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Pulse interval modulation-based method to extract the respiratory rate from oscillometric cuff pressure waveform during blood pressure measurement
conference contribution
posted on 2023-08-30, 15:33 authored by Yihan Gui, Fei Chen, Alan Murray, Dingchang ZhengRespiratory frequency has been extensively used to assess health status. This study aimed to evaluate two methods of extracting the respiratory rate from oscillometric cuff pressure pulses (OscP) during blood pressure (BP) measurement, which was compared with reference respiration signal (Resp). OscP and Resp were simultaneously recorded on 20 healthy subjects during the linear cuff deflation period of BP measurement. Reference Resp was obtained from a chest magnetometer and OscP from an electronic pressure sensor connected to the cuff. Two de-modulation methods were developed by using the peak or valley positions of the OscP waveform to measure pulse intervals, from which the respiration modulation signal was derived. Statistical analysis showed that, in comparison with the Resp, there was no significant difference (-0.001 Hz for the peak-based method, and 0.001 Hz for valley-based method), and their corresponding limits of agreement were -0.08 Hz to 0.08 Hz and -0.10 Hz to 0.11 Hz, respectively. There was also a high correlation between Resp and respiratory frequencies extracted from OscP waveform, with the correlation coefficients of 0.7 for both methods. In conclusion, the present work demonstrated that, during BP measurement, respiratory frequency can be accurately derived from using either peak or valley point to characterize pulse intervals.
History
Page range
1-4ISSN
2325-887XExternal DOI
Publisher
IEEEPlace of publication
OnlineISBN
978-1-5386-6630-2Conference proceeding
2017 Computing in Cardiology (CinC)Name of event
2017 Computing in Cardiology (CinC)Location
Rennes, FranceEvent start date
2017-09-24Event finish date
2017-09-27File version
- Accepted version
Language
- eng
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Legacy posted date
2018-08-16Legacy creation date
2018-08-15Legacy Faculty/School/Department
ARCHIVED Faculty of Medical Science (until September 2018)Note
© 2017 IEEEUsage metrics
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