| Autor: |
Steve Merschel, Lars Reinhardt |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
JMIR Formative Research, Vol 6, Iss 3, p e29479 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2561-326X |
| DOI: |
10.2196/29479 |
| Popis: |
BackgroundContinuous heart rate monitoring via mobile health technologies based on photoplethysmography (PPG) has great potential for the early detection of sustained cardiac arrhythmias such as atrial fibrillation. However, PPG measurements are impaired by motion artifacts. ObjectiveThe aim of this investigation was to evaluate the analyzability of smartwatch-derived PPG data during everyday life and to determine the relationship between the analyzability of the data and the activity level of the participant. MethodsA total of 41 (19 female and 22 male) adults in good cardiovascular health (aged 19-79 years) continuously wore a smartwatch equipped with a PPG sensor and a 3D accelerometer (Cardio Watch 287, Corsano Health BV) for a period of 24 hours that represented their individual daily routine. For each participant, smartwatch data were analyzed on a 1-minute basis by an algorithm designed for heart rhythm analysis (Preventicus Heartbeats, Preventicus GmbH). As outcomes, the percentage of analyzable data (PAD) and the mean acceleration (ACC) were calculated. To map changes of the ACC and PAD over the course of one day, the 24-hour period was divided into 8 subintervals comprising 3 hours each. ResultsUnivariate analysis of variance showed a large effect (ηp2> 0.6; P94%) and the lowest for the ACC ( |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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