Extracting ECG Signals: A Singular Value and Wavelet Approach

Accurate extraction of electrocardiogram (ECG) signals is essential for diagnosing cardiovascular conditions, yet conventional methods often face challenges due to noise and other artefacts. This research study proposes a hybrid approach utilizing Singular Value Selection (SVS) and Wavelet Transform (WT) to enhance ECG signal clarity. The SVS technique effectively filters out noise, while the WT enables multi-resolution analysis, preserving critical diagnostic features within the signal. Experimental evaluations indicate that this method achieves higher accuracy and efficiency compared to traditional techniques, making it a promising candidate for integration into real-time ECG monitoring systems. This dual-method approach not only improves signal quality but also aids in more precise decision-making in clinical environments.