Abstract
In the present work, a wavelet transform-based filter bank architecture suitable for ECG signal denoising is proposed. Firstly, wavelet transform functions are used to filter the signals in Matlab R2013b, and then, the resulting signal is converted into 16-bit binary data. This data is used further as an input of QRS detection block. Modified architecture contains only three low-pass filters and a high-pass filter, which is less compared to previously designed architectures. One of the key advantages of the proposed architecture is that no multiplexer and multiplier circuits are required for the further processing. The proposed architecture consumes less area and is relatively fast compared to previously designed architectures.
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Kumar, A., Komaragiri, R., Kumar, M. (2018). A Wavelet Transform-Based Filter Bank Architecture for ECG Signal Denoising. In: Sa, P., Bakshi, S., Hatzilygeroudis, I., Sahoo, M. (eds) Recent Findings in Intelligent Computing Techniques . Advances in Intelligent Systems and Computing, vol 708. Springer, Singapore. https://doi.org/10.1007/978-981-10-8636-6_26
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DOI: https://doi.org/10.1007/978-981-10-8636-6_26
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