Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/108812
Title: Reconstruction of the respiratory signal through ECG and wrist accelerometer data
Author(s): Leube, Julian
Zschocke, JohannesLook up in the Integrated Authority File of the German National Library
Kluge, Maria
Pelikan, Luise
Graf, Antonia
Glos, Martin
Müller, Alexander
Bartsch, Ronny P.
Penzel, ThomasLook up in the Integrated Authority File of the German National Library
Kantelhardt, Jan W.Look up in the Integrated Authority File of the German National Library
Issue Date: 2020
Type: Article
Language: English
Abstract: Respiratory rate and changes in respiratory activity provide important markers of health and fitness. Assessing the breathing signal without direct respiratory sensors can be very helpful in large cohort studies and for screening purposes. In this paper, we demonstrate that long-term nocturnal acceleration measurements from the wrist yield significantly better respiration proxies than four standard approaches of ECG (electrocardiogram) derived respiration. We validate our approach by comparison with flow-derived respiration as standard reference signal, studying the full-night data of 223 subjects in a clinical sleep laboratory. Specifically, we find that phase synchronization indices between respiration proxies and the flow signal are large for five suggested acceleration-derived proxies with γ=0.55±0.13 for males and 0.58±0.14 for females (means ± standard deviations), while ECG-derived proxies yield only γ=0.36±0.16 for males and 0.39±0.14 for females. Similarly, respiratory rates can be determined more precisely by wrist-worn acceleration devices compared with a derivation from the ECG. As limitation we must mention that acceleration-derived respiration proxies are only available during episodes of non-physical activity (especially during sleep).
URI: https://opendata.uni-halle.de//handle/1981185920/110767
http://dx.doi.org/10.25673/108812
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Journal Title: Scientific reports
Publisher: Macmillan Publishers Limited, part of Springer Nature
Publisher Place: [London]
Volume: 10
Issue: 14530
Original Publication: 10.1038/s41598-020-71539-0
Appears in Collections:Open Access Publikationen der MLU

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