Optical fiber sensing-based respiratory signals motion artifacts suppression using empirical mode decomposition

Tong Zhang; Yuanli Wang; Jing Zhan; Kewei Chen; Ning Jiang

doi:10.1117/12.3036835

13 July 2024 Optical fiber sensing-based respiratory signals motion artifacts suppression using empirical mode decomposition

Tong Zhang, Yuanli Wang, Jing Zhan, Kewei Chen, Ning Jiang

Author Affiliations +

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 132081E (2024) https://doi.org/10.1117/12.3036835
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

The monitoring of respiratory holds significant importance in clinical applications, encompassing parameters such as respiratory rate, tidal volume, and maximal airflow velocity. Respiratory monitoring is categorized into contact and noncontact methods. Non-contact respiratory monitoring, owing to its minimal interference with the user's breathing and comfort, has garnered considerable attention in research. However, motion artifacts significantly affect respiratory monitoring, leading to a substantial reduction in the accuracy of calculation of tidal volume, respiratory rate and so on. Hence, the suppression of motion artifacts is a crucial aspect of non-contact respiratory monitoring. This paper reports a method for suppressing motion artifacts in respiratory signals obtained from fiber optic sensing mattress. The proposed method uses empirical mode decomposition (EMD) to suppress motion artifacts by decomposing and reconstructing the signals. The method demonstrates effective suppression of motion artifacts, resulting in an improvement of 0.015 in the Pearson correlation coefficient between the respiratory signal after suppressing motion artifacts and the standard respiratory signal obtained from airflow sensors.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tong Zhang, Yuanli Wang, Jing Zhan, Kewei Chen, and Ning Jiang "Optical fiber sensing-based respiratory signals motion artifacts suppression using empirical mode decomposition", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 132081E (13 July 2024); https://doi.org/10.1117/12.3036835

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KEYWORDS

Modal decomposition

Optical fibers

Fiber optics

Background noise

Correlation coefficients

Fiber optics sensors

Sensors

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