Circuit Implementation of Respiratory Information Extracted from Electrocardiograms

Circuit Implementation of Respiratory Information Extracted from Electrocardiograms

Shi Cheng, JinBao Zhang, Zhan Gao, Jiehua Wang
Copyright: © 2022 |Pages: 12
DOI: 10.4018/JDM.314211
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Abstract

Breathing is an important physiological process in the human body. The wavelet transform method can extract respiratory information from electrocardiogram (ECG) data; thus, the authors designed an integrated circuit of ECG-derived respiration (EDR). They propose a discrete wavelet transform (DWT) EDR algorithm based on an analysis of the heartbeat frequency and respiration. They verified the algorithm in both the time domain and the frequency domain using Matlab. Next, the DWT EDR digital circuit was designed using the QUARTUS program. Finally, they used a field programmable gate array (FPGA) for downloading and simulation, and they verified the designed circuits using a logic analyzer, where they compared the waveform of the data obtained from the EDR circuit with the waveform obtained after processing the wavelet transform EDR in Matlab. The experimental results showed that the circuit can allow the extraction of respiratory information from ECG data.
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2. Wavelet Transform Method And Its Verification

The wavelet transform of ECG-derived respiration (EDR) is based mainly on the respiration and heartbeat frequencies in different bands (Zhuang et al., 2021; Katam et al., 2018; Yu et al., 2007). The wavelet transform principle employed by EDR aims to filter signals outside the scope of the respiratory frequency to derive breathing information from ECG signals. The original signals are discrete so the discrete wavelet transform (DWT) is used.

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