In recent years, the use of remote patient monitoring technologies has extended the diagnosis and surveillance of chronic diseases beyond hospitals. In chronic respiratory diseases, oscillometry measurement has been recognized as a portable approach that can be used in non-laboratory, unsupervised environments to measure lung function serially. In this study, the susceptibility of oscillometry output signals to motion artifact is investigated. Through a comprehensive experimental measurement, it is found that the coefficient of variation of the oscillometer output signals increases 4.51 times in the presence of motion artifact. The maximum deviation in the oscillometer signals caused by motion artifact was observed in the reactance parameter at a low frequency of 5 Hz. Results indicate that a signal processing technique to address motion artifacts can enhance the quality of data obtained from unsupervised oscillometry testing. This will help further establish oscillometry as an accurate and reliable remote outpatient lung function monitoring modality.
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| http://dx.doi.org/10.1109/EMBC53108.2024.10782180 | DOI Listing |
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