monitor R-waves in ECG signals. This monitoring approach can also be extended to singularity detection in other signal types. Through wavelet singularity detection, we can effectively identify and analyze R-wave peaks in ECG signals by implementing algorithms that detect modulus maxima across different wavelet decomposition scales. When applied to other signals, this method helps researchers better understand and explore singularity characteristics in various datasets. The core implementation typically involves selecting appropriate wavelet bases (like 'db4' or 'sym8'), calculating wavelet coefficients, and applying threshold-based peak detection algorithms. Therefore, wavelet singularity detection method shows broad application prospects in signal processing领域, particularly for biomedical signal analysis and fault detection in mechanical systems.

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