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Published on: April 28, 2023
Using the Lomb periodogram for non-contact estimation of respiration rates
1The Institute of Electronics, Communications and Information Technology, Queen's University Belfast, BT3 9DT, Northern Ireland, U.K.
Abstract:
We describe a contact-less method for measurement of respiration rate during sleep using a 5.8GHz radio-frequency bio-motion sensor. The sensor operates by sensing phase shifts in reflected radio waves from the torso caused by respiratory movements and other bodily movements such as twitches, positional changes etc. These non-respiratory motion artefacts can obscure reliable estimation of breathinig rates if conventional spectral analysis is used. This paper reports on the accuracy of the respiration rate estimates obtained via algorithmic approaches using Lomb-periodogram based analysis (which can deal with missing or corrupted data), as compared to conventional spectral analysis. Gold-standard respiration rates are derived by expert scoring of respiration rates measured through polysomnography (PSG) from sensors (Respiratory Inductance Plethysmography (RIP) belts) in contact with the subject in an accredited sleep laboratory. Specifically, respiration rates for 15-minute segments chosen from 10 subjects free of Sleep-Disorded Breathing (AHI〈5) were selected for analysis in this paper. Comparison to the expert annotation indicates strong agreement, with the Lomb-periodogram respiration rates with the average error between the measurements being less than 0.4 breaths/min and a standard deviation of 0.3 breaths/minute. Moreover, we showed that the proposed algorithm could track respiration rate over the complete night's recordings for those 10 subjects. We conclude that the non-contact biomotion sensor may provide a promising approach to continuous respiration rate monitoring of reasonable accuracy.
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