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  5. Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients
 
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2022
Zweitveröffentlichung
Artikel
Verlagsversion

Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients

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Hauptpublikation
s41598-021-87489-0.pdf
CC BY 4.0 International
Format: Adobe PDF
Size: 1.68 MB
TUDa URI
tuda/8601
URN
urn:nbn:de:tuda-tuprints-212004
DOI
10.26083/tuprints-00021200
Autor:innen
Hoog Antink, Christoph ORCID 0000-0001-7948-8181
Mai, Yen
Peltokangas, Mikko
Leonhardt, Steffen
Oksala, Niku
Vehkaoja, Antti
Kurzbeschreibung (Abstract)

Optical heart rate monitoring (OHR) with reflective wrist photoplethysmography is a technique mainly used in the wellness application domain for monitoring heart rate levels during exercise. In the absence of motion, OHR technique is also able to estimate individual beat‑to‑beat intervals relatively well and can therefore also be used, for example, in monitoring of cardiac arrhythmias, stress, or sleep quality through heart rate variability (HRV) analysis. HRV analysis has also potential in monitoring the recovery of patients, e.g. after a medical intervention. However, in order to detect subtle changes, the calculated HRV parameters should be sufficiently accurate and very few studies exist that asses the accuracy of OHR derived HRV in non‑healthy subjects. In this paper, we present a method to estimate beat‑to‑beat‑intervals (BBIs) from reflective wrist PPG signal and evaluated the accuracy of the proposed method in estimating BBIs in a cross‑sectional study with 29 hospitalized patients (mean age 70.6 years) in 24‑h recordings performed after peripheral vascular surgery or endovascular interventions. Finally, we evaluate the accuracy of more than 30 commonly used HRV parameters and find that the accuracy of certain metrics, for example SDNN and triangular index, shown in the literature to be associated with the deterioration of the status of the patients during recovery from surgical intervention, could be adequate for patient monitoring. On the other hand, the parameters more affected by the high‑frequency content of the HRV and especially the LF/HF‑ratio should be used with caution.

Sprache
Englisch
Fachbereich/-gebiet
18 Fachbereich Elektrotechnik und Informationstechnik > Künstlich intelligente Systeme der Medizin (KISMED)
DDC
600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin, Gesundheit
Institution
Universitäts- und Landesbibliothek Darmstadt
Ort
Darmstadt
Titel der Zeitschrift / Schriftenreihe
Scientific Reports
Jahrgang der Zeitschrift
11
ISSN
2045-2322
Verlag
Springer Nature
Publikationsjahr der Erstveröffentlichung
2022
Verlags-DOI
10.1038/s41598-021-87489-0
PPN
494177055
Zusätzliche Links (Verlag)
https://www.nature.com/srep/

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