Abstract
Applying signal processing to bio-signal record such as electrocardiogram or ECG signals provide vital insights to the details in diagnosis. The diagnosis will be exact when the extracted information about the ECG is accurate. However, these records usually gets corrupted/contaminated with several artifacts and power-line interferences (PLI) thereby affects the quality of diagnosis. Power-line interferences occurs in the range close to 50 Hz/60 Hz. The challenge is to remove the interferences without altering the original characteristics of ECG signal. Since the ECG signals frequency range is close to PLI, several articles discuss PLI removal methods which are mathematically complex and computationally intense. The present paper proposes a novel PLI removal method that uses a simple optimization method involving a circular convolution based \({\ell _2}\)-norm regularization. The solution is obtained in closed form and hence computationally simple and fast. The effectiveness of the proposed method is evaluated using output signal-to-noise-ratio (SNR) measure, and is found to be state-of-the-art.
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Sujadevi, V.G., Soman, K.P., Kumar, S.S., Mohan, N. (2018). A Novel Cyclic Convolution Based Regularization Method for Power-Line Interference Removal in ECG Signal. In: Thampi, S., Krishnan, S., Corchado Rodriguez, J., Das, S., Wozniak, M., Al-Jumeily, D. (eds) Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2017. Advances in Intelligent Systems and Computing, vol 678. Springer, Cham. https://doi.org/10.1007/978-3-319-67934-1_11
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