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Phase difference between respiration signal and respiratory modulation signal from oscillometric cuff pressure pulses during blood pressure measurement

Lookup NU author(s): Emeritus Professor Alan MurrayORCiD, Dr Dingchang Zheng



This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by IEEE Computer Society, 2016.

For re-use rights please refer to the publisher's terms and conditions.


© 2016 CCAL. Respiration influences the oscillometric cuff pressure waveform from which blood pressure (BP) is estimated. However, there is little information available on the phase shift between reference respiration signal and respiratory modulation signal from oscillometric cuff pressure pulses (OscP) during BP measurement. This study aimed to provide this information and investigate the effect of breathing pattern on the phase difference. Two manual BP measurements were performed on 20 subjects under both normal and deep breathing conditions. During linear cuff deflation, OscP and respiration signal (Resp) were digitally recorded. Respiratory modulation signal was derived from pulse interval of OscP. After filtering the Resp and respiratory modulation signal with a band pass filter, phase shift was calculated by cross spectral analysis, and then compared between the two measurement conditions. Experimental results showed that there was phase shift between Resp and respiratory modulation signal from OscP under both normal (phase difference 0.20±0.09 rad) and regular deep breathing (phase difference 0.64±0.19 rad) conditions. Statistical analysis showed that deep breathing significantly (p<0.05) increased phase shift in comparison with normal breathing. In conclusion, this study demonstrated the presence of phase shift between respiration signal and respiratory modulation signal from OscP during BP measurement and that the phase shift is associated with breathing pattern.

Publication metadata

Author(s): Chen D, Chen F, Murray A, Zheng D

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computing in Cardiology Conference (CinC) 2016

Year of Conference: 2016

Pages: 1013-1016

Online publication date: 02/03/2017

Acceptance date: 02/04/2016

Date deposited: 22/05/2017

ISSN: 2325-887X

Publisher: IEEE Computer Society


Library holdings: Search Newcastle University Library for this item

ISBN: 9781509008964