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, 2022, 11
doi: 10.26083/tuprints-00021200
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients |
Language: | English |
Date: | 2022 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2022 |
Publisher: | Springer Nature |
Journal or Publication Title: | Scientific Reports |
Volume of the journal: | 11 |
Collation: | 12 Seiten |
DOI: | 10.26083/tuprints-00021200 |
Corresponding Links: | |
Origin: | Secondary publication via sponsored Golden Open Access |
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. |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-212004 |
Classification DDC: | 600 Technology, medicine, applied sciences > 600 Technology 600 Technology, medicine, applied sciences > 610 Medicine and health |
Divisions: | 18 Department of Electrical Engineering and Information Technology > Artificial Intelligent Systems in Medicine (KISMED) |
Date Deposited: | 03 May 2022 11:19 |
Last Modified: | 23 Aug 2022 07:49 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/21200 |
PPN: | 494177055 |
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