Estimation of respiratory rate from motion contaminated photoplethysmography signals incorporating accelerometry
- Author(s): Delaram Jarchi 1 ; Peter Charlton 2 ; Marco Pimentel 1 ; Alex Casson 3 ; Lionel Tarassenko 1 ; David A. Clifton 1
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View affiliations
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Affiliations:
1:
Department of Engineering Science , Institute of Biomedical Engineering, University of Oxford , Oxford , UK ;
2: School of Medicine, King's College London , London , UK ;
3: School of Electrical and Electronic Engineering, University of Manchester , Manchester , UK
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Affiliations:
1:
Department of Engineering Science , Institute of Biomedical Engineering, University of Oxford , Oxford , UK ;
- Source:
Volume 6, Issue 1,
February
2019,
p.
19 – 26
DOI: 10.1049/htl.2018.5019 , Online ISSN 2053-3713
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Estimation of respiratory rate (RR) from photoplethysmography (PPG) signals has important applications in the healthcare sector, from assisting doctors onwards to monitoring patients in their own homes. The problem is still very challenging, particularly during the motion for large segments of data, where results from different methods often do not agree. The authors aim to propose a new technique which performs motion reduction from PPG signals with the help of simultaneous acceleration signals where the PPG and accelerometer sensors need to be embedded in the same sensor unit. This method also reconstructs motion corrupted PPG signals in the Hilbert domain. An auto-regressive (AR) based technique has been used to estimate the RR from reconstructed PPGs. The proposed method has provided promising results for the estimation of RRs and their variations from PPG signals corrupted with motion artefact. The proposed platform is able to contribute to continuous in-hospital and home-based monitoring of patients using PPG signals under various conditions such as rest and motion states.
Inspec keywords: pneumodynamics; patient monitoring; accelerometers; medical signal processing; photoplethysmography; health care
Other keywords: autoregressive based technique; motion corrupted PPG signals; home-based monitoring; motion artefact; PPG signals; Hilbert domain; motion reduction; simultaneous acceleration signals; rest states; accelerometry; respiratory rate; motion contaminated photoplethysmography signals; motion states; accelerometer sensors; reconstructed PPGs
Subjects: Sensing devices and transducers; Signal processing and detection; Haemodynamics, pneumodynamics; Digital signal processing; Patient diagnostic methods and instrumentation; Optical and laser radiation (medical uses); Optical and laser radiation (biomedical imaging/measurement); Biology and medical computing; Velocity, acceleration and rotation measurement
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