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РН
SpaceX
Роскосмос
NASA
СпутникиРНSpaceXРоскосмосNASAPublication date: 30 September 2026
Source: Advanced Engineering Forum Vol. 60
Author(s): Pallavee Jaiswal, Saurabh Mitra
Electrocardiogram (ECG) signal denoising is a crucial step in medical signal processing to enhance the diagnostic accuracy and reliability of cardiovascular disease detection. The accurate extraction of ECG signals is crucial in clinical applications, and the choice of filtering techniques plays a pivotal role in enhancing the diagnostic accuracy. Infinite Impulse Response (IIR) filters, known for their computational efficiency, are widely used for ECG signal processing. However, when implemented in resource-constrained environments, the finite word length effects due to coefficient quantization become a critical consideration. This research paper presents a comprehensive study that compares number of coefficient quantization techniques in IIR filter design for ECG signal denoising, with a specific focus on minimizing finite word length effects. In pursuit of this purpose, ECG data is retrieved from the MIT-BIH Arrhythmia Database Directory. Using Signal-to-Noise Ratio (SNR) measures, the study assesses how well these filters work.
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