A Comparative Study of Accuracy in Major Adaptive Filters for Motion Artefact Removal in Sleep Apnea Tests
Affiliation
University of Chester; Passion for Life HealthcarePublication Date
2023-12-05
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Sleep apnoea is probably the most common respiratory disorder, respiration and blood oxygen saturation (SpO2) are major concerns in sleep apnoea and are also the two main parameters checked by Polysomnography (PSG, the gold standard for diagnosing sleep apnoea). In this study, we used a simple, non-invasive monitoring system based on photoplethysmography (PPG) to continuously monitor SpO2 and heart rate (HR) for individuals at home. Various breathing experiments were conducted to investigate the relationship between SpO2, HR, and apnoea under different conditions, where two techniques (empirical formula and customized formula) for calculating SpO2 and two methods (resting HR and instantaneous HR) for assessing HR were compared. Various adaptive filters were implemented to compare the effectiveness in removing motion artefacts (MA) during the tests. This study fills the gap in the literature by comparing the performance of different adaptive filters on estimating SpO2 and HR during apnoea. The results showed that up-down finger motion introduced more MA than left-right motion, and the errors in SpO2 estimation were increased as the frequency of movement was increased; due to the low sampling frequency features of these tests, the insertion of adaptive filter increased the noise in the data instead of eliminating the MA for SpO2 estimation; the normal least mean squares (NLMS) filter is more effective in removing MA in HR estimation than other filters.Citation
Chen, Y., Zheng, Y., Johnson, S. Wiffen, R., & Yang, B. (2024). A comparative study of accuracy in major adaptive filters for motion artefact removal in sleep apnea tests. Medical & Biological Engineering & Computing, 62, 829-842. https://doi.org/10.1007/s11517-023-02979-9Publisher
SpringerAdditional Links
https://link.springer.com/article/10.1007/s11517-023-02979-9Type
ArticleDescription
The version of record of this article, first published in [Medical & Biological Engineering & Computing], is available online at Publisher’s website: http://dx.doi.org/10.1007/s11517-023-02979-9ISSN
0140-0118EISSN
1741-0444ae974a485f413a2113503eed53cd6c53
10.1007/s11517-023-02979-9
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