Abstract
Cardiac Output (CO) is a significant hemodynamic index for the diagnosis and treatment of cardiovascular diseases. Impedance cardiography (ICG) is one of the non-invasive methods widely investigated for its simplicity, cost-effectiveness and ability to measure cardiac output continuously. However, measured ICG signals are contaminated by the respiratory artefact leading to difficulties in determining characteristic points in the signal waveform, thereby lowering the accuracy of measurement results. Thus, suppressing this artefact plays an important role in ICG signal processing. This paper aims to propose a method of noise filtering to improve the quality of the signal as well as a model to evaluate the noise filtering efficiency of the method. The proposed algorithm showed promising results with the output SNR values of 21.99 ± 3.20 dB, 20.40 ± 2.88 dB, 15.57 ± 4.79 dB for normal breathing, forced breathing, and rapid breathing respectively. The root mean square percentage error (RMSPE) values of the output signals processed by the proposed algorithm compared to the standard ICG signal source for normal breathing, forced breathing, and rapid breathing are 24.13 ± 22.66%, 18.09 ± 12.98%, 32.13 ± 20.40% respectively. The quality-enhanced ICG signal could be effective tool for assisting doctors to detect cardiac abnormalities via evaluating the morphology of ICG signal waveforms as well as improving accuracy in calculating beat-to-beat and averaged hemodynamic parameters.
Published Version
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