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Multiwavelet-based ECG compressed sensing
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DOI：10.1016/j.measurement.2023.113393.png)
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摘要
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This paper presents a novel Multiwavelet-based hybrid method for compressed sensing (CS) and reconstruction of ECG signals. The proposed method is patient-agnostic and does not require any prior patient-specific information. The proposed method removes low-frequency components by using multi-scaling wavelet functions, which sparsify the ECG signals in the multi-wavelet domain. A novel way of CS acquisition is used to acquire the high-frequency component of the ECG signal. The compressed sensed signal acquisition is performed based on sample difference thresholding. This approach ensures that a significant portion of the ECG signal will be acquired, without a need for a QRS complex or an R peak detector. The main compression is achieved by CS and linear and nonlinear quantization. Arithmetic encoding is used to improve compression further. The results show good reconstruction quality while maintaining a high compression ratio. The proposed method was evaluated for different multi-wavelet functions.
Keyword:
Compressed sensing
Multiwavelets
ECG compression
期刊
IF:
5.6
论文数:
2.0W
被引数:
5.4W
机构
引用论文
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