A mathematical algorithm for ECG signal denoising using window analysis

• Published in: Biomedical papers of the Medical Faculty of the University Palacký, Olomouc, Czechoslovakia Vol. 151; no. 1; pp. 73 - 78
• Main Authors: SadAbadi, Hamid, Ghasemi, Masood, Ghaffari, Ali
• Format: Journal Article
• Language: English
• Published: Czech Republic 01.06.2007
• Subjects: Algorithms; Electrocardiography; Humans; Signal Processing, Computer-Assisted
• ISSN: 1213-8118; 1804-7521
• DOI: 10.5507/bp.2007.013

The presence of parasite interference signals could cause serious problems in the registration of ECG signals and many works have been done to suppress electromyogram (EMG) artifacts noises and disturbances from electrocardiogram (ECG). Recently, new developed techniques based on global and local transforms have become popular such as wavelet shrinkage approaches (1995) and time-frequency dependent threshold (1998). Moreover, other techniques such as artificial neural networks (2003), energy thresholding and Gaussian kernels (2006) are used to improve previous works. This review summarizes windowed techniques of the concerned issue. We conducted a mathematical method based on two sets of information, which are dominant scale of QRS complexes and their domain. The task is proposed by using a varying-length window that is moving over the whole signals. Both the high frequency (noise) and low frequency (base-line wandering) removal tasks are evaluated for manually corrupted ECG signals and are validated for actual recorded ECG signals. Although, the simplicity of the method, fast implementation, and preservation of characteristics of ECG waves represent it as a suitable algorithm, there may be some difficulties due to pre-stage detection of QRS complexes and specification of algorithm's parameters for varying morphology cases.