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

Hoog Antink, Christoph ; Mai, Yen ; Peltokangas, Mikko ; Leonhardt, Steffen ; Oksala, Niku ; Vehkaoja, Antti (2022)
Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients.
In: Scientific Reports, 11
doi: 10.1038/s41598-021-87489-0
Artikel, Bibliographie

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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.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Hoog Antink, Christoph ; Mai, Yen ; Peltokangas, Mikko ; Leonhardt, Steffen ; Oksala, Niku ; Vehkaoja, Antti
Art des Eintrags: Bibliographie
Titel: Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients
Sprache: Englisch
Publikationsjahr: 2022
Verlag: Springer Nature
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Scientific Reports
Jahrgang/Volume einer Zeitschrift: 11
Kollation: 12 Seiten
DOI: 10.1038/s41598-021-87489-0
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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.

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 600 Technik
600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin, Gesundheit
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Künstlich intelligente Systeme der Medizin (KISMED)
Hinterlegungsdatum: 02 Aug 2024 12:40
Letzte Änderung: 02 Aug 2024 12:40
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