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A static algorithm-based method is described here to differentiate between recoverable sedentary respiratory rate data extraneous motion segments measured using Doppler radar. Extraneous motion such as locomotion and fidgeting can cause drastic changes in dc offset and SNR of the received signal. Such extraneous data may not be excluded and can lead to an erroneous assessment of the respiration rate. In some cases, however, moderate distinct extraneous motion does not completely occlude the measurement of respiratory torso motion, allowing for respiration rate recovery. This work focuses on the accurate classification of data which is suitable for respiration rate analysis in the presence of locomotion and small extraneous movements. The proposed algorithm has been demonstrated to be accurate for classifying data with recoverable respiratory rates for 2 subjects and 3 types of fidgets with 99.4% accuracy on average.
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Dynamic Arctangent Center-Tracking Method for Respiratory Displacement Monitoring of Subjects in Arbitrary Positions
Accurate continuous measurement of respiratory displacement using continuous wave Doppler radar requires rigorous management of dc offset which changes when a subject changes distance from the radar measurement system. Effective measurement, therefore, requires robust dynamic calibration which can recognize and compensate for changes in the nominal position of a subject. In this paper, a respiratory displacement measurement algorithm is proposed which can differentiate between sedentary and non-sedentary conditions and continuously adapt to provide long-term monitoring of a subject’s sedentary respiration. Arctangent demodulation is an effective means of quantifying continuous displacement using a quadrature Doppler radar, yet it depends on accurate identification of dc offset and dc information contributions in the radar I-Q arc with the subject in a particular position. The dynamic calibration method proposed here is demonstrated to differentiate between sedentary and non-sedentary conditions for six subjects to produce accurate sedentary respiration measurements even when the subject arbitrarily changes position, once the appropriate thresholds are established for the measurement environment.
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- PAR ID:
- 10547786
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3503-2447-1
- Page Range / eLocation ID:
- 1 to 4
- Subject(s) / Keyword(s):
- Humans Monitoring, Physiologic Respiration Respiratory Rate Radar Algorithms
- Format(s):
- Medium: X
- Location:
- Sydney, Australia
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/EMBC40787.2023.10340361
